kth.sePublications
Change search
Refine search result
1 - 33 of 33
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    B. da Silva Jr., Jose Mairton
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Optimization and Fundamental Insights in Full-Duplex Cellular Networks2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The next generations of cellular networks are expected to provide explosive data rate transmissions and very low latencies. To meet such demands, one of the promising wireless transmissions candidates is in-band full-duplex communications, which enable wireless devices to simultaneously transmit and receive on the same frequency channel. Full-duplex communications have the potential to double the spectral efficiency and reduce the transmission delays when compared to current half-duplex systems that either transmit or receive on the same frequency channel. Until recently, full-duplex communications have been hindered by the interference that leaks from the transmitter to its own receiver,the so-called self-interference. However, advances in digital and analog self-interference suppression techniques are making it possible to reduce the self-interference to manageable levels, and thereby make full-duplex a realistic candidate for advanced wireless systems.

    Although in-band full-duplex promises to double the data rates of existing wireless technologies, its deployment in cellular networks must be gradual due to the large number of legacy devices operating in half-duplex mode. When half-duplex devices are deployed in full-duplex cellular networks, the user-to-user interference may become the performance bottleneck. In such new interference situation, the techniques such as user pairing, frequency channel assignment, power control, beamforming, and antenna splitting become even more important than before, because they are essential to mitigate both the user-to-user interference and the residual self-interference. Moreover, introduction of full- duplex in cellular networks must comply with current multi-antenna systems and, possibly, transmissions in the millimeter-wave bands. In these new scenarios, no comprehensive analysis is available to understand the trade-offs in the performance of full-duplex cellular networks.

    This thesis investigates the optimization and fundamental insights in the design of spectral efficient and fair mechanisms in full-duplex cellular networks. The novel analysis proposed in this thesis suggests new solutions for maximizing full-duplex performance in the sub-6 GHz and millimeter-wave bands. The investigations are based on an optimization theory approach that includes distributed and nonconvex optimization with mixed integer-continuous variables, and novel extensions of Fast-Lipschitz optimization. The analysis sheds lights on fundamental questions such as which antenna architecture should be used and whether full-duplex in the millimeter-wave band is feasible. The results establish fundamental insights in the role of user pairing, frequency assignment, power control and beamforming; reveal the special behaviour between the self-interference and user- to-user interference; analyse the trade-offs between antenna sharing and splitting for uplink/downlink signal separation; and investigate the role of practical beamforming design in full-duplex millimeter-wave systems. This thesis may provide input to future standardization process of full-duplex communications.

    Download full text (pdf)
    MairtonBarros_Doctoral_Thesis
  • 2.
    B. da Silva Jr., Jose Mairton
    KTH, School of Electrical Engineering (EES), Network and Systems engineering.
    Spectral Efficiency and Fairness Maximization in Full-Duplex Cellular Networks2017Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Future cellular networks, the so-called 5G, are expected to provide explosive data volumes and data rates. To meet such a demand, the research communities are investigating new wireless transmission technologies. One of the most promising candidates is in-band full-duplex communications. These communications are characterized by that a wireless device can simultaneously transmit and receive on the same frequency channel. In-band full-duplex communications have the potential to double the spectral efficiencywhen compared to current half duplex systems. The traditional drawback of full-duplex was the interference that leaks from the own transmitter to its own receiver, the so- called self-interference, which renders the receiving signal unsuitable for communication.However, recent advances in self-interference suppression techniques have provided high cancellation and reduced the self-interference to noise floor levels, which shows full-duplex is becoming a realistic technology component of advanced wireless systems.

    Although in-band full-duplex promises to double the data rate of existing wireless technologies, its deployment in cellular networks is challenging due to the large number of legacy devices working in half-duplex. A viable introduction in cellular networks is offered by three-node full-duplex deployments, in which only the base stations are full-duplex, whereas the user- or end-devices remain half-duplex. However, in addition to the inherent self-interference, now the interference between users, the user-to-user interference, may become the performance bottleneck, especially as the capability to suppress self-interference improves. Due to this new interference situation, user pairing and frequency channel assignment become of paramount importance, because both mechanisms can help to mitigate the user-to-user interference. It is essential to understand the trade-offs in the performance of full-duplex cellular networks, specially three-node full-duplex, in the design of spectral and energy efficient as well as fair mechanisms.

    This thesis investigates the design of spectral efficient and fair mechanisms to improve the performance of full-duplex in cellular networks. The novel analysis proposed in this thesis suggests centralized and distributed user pairing, frequency channel assignment and power allocation solutions to maximize the spectral efficiency and fairness in future full-duplex cellular networks. The investigations are based on distributed optimization theory with mixed integer-real variables and novel extensions of Fast-Lipschitz optimization. The analysis sheds lights on two fundamental problems of standard cellular networks, namely the spectral efficiency and fairness maximization, but in the new context of full-duplex communications. The results in this thesis provide important understanding in the role of user pairing, frequency assignment and power allocation, and reveal the special behaviourbetween the legacy self-interference and the new user-to-user interference. This thesis can provide input to the standardization process of full-duplex communications, and have the potential to be used in the implementation of future full-duplex in cellular networks.

    Download full text (pdf)
    fulltext
  • 3.
    B. da Silva Jr., Jose Mairton
    et al.
    KTH, School of Electrical Engineering (EES), Network and Systems engineering.
    Fodor, Gabor
    KTH, School of Electrical Engineering (EES), Automatic Control. Ericsson Research.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Network and Systems engineering.
    Fast-Lipschitz Power Control and User-Frequency Assignment in Full-Duplex Cellular Networks2017In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 16, no 10, p. 6672-6687Article in journal (Refereed)
    Abstract [en]

    In cellular networks, the three-node full-duplex transmission mode has the po-tential to increase spectral efficiency without requiring full-duplex capability ofusers. Consequently, three-node full-duplex in cellular networks must deal with self-interference and user-to-user interference, which can be managed by power controland user-frequency assignment techniques. This paper investigates the problem ofmaximizing the sum spectral efficiency by jointly determining the transmit powersin a distributed fashion, and assigning users to frequency channels. The problem is for-mulated as a mixed-integer nonlinear problem, which is shown to be non-deterministicpolynomial-time hard. We investigate a close-to-optimal solution approach by dividingthe joint problem into a power control problem and an assignment problem. The powercontrol problem is solved by Fast-Lipschitz optimization, while a greedy solution withguaranteed performance is developed for the assignment problem. Numerical resultsindicate that compared with the half-duplex mode, both spectral and energy efficienciesof the system are increased by the proposed algorithm. Moreover, results show that thepower control and assignment solutions have important, but opposite roles in scenarioswith low or high self-interference cancellation. When the self-interference cancellationis high, user-frequency assignment is more important than power control, while powercontrol is essential at low self-interference cancellation.

    Download full text (pdf)
    fd_lipschitz
  • 4.
    B. da Silva Jr., Jose Mairton
    et al.
    KTH, School of Electrical Engineering (EES), Network and Systems engineering.
    Fodor, Gabor
    KTH, School of Electrical Engineering (EES), Automatic Control. Ericsson Research.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Network and Systems engineering.
    On the Spectral Efficiency and Fairness in Full-Duplex Cellular Networks2017In: 2017 IEEE International Conference on Communications (ICC), Paris: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 1-6, article id 7996391Conference paper (Refereed)
    Abstract [en]

    To increase the spectral efficiency of wireless networks without requiring full-duplex capability of user devices, a potential solution is the recently proposed three-node full-duplex mode. To realize this potential, networks employing three-node full-duplex transmissions must deal with self-interference and user-to-user interference, which can be managed by frequency channel and power allocation techniques. Whereas previous works investigated either spectral efficient or fair mechanisms, a scheme that balances these two metrics among users is investigated in this paper. This balancing scheme is based on a new solution method of the multi-objective optimization problem to maximize the weighted sum of the per-user spectral efficiency and the minimum spectral efficiency among users. The mixed integer non-linear nature of this problem is dealt by Lagrangian duality. Based on the proposed solution approach, a low-complexity centralized algorithm is developed, which relies on large scale fading measurements that can be advantageously implemented at the base station. Numerical results indicate that the proposed algorithm increases the spectral efficiency and fairness among users without the need of weighting the spectral efficiency. An important conclusion is that managing user-to-user interference by resource assignment and power control is crucial for ensuring spectral efficient and fair operation of full-duplex networks.

    Download full text (pdf)
    fd_tradeoff
  • 5.
    B. da Silva Jr., Jose Mairton
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Fodor, Gabor
    KTH, School of Electrical Engineering (EES), Automatic Control. Ericsson Research.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Spectral Efficient and Fair User Pairing for Full-Duplex Communication in Cellular Networks2016In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 15, no 11, p. 7578-7593Article in journal (Refereed)
    Abstract [en]

    —A promising new transmission mode in cellular networks is the three-node full-duplex mode, which involves a base station with full-duplex capability and two half-duplex user transmissions on the same frequency channel for uplink and downlink. The three-node full-duplex mode can increase spectral efficiency, especially in the low transmit power regime, without requiring full-duplex capability at user devices. However, when a large set of users is scheduled in this mode, self-interference at the base station and user-to-user interference can substantially hinder the potential gains of full-duplex communications. This paper investigates the problem of grouping users to pairs and assigning frequency channels to each pair in a spectral efficient and fair manner. Specifically, the joint problem of user uplink/downlink frequency channel pairing and power allocation is formulated as a mixed integer nonlinear problem that is solved by a novel joint fairness assignment maximization algorithm. Realistic system level simulations indicate that the spectral efficiency of the users having the lowest spectral efficiency is increased by the proposed algorithm, while a high ratio of connected users in different loads and self-interference levels is maintained.

    Download full text (pdf)
    fd_fairness
  • 6.
    B. da Silva Jr., Jose Mairton
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Ghauch, Hadi
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    How to Split UL/DL Antennas in Full-DuplexCellular Networks2018In: IEEE International Conference on Communication (ICC’18): ThirdWorkshop on Full-Duplex Communications for Future Wireless Networks, Kansas City, MO, USA: IEEE Communications Society, 2018Conference paper (Refereed)
    Abstract [en]

    To further improve the potential of full-duplex com-munications, networks may employ multiple antennas at thebase station or user equipment. To this end, networks thatemploy current radios usually deal with self-interference andmulti-user interference by beamforming techniques. Althoughprevious works investigated beamforming design to improvespectral efficiency, the fundamental question of how to split theantennas at a base station between uplink and downlink infull-duplex networks has not been investigated rigorously. Thispaper addresses this question by posing antenna splitting as abinary nonlinear optimization problem to minimize the sum meansquared error of the received data symbols. It is shown that thisis an NP-hard problem. This combinatorial problem is dealt withby equivalent formulations, iterative convex approximations, anda binary relaxation. The proposed algorithm is guaranteed toconverge to a stationary solution of the relaxed problem with muchsmaller complexity than exhaustive search. Numerical resultsindicate that the proposed solution is close to the optimal in bothhigh and low self-interference capable scenarios, while the usuallyassumed antenna splitting is far from optimal. For large numberof antennas, a simple antenna splitting is close to the proposedsolution. This reveals that the importance of antenna splittingdiminishes with the number of antennas.

  • 7.
    Barros da Silva Jr., Jose Mairton
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Fodor, Gabor
    KTH, School of Electrical Engineering (EES), Automatic Control. Ericsson Research.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Distributed Spectral Efficiency Maximization in Full-Duplex Cellular Networks2016In: IEEE International Conference on Communication (ICC16): Workshop on Novel Medium Access and Resource Allocation for 5G Networks, Kuala Lumpur: IEEE Communications Society, 2016, p. 80-86, article id 7503768Conference paper (Refereed)
    Abstract [en]

    Three-node full-duplex is a promising new transmission mode between a full-duplex capable wireless node and two other wireless nodes that use half-duplex transmission and reception respectively. Although three-node full-duplex transmissions can increase the spectral efficiency without requiring full-duplex capability of user devices, inter-node interference - in addition to the inherent self-interference - can severely degrade the performance. Therefore, as methods that provide effective self-interference mitigation evolve, the management of inter-node interference is becoming increasingly important. This paper considers a cellular system in which a full-duplex capable base station serves a set of half-duplex capable users. As the spectral efficiencies achieved by the uplink and downlink transmissions are inherently intertwined, the objective is to device channel assignment and power control algorithms that maximize the weighted sum of the uplink-downlink transmissions. To this end a distributed auction based channel assignment algorithm is proposed, in which the scheduled uplink users and the base station jointly determine the set of downlink users for full-duplex transmission. Realistic system simulations indicate that the spectral efficiency can be up to 89% better than using the traditional half-duplex mode. Furthermore, when the self-interference cancelling level is high, the impact of the user-to-user interference is severe unless properly managed.

    Download full text (pdf)
    fd_weighted
  • 8.
    Barros da Silva Jr., José Mairton
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Fodor, Gábor
    KTH, School of Electrical Engineering (EES), Automatic Control. Ericsson Research.
    A Binary Power Control Scheme for D2D Communications2015In: IEEE Wireless Communications Letters, ISSN 2162-2337, E-ISSN 2162-2345, Vol. 4, no 6, p. 669-672Article in journal (Refereed)
    Abstract [en]

    Binary power control (BPC) is known to maximize the capacity of a two-cell interference limited system and performs near optimally for larger systems. However, when device-to-device (D2D) communication underlaying the cellular layer is supported, an objective function that considers the power consumption is more suitable. We find that BPC remains optimal for D2D communications when the weight of the overall power consumption in the utility function is bounded. Building on this insight, we propose a simple near-optimal extended BPC scheme and compare its performance with a recently proposed utility optimal iterative scheme using a realistic multicell simulator. Our results indicate that a near optimal D2D performance can be achieved without lengthy iterations or complex signaling mechanisms.

    Download full text (pdf)
    utility_bpc
  • 9.
    Barros da Silva Jr., José Mairton
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering. Royal Inst Technol, KTH, Stockholm, Sweden..
    Ghauch, Hadi
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    How to Split UL/DL Antennas in Full-Duplex Cellular Networks2018In: 2018 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS (ICC WORKSHOPS), IEEE, 2018Conference paper (Refereed)
    Abstract [en]

    To further improve the potential of full-duplex communications, networks may employ multiple antennas at the base station or user equipment. To this end, networks that employ current radios usually deal with self-interference and multi-user interference by beamforming techniques. Although previous works investigated beamforming design to improve spectral efficiency, the fundamental question of how to split the antennas at a base station between uplink and downlink in full-duplex networks has not been investigated rigorously. This paper addresses this question by posing antenna splitting as a binary nonlinear optimization problem to minimize the sum mean squared error of the received data symbols. It is shown that this is an NP-hard problem. This combinatorial problem is dealt with by equivalent formulations, iterative convex approximations, and a binary relaxation. The proposed algorithm is guaranteed to converge to a stationary solution of the relaxed problem with much smaller complexity than exhaustive search. Numerical results indicate that the proposed solution is close to the optimal in both high and low self-interference capable scenarios, while the usually assumed antenna splitting is far from optimal. For large number of antennas, a simple antenna splitting is close to the proposed solution. This reveals that the importance of antenna splitting diminishes with the number of antennas.

  • 10.
    Barros da Silva Jr., José Mairton
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Ghauch, Hadi
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Fodor, Gabor
    Ericsson Research, Kista, Sweden..
    Skoglund, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Smart Antenna Assignment is Essential in Full-Duplex Communications2021In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 69, no 5, p. 3450-3466Article in journal (Refereed)
    Abstract [en]

    Full-duplex communications have the potential to almost double the spectralefficiency. To realize such a potentiality, the signal separation at base station’s antennasplays an essential role. This paper addresses the fundamentals of such separationby proposing a new smart antenna architecture that allows every antenna to beeither shared or separated between uplink and downlink transmissions. The benefitsof such architecture are investigated by an assignment problem to optimally assignantennas, beamforming and power to maximize the weighted sum spectral efficiency.We propose a near-to-optimal solution using block coordinate descent that divides theproblem into assignment problems, which are NP-hard, a beamforming and powerallocation problems. The optimal solutions for the beamforming and power allocationare established while near-to-optimal solutions to the assignment problems are derivedby semidefinite relaxation. Numerical results indicate that the proposed solution isclose to the optimum, and it maintains a similar performance for high and low residualself-interference powers. With respect to the usually assumed antenna separationtechnique and half-duplex transmission, the sum spectral efficiency gains increase withthe number of antennas. We conclude that our proposed smart antenna assignment forsignal separation is essential to realize the benefits of multiple antenna full-duplexcommunications.

  • 11.
    Barros da Silva Jr., José Mairton
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Ntougias, Konstantinos
    University of Cyprus.
    Krikidis, Ioannis
    University of Cyprus.
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Simultaneous Wireless Information and PowerTransfer for Federated Learning2021In: IEEE 22nd International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Lucca, Italy, Sep. 2021, IEEE Communications Society, 2021, p. 296-300Conference paper (Refereed)
    Abstract [en]

    In the Internet of Things, learning is one of most prominent tasks. In this paper, we consider an Internet of Things scenario where federated learning is used with simultaneous transmission of model data and wireless power. We investigate the trade-off between the number of communication rounds and communication round time while harvesting energy to compensate the energy expenditure. We formulate and solve an optimization problem by considering the number of local iterations on devices, the time to transmit-receive the model updates, and to harvest sufficient energy. Numerical results indicate that maximum ratio transmission and zero-forcing beamforming for the optimization of the local iterations on devices substantially boost the test accuracy of the learning task. Moreover, maximum ratio transmission instead of zero-forcing provides the best test accuracy and communication round time trade-off for various energy harvesting percentages. Thus, it is possible to learn a model quickly with few communication rounds without depleting the battery.

  • 12.
    Barros da Silva Jr., José Mairton
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Sabharwal, Ashutosh
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). Ericsson Res, S-16480 Stockholm, Sweden.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    1-bit Phase Shifters for Large-Antenna Full-Duplex mmWave Communications2020In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 19, no 10, p. 6916-6931Article in journal (Refereed)
    Abstract [en]

    Millimeter-wave using large-antenna arrays is a key technological component forthe future cellular systems, where it is expected that hybrid beamforming along withquantized phase shifters will be used due to their implementation and cost efficiency.In this paper, we investigate the efficacy of full-duplex mmWave communicationwith hybrid beamforming using low-resolution phase shifters, without any analogself-interference cancellation. We formulate the problem of joint self-interferencesuppression and downlink beamforming as a mixed-integer nonconvex joint opti-mization problem. We propose LowRes, a near-to-optimal solution using penaltydual decomposition. Numerical results indicate that LowRes using low-resolutionphase shifters perform within 3% of the optimal solution that uses infinite phaseshifter resolution. Moreover, even a single quantization bit outperforms half-duplextransmissions, respectively by 29% and 10% for both low and high residual self-interference scenarios, and for a wide range of practical antenna to radio-chain ratios.Thus, we conclude that 1-bit phase shifters suffice for full-duplex millimeter-wavecommunications, without requiring any additional new analog hardware.

  • 13.
    Barros da Silva Jr., José Mairton
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Sabharwal, Ashutosh
    Rice Univ, Houston, TX USA..
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). Ericsson Res, Kista, Sweden..
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Low Resolution Phase Shifters Suffice for Full-Duplex mmWave Communications2019In: 2019 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS (ICC WORKSHOPS), IEEE , 2019Conference paper (Refereed)
    Abstract [en]

    Full-duplex base-stations with half-duplex nodes, allowing simultaneous uplink and downlink from different nodes, have the potential to double the spectrum efficiency without adding additional complexity at mobile nodes. Hybrid beam forming is commonly used in millimeter wave systems for its implementation efficiency. An important element of hybrid beam-forming is quantized phase shifters. In this paper, we ask if low-resolution phase shifters suffice for beamforming-based full-duplex millimeter wave systems. We formulate the problem of joint design for both self-interference suppression and downlink beamforming as an optimization problem, which we solve using penalty dual decomposition to obtain a near-optimal solution. Numerical results indicate that low-resolution phase shifters can perform close to systems that use infinite phase shifter resolution, and that even a single quantization bit outperforms half-duplex transmissions in both low and high residual self-interference scenarios.

  • 14.
    Barros da Silva Jr., José Mairton
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Skouroumounis, Christodoulos
    University of Cyprus.
    Krikidis, Ioannis
    University of Cyprus.
    Fodor, Gabor
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Energy Efficient Full-Duplex Networks2020In: Green Communications for Energy-Efficient Wireless Systems and Networks / [ed] H. Suraweera, J. Yang, A. Zappone, J. S. Thompson, The Institution of Engineering and Technology (IET) , 2020Chapter in book (Refereed)
    Abstract [en]

    As the specifications of the 5th generation of cellular networks mature, the deployment phase is starting up. Hence, peaks of data rates in the order of tens of Gbit/s as well as more energy efficient deployments are expected. Nevertheless, the quick development of new applications and services encourage the research community to look beyond 5G and explore new technological components. Indeed, to meet the increasing demand for mobile broadband as well as internet of things type of services, the research and standardization communities are currently investigating novel physical and medium access layer technologies, including further virtualization of networks, the use of the lower Terahertz bands, even higher cell densification, and full-duplex (FD) communications.

     

    FD has been proposed as one of the enabling technologies to increase the spectral efficiency of conventional wireless transmission modes, by overcoming our prior understanding that it is not possible for radios to transmit and receive simultaneously on the same time-frequency resource. Due to this, we can also refer to FD communications as in-band FD. In-band FD transceivers have the potential of improving the attainable spectral efficiency of traditional wireless networks operating with half-duplex (HD) transceivers by a factor close to two. In addition to the spectral efficiency gains, full-duplex can provide gains in the medium access control layer, in which problems such as the hidden/exposed nodes and collision detection can be mitigated and the energy consumption can be reduced.

     

    Until recently, in-band FD was not considered as a solution for wireless networks due to the inherent interference created from the transmitter to its own receiver, the so-called self-interference (SI). However, recent advancements in antenna and analog/digital interference cancellation techniques demonstrate FD transmissions as a viable alternative to traditional HD transmissions. Given the recent architectural progression of 5G towards smaller cells, higher densification, higher number of antennas and utilizing the millimeter wave (mmWave) band, the integration of FD communications into such scenarios is appealing. In-band FD communications are suited for short range communication, and although the SI remains a challenge, the use of multiple antennas and the transmission in the mmWave band are allies that help to mitigate the SI in the spatial domain and provide even more gains for spectral and energy efficiency. To achieve the spectral and energy efficiency gains, it is important to understand the challenges and solutions, which can be roughly divided into resource allocation, protocol design, hardware design and energy harvesting. Hence, FD communications appears as an important technology component to improve the spectral and energy efficiency of current communication systems and help to meet the goals of 5G and beyond.

     

    The chapter starts with an overview of FD communications, including its challenges and solutions. Next, a comprehensive literature review of energy efficiency in FD communications is presented along with the key solutions to improve energy efficiency. Finally, we evaluate the key aspects of energy efficiency in FD communications for two scenarios: single-cell with multiple users in a pico-cell scenario, and a system level evaluation with macro- and small-cells with multiple users.

  • 15.
    Barros da Silva Jr., José Mairton
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Wikström, Gustav
    Mungara, Ratheesh K.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Full-Duplex and Dynamic-TDD: Pushing the Limits of Spectrum Reuse in Multi-Cell Communications2021In: IEEE wireless communications, ISSN 1536-1284, E-ISSN 1558-0687, ISSN 1536-1284, Vol. 28, no 1, p. 44-50Article in journal (Refereed)
    Abstract [en]

    Although in cellular networks full duplex and dynamic time-division duplexing promise increased spectrum efficiency, their potential is so far challenged by increased interference. While previous studies have shown that self-interference can be suppressed to a sufficient level, we show that the cross-link interference for both duplexing modes, especially from base station to base station, is the remaining challenge in multi-cell networks, restricting the uplink performance. Using beamforming techniques of low complexity, we show that this interference can be mitigated, and that full duplex and dynamic time-division duplexing can substantially increase the capacity of multi-cell networks. Our results suggest that if we can control the cross-link interference in full duplex, we can almost double the multi-cell network capacity as well as user throughput. Therefore, the techniques in this article have the potential to enable a smooth introduction of full duplex into cellular systems.

  • 16.
    Fodor, Gábor
    et al.
    Ericsson Research, Sweden.
    Roger, Sandra
    Rajatheva, Nandana
    Ben Slimane, Slimane
    KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS, Radio Systems Laboratory (RS Lab).
    Svensson, Tommy
    Popovski, Petar
    B. da Silva Jr., Jose Mairton
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Ali, Samad
    An Overview of Device-to-Device Communications Technology Components in METIS2016In: IEEE Access, E-ISSN 2169-3536, Vol. 4, p. 3288-3299Article in journal (Refereed)
    Abstract [en]

    As the standardization of network-assisted deviceto-device (D2D) communications by the 3 rd Generation Partnership Project progresses, the research community has started to explore the technology potential of new advanced features that will largely impact the performance of 5G networks. For 5G, D2D is becoming an integrative term of emerging technologies that take advantage of the proximity of communicating entities in licensed and unlicensed spectra. The European 5G research project Mobile and Wireless Communication Enablers for the 2020 Information Society (METIS) has identified advanced D2D as a key enabler for a variety of 5G services, including cellular coverage extension, social proximity and communicating vehicles. In this paper, we review the METIS D2D technology components in three key areas of proximal communications – network-assisted multi-hop, full-duplex, and multi-antenna D2D communications – and argue that the advantages of properly combining cellular and ad hoc technologies help to meet the challenges of the information society beyond 2020.

  • 17.
    Giupponil, Lorenza
    et al.
    Ericsson, Spain.
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). Ericsson AB, Sweden.
    Ambede, Abhishek
    Ericsson AB, Sweden.
    Hui, Dennis
    Ericsson, Santa Clara, CA, USA.
    Göransson, Bo
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering. Ericsson AB, Sweden.
    Barros da Silva Jr., José Mairton
    Uppsala University, Uppsala, Sweden.
    Sub-Band Full-Duplex for 5G New Radio: Challenges, Solutions and Performance2023In: Conference Record of the 57th Asilomar Conference on Signals, Systems and Computers, ACSSC 2023, Institute of Electrical and Electronics Engineers (IEEE) , 2023, p. 167-173Conference paper (Refereed)
    Abstract [en]

    Recently, multiple works in the literature have presented encouraging results on the feasibility of in-band full-duplex (IBFD) communications in point-to-point and single cell arrangements, where the IBFD capability is provided by the base station. However, in multi-cell networks, in addition to high self-interference, full-duplex operations also face the severe problems of base station-to-base station cross-link interference (CLI), inter-sector CLI, user equipment-to-user equipment CLI, and inter-operator interference. Due to these difficulties, the research and engineering communities have recently proposed to adopt sub-band full-duplex (SBFD), as an intermediary step towards IBFD in the evolution of 5G New Radio systems. With SBFD, cellular base stations may operate the downlink and uplink on different non-overlapping frequency sub-bands within a time division duplexing carrier, which helps reduce self-interference and CLI due to the frequency isolation between the uplink and downlink sub-bands. In this paper, we focus on Frequency Range 1 operation, investigate the novel SBFD concept, and compare it to traditional time division duplexing, using realistic assumptions on multi-cell deployments, adjacent channel leakage, CLI and self-interference cancellation techniques. Our results indicate that SBFD operation may primarily be a candidate for low power deployments, with complexity and feasibility challenges in scenarios using high base station transmission power, sectorization, and in the presence of multiple operators.

  • 18.
    Hellström, Henrik
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Barros da Silva Jr., José Mairton
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Amiri, Mohammad Mohammadi
    Massachusetts Institute of Technology.
    Chen, Mingzhe
    Princeton University.
    Fodor, Viktória
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Poor, H. Vincent
    Princeton University.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Wireless for Machine Learning: A Survey2022In: Foundations and Trends in Signal Processing, ISSN 1932-8346, Vol. 15, no 4, p. 290-399Article, review/survey (Refereed)
    Abstract [en]

    As data generation increasingly takes place on devices withouta wired connection, Machine Learning (ML) related traffic willbe ubiquitous in wireless networks. Many studies have shownthat traditional wireless protocols are highly inefficient or unsustainableto support ML, which creates the need for new wirelesscommunication methods. In this monograph, we give a comprehensivereview of the state-of-the-art wireless methods that arespecifically designed to support ML services over distributeddatasets. Currently, there are two clear themes within the literature,analog over-the-air computation and digital radio resourcemanagement optimized for ML. This survey gives an introductionto these methods, reviews the most important works, highlightsopen problems, and discusses application scenarios.

    Download full text (pdf)
    fulltext
  • 19.
    Kant, Shashi
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering. Ericsson AB.
    Barros da Silva Jr., José Mairton
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering. Princeton University, Princeton, NJ, USA,.
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). Ericsson AB.
    Göransson, Bo
    KTH, School of Electrical Engineering and Computer Science (EECS). Ericsson AB.
    Bengtsson, Mats
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Federated Learning using Three-Operator ADMMManuscript (preprint) (Other academic)
  • 20.
    Kant, Shashi
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering. Ericsson AB.
    Barros da Silva Jr., José Mairton
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering. Princeton University, Princeton, NJ, USA.
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). Ericsson AB.
    Göransson, Bo
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering. Ericsson AB.
    Bengtsson, Mats
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Federated Learning Using Three-Operator ADMM2023In: IEEE Journal on Selected Topics in Signal Processing, ISSN 1932-4553, E-ISSN 1941-0484, Vol. 17, no 1, p. 205-221Article in journal (Refereed)
    Abstract [en]

    Federated learning (FL) has emerged as an instance of distributed machine learning paradigm that avoids the transmission of data generated on the users' side. Although data are not transmitted, edge devices have to deal with limited communication bandwidths, data heterogeneity, and straggler effects due to the limited computational resources of users' devices. A prominent approach to overcome such difficulties is FedADMM, which is based on the classical two-operator consensus alternating direction method of multipliers (ADMM). The common assumption of FL algorithms, including FedADMM, is that they learn a global model using data only on the users' side and not on the edge server. However, in edge learning, the server is expected to be near the base station and have direct access to rich datasets. In this paper, we argue that leveraging the rich data on the edge server is much more beneficial than utilizing only user datasets. Specifically, we show that the mere application of FL with an additional virtual user node representing the data on the edge server is inefficient. We propose FedTOP-ADMM, which generalizes FedADMM and is based on a three-operator ADMM-type technique that exploits a smooth cost function on the edge server to learn a global model parallel to the edge devices. Our numerical experiments indicate that FedTOP-ADMM has substantial gain up to 33% in communication efficiency to reach a desired test accuracy with respect to FedADMM, including a virtual user on the edge server.

  • 21.
    Kim, Yeongwoo
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering. Ericsson Res, Stockholm, Sweden..
    Al Hakim, Ezeddin
    Ericsson Res, Stockholm, Sweden..
    Haraldson, Johan
    Ericsson Res, Stockholm, Sweden..
    Eriksson, Henrik
    Ericsson Res, Stockholm, Sweden..
    Barros Da Silva Junior, José Mairton
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Dynamic Clustering in Federated Learning2021In: ICC 2021 - IEEE International Conference on Communications, Institute of Electrical and Electronics Engineers (IEEE) , 2021Conference paper (Refereed)
    Abstract [en]

    In the resource management of wireless networks, Federated Learning has been used to predict handovers. However, non-independent and identically distributed data degrade the accuracy performance of such predictions. To overcome the problem, Federated Learning can leverage data clustering algorithms and build a machine learning model for each cluster. However, traditional data clustering algorithms, when applied to the handover prediction, exhibit three main limitations: the risk of data privacy breach, the fixed shape of clusters, and the non-adaptive number of clusters. To overcome these limitations, in this paper, we propose a three-phased data clustering algorithm, namely: generative adversarial network-based clustering, cluster calibration, and cluster division. We show that the generative adversarial network-based clustering preserves privacy. The cluster calibration deals with dynamic environments by modifying clusters. Moreover, the divisive clustering explores the different number of clusters by repeatedly selecting and dividing a cluster into multiple clusters. A baseline algorithm and our algorithm are tested on a time series forecasting task. We show that our algorithm improves the performance of forecasting models, including cellular network handover, by 43%.

  • 22. Li, Zexian
    et al.
    Moya, Fernando Sanchez
    Fodor, Gabor
    KTH, School of Electrical Engineering (EES), Automatic Control.
    B. da Silva Jr., Jose Mairton
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Koufos, Konstantinos
    Device-to-device (D2D) communications2016In: 5G Mobile and Wireless Communications Technology / [ed] Osseiran, A; Marsch, P; Monserrat, J F, Cambridge: Cambridge U Press , 2016, p. 107-136Chapter in book (Other academic)
  • 23.
    Lopes Batista, Rodrigo
    et al.
    Federal University of Ceará (UFC).
    F. M. e Silva, Carlos
    Federal University of Ceará (UFC).
    F. Maciel, Tarcisio
    Federal University of Ceará (UFC).
    B. da Silva Jr., Jose Mairton
    KTH, School of Electrical Engineering (EES), Network and Systems engineering.
    P. Cavalcanti, Fco. Rodrigo
    Federal University of Ceará (UFC).
    Joint Opportunistic Scheduling of Cellular and Device-to-Device Communications2017In: Journal of communication and information systems, ISSN 1980-6604Article in journal (Refereed)
    Abstract [en]

    The joint scheduling of cellular and D2D communications to share the same radio resource is a complex task.

    In one hand, D2D links provide very high throughputs. In the other hand, the intra-cell interference they cause impacts on the performance of cellular communications.

    Therefore, designing algorithms and mechanisms that allow an efficient reuse of resources by the D2D links with a reduced impact on cellular communications is a key problem.

    In general, traditional Radio Resource Management (RRM) schemes (D2D grouping and mode selection) focus on finding the most compatible D2D pair for an already scheduled cellular User Equipment (UE).

    However, such approach limits the number of possible combinations to form the group (composed by a cellular UE and a D2D pair) to be scheduled in the radio resource.

    To overcome that, in this work a unified Joint Opportunistic Scheduling (JOS) of cellular and D2D communications, which is able to improve the total system throughput by exploiting the spatial compatibility among cellular and D2D UEs, is proposed.

    But more complexity is brought to the scheduling problem.

    Thus, a low-complexity suboptimal heuristic Joint Opportunistic Assignment and Scheduling (JOAS) is also elaborated.

    Results show that it is possible to reduce the computational complexity but still improve the overall performance in terms of cellular fairness and total system throughput with less impact on cellular communications.

  • 24.
    Mahmoudi, Afsaneh
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Barros da Silva Jr., José Mairton
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering. Princeton University, NJ, USA.
    Ghadikolaei, Hossein S.
    Ericsson, Stockholm, Sweden.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    A-LAQ: Adaptive Lazily Aggregated Quantized Gradient2022In: 2022 IEEE GLOBECOM Workshops, GC Wkshps 2022: Proceedings, Institute of Electrical and Electronics Engineers (IEEE) , 2022, p. 1828-1833Conference paper (Refereed)
    Abstract [en]

    Federated Learning (FL) plays a prominent role in solving machine learning problems with data distributed across clients. In FL, to reduce the communication overhead of data between clients and the server, each client communicates the local FL parameters instead of the local data. However, when a wireless network connects clients and the server, the communication resource limitations of the clients may prevent completing the training of the FL iterations. Therefore, communication-efficient variants of FL have been widely investigated. Lazily Aggregated Quantized Gradient (LAQ) is one of the promising communication-efficient approaches to lower resource usage in FL. However, LAQ assigns a fixed number of bits for all iterations, which may be communication-inefficient when the number of iterations is medium to high or convergence is approaching. This paper proposes Adaptive Lazily Aggregated Quantized Gradient (A-LAQ), which is a method that significantly extends LAQ by assigning an adaptive number of communication bits during the FL iterations. We train FL in an energy-constraint condition and investigate the convergence analysis for A-LAQ. The experimental results highlight that A-LAQ outperforms LAQ by up to a 50% reduction in spent communication energy and an 11% increase in test accuracy.

  • 25.
    Mahmoudi, Afsaneh
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Barros da Silva Jr., José Mairton
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering. Princeton University, NJ, USA.
    Shokri-Ghadikolaei, Hossein
    Ericsson, Stockholm, Sweden.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    A-LAQ: Adaptive Lazily Aggregated Quantized GradientManuscript (preprint) (Other (popular science, discussion, etc.))
    Abstract [en]

    Federated Learning~(FL) plays a prominent role in solving machine learning problems with data distributed across clients. In FL, to reduce the communication overhead of data between clients and the server, each client communicates the local FL parameters instead of the local data. However, when a wireless network connects clients and the server, the communication resource limitations of the clients may prevent completing the training of the FL iterations. Therefore, communication-efficient variants of FL have been widely investigated. Lazily Aggregated Quantized Gradient~(LAQ) is one of the promising communication-efficient approaches to lower resource usage in FL. However, LAQ assigns a fixed number of bits for all iterations, which may be communication-inefficient when the number of iterations is medium to high or convergence is approaching. This paper proposes Adaptive Lazily Aggregated Quantized Gradient~(A-LAQ), which is a method that significantly extends LAQ by assigning an adaptive number of communication bits during the FL iterations. We train FL in an energy-constraint condition and investigate the convergence analysis for A-LAQ. The experimental results highlight that A-LAQ outperforms LAQ by up to a $50$\% reduction in spent communication energy and an $11$\% increase in test accuracy.

    Download full text (pdf)
    fulltext
  • 26.
    Mahmoudi, Afsaneh
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Shokri-Ghadikolaei, Hossein
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Barros da Silva Jr., José Mairton
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    FedCau: A Proactive Stop Policy for Communication and Computation Efficient Federated LearningManuscript (preprint) (Other academic)
    Download full text (pdf)
    fulltext
  • 27.
    Razavikia, Saeed
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Barros da Silva Jr., José Mairton
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Blind Federated Learning via Over-the-Air q-QAMManuscript (preprint) (Other academic)
    Abstract [en]

    In this work, we investigate federated edge learning over a fading multiple access channel. To alleviate the communication burden between the edge devices and the access point, we introduce a pioneering digital over-the-air computation strategy employing q-ary quadrature amplitude modulation, culminating in a low latency communication scheme. Indeed, we propose a new federated edge learning framework in which edge devices use digital modulation for over-the-air uplink transmission to the edge server while they have no access to the channel state information. Furthermore, we incorporate multiple antennas at the edge server to overcome the fading inherent in wireless communication.  We analyze the number of antennas required to mitigate the fading impact effectively. We prove a non-asymptotic upper bound for the mean squared error for the proposed federated learning with digital over-the-air uplink transmissions under both noisy and fading conditions.  Leveraging the derived upper bound, we characterize the convergence rate of the learning process of a non-convex loss function in terms of the mean square error of gradients due to the fading channel. Furthermore, we substantiate the theoretical assurances through numerical experiments concerning mean square error and the convergence efficacy of the digital federated edge learning framework. Notably, the results demonstrate that augmenting the number of antennas at the edge server and adopting higher-order modulations improve the model accuracy up to $60\%$.

  • 28.
    Razavikia, Saeed
    et al.
    Princeton University, Department of Electrical and Computer Engineering, New Jersey, USA.
    Barros da Silva Jr., José Mairton
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering. Princeton University, Department of Electrical and Computer Engineering, New Jersey, USA.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Computing Functions Over-the-Air Using Digital Modulations2023In: ICC 2023: IEEE International Conference on Communications: Sustainable Communications for Renaissance, Institute of Electrical and Electronics Engineers Inc. , 2023, Vol. 2023, p. 5780-5786Conference paper (Refereed)
    Abstract [en]

    Over-the-air computation (AirComp) is a known technique in which wireless devices transmit values by analog amplitude modulation so that a function of these values is computed over the communication channel at a common receiver. The physical reason is the superposition properties of the electromagnetic waves, which naturally return sums of analog values. Consequently, the applications of AirComp are almost entirely restricted to analog communication systems. However, the use of digital communications for over-the-air computations would have several benefits, such as error correction, synchronization, acquisition of channel state information, and easier adoption by current digital communication systems. Nevertheless, a common belief is that digital modulations are generally unfeasible for computation tasks because the overlapping of digitally modulated signals returns signals that seem to be meaningless for these tasks. This paper breaks through such a belief and proposes a fundamentally new computing method, named ChannelComp, for performing over-the-air computations by any digital modulation. In particular, we propose digital modulation formats that allow us to compute a wider class of functions than AirComp can compute, and we propose a feasibility optimization problem that ascertains the optimal digital modulation for computing functions over-the-air. The simulation results verify the superior performance of ChannelComp in comparison to AirComp, particularly for the product functions, with around 10 dB improvement of the computation error.

  • 29.
    Razavikia, Saeed
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Barros da Silva Jr., José Mairton
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    SumComp: Coding for Digital Over-the-AirComputation via the Ring of IntegersManuscript (preprint) (Other academic)
    Abstract [en]

    Communication and computation are traditionally treated as separate entities, allowing for individual optimizations. However, many applications focus on local information's functionality rather than the information itself. For such cases, harnessing interference for computation in a multiple access channel through digital over-the-air computation can notably increase the computation, as established by the ChannelComp method. However, the coding scheme originally proposed in ChannelComp may suffer from high computational complexity because it is general and is not optimized for specific modulation categories. Therefore, this study considers a specific category of digital modulations for over-the-air computations, QAM and PAM, for which we introduce a novel coding scheme called SumComp.

    Furthermore, we derive an MSE analysis for SumComp coding in the computation of the arithmetic mean function and establish an upper bound on the MAE for a set of nomographic functions. Simulation results affirm the superior performance of SumComp coding compared to traditional analog over-the-air computation and the original coding in ChannelComp approaches regarding both MSE and MAE over a noisy multiple access channel. Specifically, SumComp coding shows approximately 10 dB improvements for computing arithmetic and geometric mean on the normalized MSE for low-noise scenarios.

  • 30.
    Razavikia, Saeed
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Da Silva, José Mairton Barros
    Department of Information Technology, Uppsala University, Sweden.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    ChannelComp: A General Method for Computation by Communications2023In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, p. 1-1Article in journal (Refereed)
    Abstract [en]

    Over-the-air computation (AirComp) is a well-known technique by which several wireless devices transmit by analog amplitude modulation to achieve a sum of their transmit signals at a common receiver. The underlying physical principle is the superposition property of the radio waves. Since such superposition is analog and in amplitude, it is natural that AirComp uses analog amplitude modulations. Unfortunately, this is impractical because most wireless devices today use digital modulations. It would be highly desirable to use digital communications because of their numerous benefits, such as error correction, synchronization, acquisition of channel state information, and widespread use. However, when we use digital modulations for AirComp, a general belief is that the superposition property of the radio waves returns a meaningless overlapping of the digital signals. In this paper, we break through such beliefs and propose an entirely new digital channel computing method named ChannelComp, which can use digital as well as analog modulations. We propose a feasibility optimization problem that ascertains the optimal modulation for computing arbitrary functions over-the-air. Additionally, we propose pre-coders to adapt existing digital modulation schemes for computing the function over the multiple access channel. The simulation results verify the superior performance of ChannelComp compared to AirComp, particularly for the product functions, with more than 10 dB improvement of the computation error.

  • 31.
    Razavikia, Saeed
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Peris, Jaume Anguera
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Barros da Silva Jr., José Mairton
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering. Princeton University, Department of Electrical and Computer Engineering, New Jersey, USA.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Blind Asynchronous Over-the-Air Federated Edge Learning2022In: 2022 IEEE GLOBECOM Workshops, GC Wkshps 2022: Proceedings, Institute of Electrical and Electronics Engineers (IEEE) , 2022, p. 1834-1839Conference paper (Refereed)
    Abstract [en]

    Federated Edge Learning (FEEL) is a distributed machine learning technique where each device contributes to training a global inference model by independently performing local computations with their data. More recently, FEEL has been merged with over-the-air computation (OAC), where the global model is calculated over the air by leveraging the superposition of analog signals. However, when implementing FEEL with OAC, there is the challenge on how to precode the analog signals to overcome any time misalignment at the receiver. In this work, we propose a novel synchronization-free method to recover the parameters of the global model over the air without requiring any prior information about the time misalignments. For that, we construct a convex optimization based on the norm minimization problem to directly recover the global model by solving a convex semi-definite program. The performance of the proposed method is evaluated in terms of accuracy and convergence via numerical experiments. We show that our proposed algorithm is close to the ideal synchronized scenario by 10%, and performs 4times better than the simple case where no recovering method is used.

  • 32.
    Sousa, Diego Perdigão
    et al.
    Federal University of Ceara.
    Du, Rong
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering. Ericsson Research.
    B. da Silva Jr., Jose Mairton
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Cavalcante, Charles Casimiro
    Federal University of Ceara.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Leakage Detection In Water Distribution Networks: Efficient Training By Data Clustering2022In: IWA World Water Congress & Exhibition, Sep. 2022, IWA Publishing, 2022Conference paper (Refereed)
    Abstract [en]

    This work proposes a reliable leakage detection methodology for water distribution networks based on machine learning techniques. The design is developed through real data acquisition from a municipal area of a water distribution network. We propose to combine both unsupervised learning (K-means and cluster validation techniques) and supervised learning (LVQ-type algorithms) for the efficient design of prototype-based classifiers. We investigated several metrics aiming to define the optimal number of clusters, in which we succeeded in reporting attractive classification accuracies (approximately 90%) on scenarios of severely limited number of prototypes.

  • 33.
    Sousa, Diego Perdigão
    et al.
    Department of Teleinformatics Engineering, Federal University of Ceara, Fortaleza, Brazil.
    Du, Rong
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Barros da Silva Jr., José Mairton
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering. Department of Electrical and Computer Engineering, Princeton University, Princeton, USA.
    Cavalcante, Charles Casimiro
    Department of Teleinformatics Engineering, Federal University of Ceara, Fortaleza, Brazil.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Leakage detection in water distribution networks using machine-learning strategies2023In: Water Science and Technology: Water Supply, ISSN 1606-9749, E-ISSN 1607-0798, Vol. 23, no 3, p. 1115-1126Article in journal (Refereed)
    Abstract [en]

    This work proposes a reliable leakage detection methodology for water distribution networks (WDNs) using machine-learning strategies. Our solution aims at detecting leakage in WDNs using efficient machine-learning strategies. We analyze pressure measurements from pumps in district metered areas (DMAs) in Stockholm, Sweden, where we consider a residential DMA of the water distribution network. Our proposed methodology uses learning strategies from unsupervised learning (K-means and cluster validation techniques), and supervised learning (learning vector quantization algorithms). The learning strategies we propose have low complexity, and the numerical experiments show the potential of using machine-learning strategies in leakage detection for monitored WDNs. Specifically, our experiments show that the proposed learning strategies are able to obtain correct classification rates up to 93.98%.

1 - 33 of 33
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf