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  • 1.
    Chang, Peiliang
    KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Radio Systems Laboratory (RS Lab).
    Cross-Layer Energy-Efficient Mobile Network Design2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    To assure the sustainable development of mobile networks, it is crucial to improve their energy efficiency. This thesis is devoted to the design of energy-efficient mobile networks. A cross-layer design approach is adopted. The resource management at the MAC layer, the network layer as well as the service layer are optimized to improve the energy efficiency of mobile networks. The problem of optimizing the MAC-layer resource allocation of the downlink transmission in multi-carrier NOMA systems to maximize the system energy efficiency while satisfying users’ QoS requirements is firstly considered. The optimal power allocation across sub-carriers and across users sharing one sub-carrier are proposed. Furthermore, exploiting the structure of the optimal power allocation across users sharing one sub-carrier, a sub-optimal solution for sub-carrier assignment, which greedily minimizes the required power to serve all users with required QoS, is developed. Besides optimizing the channel assignment and power allocation within a single cell, the link scheduling in the multi-cell scenario to deal with inter-cell interference is also studied. A scalable distributed link scheduling solution is proposed to orchestrate the transmission and DTX micro-sleep of multiple base stations such that both the inter-cell interference and the energy consumption are reduced. At the network layer, the operation of base station sleeping is optimized to improve the energy efficiency of mobile networks without deteriorating users’ QoS. The spectral and energy efficiency of mobile networks, where base stations are enabled with DTX, under different traffic load is firstly studied. It shows that as the networks are more loaded, the link spectral efficiency reduces while the network spectral efficiency increases. Regarding the network energy efficiency, it will either firstly increase and then decrease or always increase when the network load gets higher. The optimal network load to maximize the network energy efficiency depends on the power consumption of base stations in DTX sleep mode. Based on the findings of the above study, the joint optimization of cell DTX and deep sleep to maximize the network energy efficiency is investigated. A scaling law of transmit power, which assures that the distribution of the received power remains unchanged as more base stations are switched into deep sleep, is proposed. Then the average resource utilization and overload probability of non-deep-sleep base stations are derived. Based on these results, the feasible range of the percentage of deep-sleep base stations is obtained. Finally, the optimal percentage of deep-sleep base stations to maximize the network energy efficiency while satisfying users’ QoS requirements is derived. Lastly, the service-layer resource provision of edge computing in mobile networks is optimized to improve the energy efficiency. With this work, the trade-offs on service latency and energy consumption between the computation and the communication subsystems are studied. It is shown that the load of the communication subsystem and that of the computation subsystem should be balanced. Increasing the resource of the highly loaded subsystem can significantly reduce the required resource of the other subsystem. An algorithm is proposed to find out the optimal processing speed and the optimal number of active base stations that minimizes the overall energy consumption while assuring the requirements on the mean service latency.

  • 2.
    Chang, Peiliang
    et al.
    KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS, Radio Systems Laboratory (RS Lab).
    Miao, Guowang
    KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS, Radio Systems Laboratory (RS Lab).
    Area Spectral and Energy Efficiency Analysis of Cellular Networks with Cell DTX2015In: IEEE Globecom 2015 , San Diego, December 6th-10th, 2015, IEEE conference proceedings, 2015, p. 1-6Conference paper (Refereed)
    Abstract [en]

    Cell discontinuous transmission (DTX) has been proposed as an effective solution to reduce energy consumption of cellular networks. In this paper, we investigate the impact of network traffic load on area spectral efficiency (ASE) and energy efficiency (EE) of cellular networks with cell DTX. Closedform expressions of ASE and EE as functions of traffic load for cellular networks with cell DTX are derived. It is shown that ASE increases monotonically in traffic load, while EE depends on the power consumption of base stations in sleep mode. If this power consumption is larger than a percentage of the active-mode power consumption, EE increases monotonically with traffic load and is maximized when the network is fully loaded. Otherwise, EE first increases and then decreases in traffic load. In this case, ASE and EE are maximized with different loads. The percentage threshold only depends on the path loss exponent of radio propagation environment and is calculated to be 56.2% when the path loss exponent is 4.

  • 3.
    Chang, Peiliang
    et al.
    KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS, Radio Systems Laboratory (RS Lab).
    Miao, Guowang
    KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS, Radio Systems Laboratory (RS Lab).
    Energy and Spectral Efficiency of Cellular Networks with Discontinuous Transmission2017In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 16, no 5, p. 2991-3002Article in journal (Refereed)
    Abstract [en]

    Cell discontinuous transmission (DTX) has been proposed as a solution to reduce energy consumption of cellular networks. This paper investigates the impact of network traffic load on spectral and energy efficiency of cellular networks with DTX. The SINR distribution as a function of traffic load is derived firstly. Then sufficient condition for ignoring thermal noise and simplifying the SINR distribution is investigated. Based on the simplified SINR distribution, the network spectral and energy efficiency as functions of network traffic load are derived. It is shown that the network spectral efficiency increases monotonically in traffic load, while the optimal network energy efficiency depends on the ratio of the sleep-mode power consumption to the active-mode power consumption of base stations. If the ratio is larger than a certain threshold, the network energy efficiency increases monotonically with network traffic load and is maximized when the network is fully loaded. Otherwise, the network energy efficiency firstly increases and then decreases in network traffic load. The optimal load can be identified with a binary search algorithm. The power ratio threshold depends solely on the path loss exponent α, e.g. 56% for α = 4. All these analytic results are further validated by the numerical simulations.

  • 4.
    Chang, Peiliang
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Radio Systems Laboratory (RS Lab).
    Miao, Guowang
    KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Radio Systems Laboratory (RS Lab).
    Energy-Efficient Resource Allocation in Multi-Carrier NOMA SystemsManuscript (preprint) (Other academic)
    Abstract [en]

    5G cellular networks are expected to support heterogeneous services with the same level of energy dissipation as current cellular networks. As a key enabler of 5G [1], the energy efficiency performance of non-orthogonal multiple access (NOMA) is of paramount importance. In NOMA systems, the system performance, e.g., spectral efficiency and energy efficiency are largely affected by resource allocation, i.e., sub-carrier assignment and power allocation. This paper studies the joint sub-carrier assignment and power allocation for the downlink transmission of multi-carrier NOMA systems to maximize the system energy efficiency (SEE). We first formulate an energyefficiency maximization problem while assuring the connectivity requirements of all users. The original optimization problem is a mixed integer programming problem and is NP hard. In order to develop optimal solutions with low complexity, the formulated problem is decomposed into three sub-problems: sub-carrier assignment, power allocation across sub-carriers and power allocation among users sharing the same sub-carrier. Given subcarrier assignment, we first obtain the optimal power allocation among users on one sub-carrier and then the optimal power allocation across sub-carriers. To find the optimal sub-carrier assignment, a greedy search solution based on the intrinsic structure of the transmitted power is proposed to minimize the overall required power to support the connectivity requirements of all users. Numerical simulations are implemented to validate the analytical findings. The results show that our proposed algorithms achieve better system energy efficiency and lower user blocking rate than the state-of-the-art solutions in the literature.

  • 5.
    Chang, Peiliang
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Radio Systems Laboratory (RS Lab).
    Miao, Guowang
    KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Radio Systems Laboratory (RS Lab).
    Interference-aware Distributed Control of Cell Discontinuous Transmission2018In: 2018 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), IEEE , 2018Conference paper (Refereed)
    Abstract [en]

    As a main enabler for the next generation (5G) cellular networks, network densification faces challenges in intercell interference and energy consumption. Cell discontinuous transmission (DTX) can be employed to reduce both energy consumption of base stations (BSs) and inter-cell interference. In this paper we study the control problem of cell DTX in dense small cell networks (DSCNs). We firstly formulate the network energy efficiency optimization problem. Then a centralized heuristic DTX control algorithm is presented. In order to address the issues of complexity and scalability of the centralized solution, an interference-aware distributed DTX control algorithm is proposed. Discussions on algorithm complexity and implementation are provided. The proposed algorithms are evaluated with numerical simulations. Results show that at high load region, the proposed algorithms can not only enhance network capacity by reducing inter-cell interference by up to 60% but also increase network energy efficiency by switching BSs into micro-sleep mode by 67%.

  • 6.
    Chang, Peiliang
    et al.
    KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS.
    Miao, Guowang
    KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS.
    Joint Optimization of Base Station Deep-Sleep and DTX Micro-Sleep2016In: 2016 IEEE Globecom Workshops, GC Wkshps 2016 - Proceedings, IEEE conference proceedings, 2016, article id 7848943Conference paper (Refereed)
    Abstract [en]

    When both base station (BS) deep-sleep and discontinuous transmission (DTX) are applied to improve network energy efficiency (EE), switching BS into deep-sleep mode would increase the load of remaining active BSs and thereby reduce their energy savings via DTX. This paper studies the optimal BS operation strategy when both deep-sleep and DTX are employed. Queuing theory and stochastic geometry are jointly applied to model network performance with consideration of both traffic dynamics and channel quality variations. Analytical expressions of average BS load and network EE are derived. Both analytical and simulation results show that there is a trade-off between deep-sleep energy saving and DTX energy saving when the energy saving capacity of DTX is considerable. Analytical expression of the optimal percentage of deep-sleep BSs is provided.

  • 7.
    Chang, Peiliang
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Radio Systems Laboratory (RS Lab).
    Miao, Guowang
    KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Radio Systems Laboratory (RS Lab).
    Optimal Operation of Base Stations With Deep Sleep and Discontinuous TransmissionIn: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359Article in journal (Refereed)
    Abstract [en]

    Traffic-aware base station (BS) sleeping is a promising approach to increase the energy efficiency (EE) of cellular networks. Both deep sleep and discontinuous transmission (DTX)can be applied to improve network EE. This paper studies the optimal BS operation when both deep sleep and DTX are employed. Queuing theory and stochastic geometry theory are jointly applied to model network performance considering both traffic dynamics and stochastic channel quality. We firstly propose a scaling law of transmit power that assures network coverage. Then, we characterize the resource utilization of active BSs when various percent-ages of BSs are switched into deep sleep, and analyze the overload probability of the remaining active BSs. Finally, we investigate the impact of BS deep sleep and DTX micro sleep on network EE. Both analytical and simulation results show that there is a trade-off between deep sleep and DTX micro sleep. Switching BSs into deep sleep would increase the load of the remaining active BSs and reduce their energy saving achieved with DTX. When the power consumption of BS in DTX micro-sleep mode is considerably low, switching BSs into deep sleep might increase the overall energy consumption, and it is not always the best practice to switch as many BSs into deep sleep as possible to maximize network EE.

  • 8.
    Chang, Peiliang
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Radio Systems Laboratory (RS Lab).
    Miao, Guowang
    KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Radio Systems Laboratory (RS Lab).
    Resource Provision for Energy-Efficient Mobile Edge Computing2018In: 2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings, IEEE Communications Society, 2018, article id 8648008Conference paper (Refereed)
    Abstract [en]

    Mobile Edge Computing (a.k.a Fog computing) is recently proposed to provide computing service for delay-sensitive mobile applications. Despite various benefits, deploying edge servers in cellular networks would increase their energy consumption. In this paper, we investigate the provision of resources, including both communication and computation resources, of Mobile Edge Computing (MEC) systems to improve their energy efficiency (EE). In a MEC system, both the communication subsystem, which allows mobile users to access Internet and offload their computing tasks, and the computation subsystem, which accomplishes the offloaded computing tasks, affect the service latency and consume energy. Modelling the whole system as tandem queues, we study the trade-offs between these two subsystems on energy consumption and service latency. Based on the analysis results, we propose an algorithm to determine the optimal provision of both communication and computation resources to minimize the overall energy consumption without sacrificing the performance on service latency. Numerical results are provided to validate our analytical findings.

1 - 8 of 8
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  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
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  • en-GB
  • en-US
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  • nn-NO
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