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Miao, Guowang, Associate professor
Publications (10 of 12) Show all publications
Wang, Y., Liu, J. & Miao, G. (2018). Decentralized Cross-Layer Optimization for Energy-Efficient Resource Allocation in HetNets. In: 2018 INTERNATIONAL CONFERENCE ON CYBER-ENABLED DISTRIBUTED COMPUTING AND KNOWLEDGE DISCOVERY (CYBERC 2018): . Paper presented at 10th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), OCT 18-20, 2018, Zhengzhou Univ, Zhengzhou, PEOPLES R CHINA (pp. 470-474). IEEE
Open this publication in new window or tab >>Decentralized Cross-Layer Optimization for Energy-Efficient Resource Allocation in HetNets
2018 (English)In: 2018 INTERNATIONAL CONFERENCE ON CYBER-ENABLED DISTRIBUTED COMPUTING AND KNOWLEDGE DISCOVERY (CYBERC 2018), IEEE , 2018, p. 470-474Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we develop a joint physical and medium access control (MAC) layer optimization (JPMO) scheme based on game theory for energy-efficient resource allocation and interference management in heterogeneous networks (HetNets). In HetNets, cross-tier interference and co-tier interference significantly limit the network performance. Moreover, when each user only has its own channel state information and chooses its transmission policy independently without any coordination mechanism, it will result in the network collapse or waste of channel resources. To maximize the network efficiency, we develop the JPMO scheme through pricing mechanism from the perspective of game theory. Then we transform this scheme into a two-stage Stackelberg game, in which macrocell determines the transmission policy in MAC layer first, and then SCs perform EE power allocation in physical layer. Simulation results validate the effectiveness of the proposed scheme.

Place, publisher, year, edition, pages
IEEE, 2018
Series
International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, ISSN 2475-7020
Keywords
Cross-layer design, HetNets, Energy-efficient, Resource allocation
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:kth:diva-249831 (URN)10.1109/CyberC.2018.00091 (DOI)000462960100079 ()2-s2.0-85063163803 (Scopus ID)978-1-7281-0974-9 (ISBN)
Conference
10th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), OCT 18-20, 2018, Zhengzhou Univ, Zhengzhou, PEOPLES R CHINA
Note

QC 20190423

Available from: 2019-04-23 Created: 2019-04-23 Last updated: 2019-04-23Bibliographically approved
Kwon, Y., Park, H., Oh, J., Miao, G. & Hwang, T. (2018). Energy-Efficient Routing and Link Adaptation for 2D Wireless Relay Networks in the Wideband Regime. IEEE Transactions on Wireless Communications, 17(11), 7325-7339
Open this publication in new window or tab >>Energy-Efficient Routing and Link Adaptation for 2D Wireless Relay Networks in the Wideband Regime
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2018 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 17, no 11, p. 7325-7339Article in journal (Refereed) Published
Abstract [en]

We discuss the globally optimal energy-efficient design of a 2D relay network. Different from the existing routing protocols on energy saving, which finds the minimal energy route for a given data rate, the proposed algorithm jointly optimizes routing and data rate to maximize energy efficiency (EE) defined as the achievable data rate per power consumption. We propose a low-complexity algorithm to circumvent the huge complexity of the exhaustive search for the network EE maximization and prove its global optimality. Moreover, the proposed algorithm is implemented in a distributed fashion because each relay needs to send its routing information only to the relays in its adjacent tiers, which significantly reduces the signaling overhead of the centralized implementation. Our analysis on the worst-case complexity in a fading channel shows that the complexity of the proposed algorithm increases linearly while that of the exhaustive search increases exponentially as the tier index increases. Simulation results confirm that the proposed algorithm outperforms the existing routing protocols on energy saving and achieves the globally optimal network EE at a significantly lower complexity than the exhaustive search.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2018
Keywords
Energy efficiency, routing, link adaptation, widehand
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-239805 (URN)10.1109/TWC.2018.2866422 (DOI)000449978700016 ()2-s2.0-85052649060 (Scopus ID)
Note

QC 20190107

Available from: 2019-01-07 Created: 2019-01-07 Last updated: 2019-01-07Bibliographically approved
Chang, P. & Miao, G. (2018). Interference-aware Distributed Control of Cell Discontinuous Transmission. In: 2018 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC): . Paper presented at IEEE Wireless Communications and Networking Conference (WCNC), APR 15-18, 2018, Barcelona, SPAIN. IEEE
Open this publication in new window or tab >>Interference-aware Distributed Control of Cell Discontinuous Transmission
2018 (English)In: 2018 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), IEEE , 2018Conference paper, Published 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%.

Place, publisher, year, edition, pages
IEEE, 2018
Series
IEEE Wireless Communications and Networking Conference, ISSN 1525-3511
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-232290 (URN)000435542401052 ()2-s2.0-85049198826 (Scopus ID)978-1-5386-1734-2 (ISBN)
Conference
IEEE Wireless Communications and Networking Conference (WCNC), APR 15-18, 2018, Barcelona, SPAIN
Note

QC 20180718

Available from: 2018-07-18 Created: 2018-07-18 Last updated: 2019-04-04Bibliographically approved
Azari, A., Miao, G., Stefanovic, C. & Popovski, P. (2018). Latency-Energy Tradeoff based on Channel Scheduling and Repetitions in NB-IoT Systems. In: 2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings: . Paper presented at 2018 IEEE Global Communications Conference, GLOBECOM 2018; Abu Dhabi National Exhibition Centre (ADNEC)Abu Dhabi; United Arab Emirates; 9 December 2018 through 13 December 2018. Institute of Electrical and Electronics Engineers (IEEE), Article ID 8648024.
Open this publication in new window or tab >>Latency-Energy Tradeoff based on Channel Scheduling and Repetitions in NB-IoT Systems
2018 (English)In: 2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings, Institute of Electrical and Electronics Engineers (IEEE), 2018, article id 8648024Conference paper, Published paper (Refereed)
Abstract [en]

Narrowband Internet of Things (NB-IoT) is the latest IoT connectivity solution presented by the 3rd generation partnership project (3GPP). NB-IoT introduces coverage classes and offers a significant link budget improvement by allowing repeated transmissions by nodes that experience high path loss. However, those repetitions necessarily increase the energy consumption and the latency in the whole NB-IoT system. The extent to which the whole system is affected depends on the scheduling of the uplink and downlink channels. We address this question, not treated previously, by developing a tractable model of NB-IoT access protocol operation, comprising message exchanges in random-access, control, and data channels, both in the uplink and downlink The model is then used to analyze the impact of channel scheduling as well as the interaction of coexisting coverage classes, through derivation of the expected latency and battery lifetime for each coverage class. These results are subsequently employed in investigation of latency-energy tradeoff in NB-IoT channel scheduling as well as determining the optimized operation points. Simulations results show validity of the analysis and confirm that channel scheduling and coexistence of coverage classes significantly affect latency and battery lifetime performance of NB-IoT devices.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Series
IEEE Global Communications Conference, ISSN 2334-0983
Keywords
NB-IoT, Latency energy tradeoff, repetition, multiplexing, انرژی تاخیر، اینترنت اشیاء باند باریک، تکرار سیگنال
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-232211 (URN)10.1109/GLOCOM.2018.8648024 (DOI)000465774305078 ()2-s2.0-85063419292 (Scopus ID)9781538647271 (ISBN)
Conference
2018 IEEE Global Communications Conference, GLOBECOM 2018; Abu Dhabi National Exhibition Centre (ADNEC)Abu Dhabi; United Arab Emirates; 9 December 2018 through 13 December 2018
Note

QC 20180716

Available from: 2018-07-15 Created: 2018-07-15 Last updated: 2019-06-12Bibliographically approved
Chang, P. & Miao, G. (2018). Resource Provision for Energy-Efficient Mobile Edge Computing. In: 2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings: . Paper presented at 2018 IEEE Global Communications Conference, GLOBECOM 2018; Abu Dhabi National Exhibition Centre (ADNEC)Abu Dhabi; United Arab Emirates; 9 December 2018 through 13 December 2018. IEEE Communications Society, Article ID 8648008.
Open this publication in new window or tab >>Resource Provision for Energy-Efficient Mobile Edge Computing
2018 (English)In: 2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings, IEEE Communications Society, 2018, article id 8648008Conference paper, Published 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.

Place, publisher, year, edition, pages
IEEE Communications Society, 2018
Series
IEEE Global Communications Conference, ISSN 2334-0983
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-238789 (URN)10.1109/GLOCOM.2018.8648008 (DOI)000465774305062 ()2-s2.0-85063502785 (Scopus ID)9781538647271 (ISBN)
Conference
2018 IEEE Global Communications Conference, GLOBECOM 2018; Abu Dhabi National Exhibition Centre (ADNEC)Abu Dhabi; United Arab Emirates; 9 December 2018 through 13 December 2018
Note

QC 20181112

Available from: 2018-11-11 Created: 2018-11-11 Last updated: 2019-06-12Bibliographically approved
Azari, A. & Miao, G. (2017). Fundamental Tradeoffs in Resource Provisioning forIoT Services over Cellular Networks. In: Proceedings of the 2017 IEEE International Conference on Communications: . Paper presented at 2017 IEEE International Conference on Communications, ICC 2017, Paris, France, 21 May 2017 through 25 May 2017. Institute of Electrical and Electronics Engineers (IEEE), Article ID 7996885.
Open this publication in new window or tab >>Fundamental Tradeoffs in Resource Provisioning forIoT Services over Cellular Networks
2017 (English)In: Proceedings of the 2017 IEEE International Conference on Communications, Institute of Electrical and Electronics Engineers (IEEE), 2017, article id 7996885Conference paper, Published paper (Refereed)
Abstract [en]

Performance tradeoffs in resource provisioningfor mixed internet-of-things (IoT) and human-orientedcommunications(HoC) services over cellular networks are investigated.First, we present a low-complexity model of cellularconnectivity in the uplink direction in which both accessreservation and scheduled data transmission procedures areincluded. This model is employed subsequently in derivinganalytical expressions for energy efficiency, spectral efficiency,and experienced delay in data transmission of connected devicesas well as energy consumption of base stations. The derivedexpressions indicate that the choice of uplink resource provisioningstrategy introduces tradeoffs between battery lifetime forIoT communications, quality of service (QoS) for HoC, spectralefficiency and energy consumption for the access network. Then,the impacts of system and traffic parameters on the introducedtradeoffs are investigated. Performance analysis illustrates thatimproper resource provisioning for IoT traffic not only degradesQoS of high-priority services and decreases battery lifetime ofIoT devices, but also increases energy consumption of the accessnetwork. The presented analytical and simulations results figureout the ways in which spectral/energy efficiency for the accessnetwork and QoS for high-priority services could be traded toprolong battery lifetimes of connected devices by compromisingon the level of provisioned radio resources.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017
Series
IEEE International Conference on Communications, ISSN 1550-3607
Keywords
Internet of things, Machine-type communications, Resource provisioning, Energy efficiency, Green cellular network., اینترنت اشیا، چیزنت، بهینگی انرژی، طول عمر باتری، مخام، مخابرات ماشین به ماشین، نسل پنجم، مصالحه انرژِ تاخیر
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-194414 (URN)10.1109/ICC.2017.7996885 (DOI)000424872103084 ()2-s2.0-85028314875 (Scopus ID)9781467389990 (ISBN)
Conference
2017 IEEE International Conference on Communications, ICC 2017, Paris, France, 21 May 2017 through 25 May 2017
Note

QC 20161103

Available from: 2016-10-27 Created: 2016-10-27 Last updated: 2018-03-14Bibliographically approved
Azari, A. & Miao, G. (2017). Network Life time Maximization for Cellular-Based M2M Networks. IEEE Access, 5, 18927-18940, Article ID 8045999.
Open this publication in new window or tab >>Network Life time Maximization for Cellular-Based M2M Networks
2017 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 5, p. 18927-18940, article id 8045999Article in journal (Refereed) Published
Abstract [en]

High energy efficiency is critical for enabling massive machine-type communications (MTC) over cellular networks. This paper is devoted to energy consumption modeling, battery lifetime analysis, lifetime-aware scheduling, and transmit power control for massive MTC over cellular networks. We consider a realistic energy consumption model for MTC and model network battery-lifetime. Analytic expressions are derived to demonstrate the impact of scheduling on both the individual and network battery lifetimes. The derived expressions are subsequently employed in the uplink scheduling and transmit power control for mixed-priority MTC traffic in order to maximize the network lifetime. Besides the main solutions, low complexity solutions with limited feedback requirement are investigated, and the results are extended to existing LIE networks. In addition, the energy efficiency, spectral efficiency, and network lifetime tradeoffs in resource provisioning and scheduling for MTC over cellular networks are investigated. The simulation results show that the proposed solutions can provide substantial network lifetime improvement and network maintenance cost reduction in comparison with the existing scheduling schemes.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017
Keywords
Internet of things, machine to machine communications, scheduling, energy efficiency, resource allocation
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-217081 (URN)10.1109/ACCESS.2017.2753283 (DOI)000412767700013 ()2-s2.0-85030651564 (Scopus ID)
Note

QC 20171121

Available from: 2017-11-21 Created: 2017-11-21 Last updated: 2018-11-07Bibliographically approved
Azari, A. & Miao, G. (2017). Network Lifetime Maximization for Cellular-Based M2M Networks. IEEE Access
Open this publication in new window or tab >>Network Lifetime Maximization for Cellular-Based M2M Networks
2017 (English)In: IEEE Access, E-ISSN 2169-3536Article in journal (Refereed) Accepted
Abstract [en]

High energy efficiency is critical for enabling massivemachine-type communications (MTC) over cellular networks.This work is devoted to energy consumption modeling,battery lifetime analysis, lifetime-aware scheduling and transmitpower control for massive MTC over cellular networks. Weconsider a realistic energy consumption model for MTC andmodel network battery-lifetime. Analytic expressions are derivedto demonstrate the impact of scheduling on both the individualand network battery lifetimes. The derived expressions aresubsequently employed in uplink scheduling and transmit powercontrol for mixed-priority MTC traffic in order to maximizethe network lifetime. Besides the main solutions, low-complexitysolutions with limited feedback requirement are investigated,and the results are extended to existing LTE networks. Also,the energy efficiency, spectral efficiency, and network lifetimetradeoffs in resource provisioning and scheduling for MTC overcellular networks are investigated. The simulation results showthat the proposed solutions can provide substantial networklifetime improvement and network maintenance cost reductionin comparison with the existing scheduling schemes.

Place, publisher, year, edition, pages
IEEE Press, 2017
Keywords
Internet of Things, Machine to Machine Communications, Cellular Networks, Scheduling, Energy Efficiency, Resource Allocation., زمانبندی، مخام، اینترنت اشیا، مخابرات گوشی به گوشی، طول عمر باتری، بهینگی انرژی
National Category
Engineering and Technology Communication Systems
Identifiers
urn:nbn:se:kth:diva-194413 (URN)
Note

QC 20161103

Available from: 2016-10-27 Created: 2016-10-27 Last updated: 2017-11-29Bibliographically approved
Wu, J., Bao, Y., Miao, G., Zhou, S. & Niu, Z. (2016). Base-Station Sleeping Control and Power Matching for Energy–Delay Tradeoffs With Bursty Traffic. IEEE Transactions on Vehicular Technology
Open this publication in new window or tab >>Base-Station Sleeping Control and Power Matching for Energy–Delay Tradeoffs With Bursty Traffic
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2016 (English)In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359Article in journal (Refereed) Published
Abstract [en]

In this paper, we study sleeping control (SC) and power matching (PM) for a single cell in cellular networks with bursty traffic. The base station (BS) sleeps whenever the system is empty and wakes up when N users are assembled during the sleep period. The service capacity of the BS in the active mode is controlled by adjusting its transmit power. The total power consumption and average delay are analyzed, and based on this, the impact of parameter N and transmit power on the energy-delay tradeoff is studied. It is shown that, given the average traffic load, the more bursty the traffic is, the less total power consumed, although the delay performance of more bursty traffic is better only under certain circumstances. The optimal energy-delay tradeoff is then obtained through joint SC and PM optimization. The relationship between the optimal control parameters and the asymptotic performance are also provided. Moreover, the influence of the traffic autocorrelation is explored, which shows less impact on the system performance compared with that of the burstiness. Numerical results show the energy saving gain of the joint SC and PM scheme, as well as the impact of burstiness on the optimal energy-delay tradeoff.

Place, publisher, year, edition, pages
IEEE Press, 2016
Keywords
base station, energy efficient, sleeping, delay
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
SRA - ICT
Identifiers
urn:nbn:se:kth:diva-198279 (URN)10.1109/TVT.2015.2434381 (DOI)000376094500061 ()2-s2.0-84970006311 (Scopus ID)
Funder
VINNOVA, 60056
Note

QC 20170112

Available from: 2016-12-13 Created: 2016-12-13 Last updated: 2017-11-29Bibliographically approved
Chang, P. & Miao, G. (2016). Joint Optimization of Base Station Deep-Sleep and DTX Micro-Sleep. In: 2016 IEEE Globecom Workshops, GC Wkshps 2016 - Proceedings: . Paper presented at 2016 IEEE Globecom Workshops, GC Wkshps 2016, Washington, United States, 4 December 2016 through 8 December 2016. IEEE conference proceedings, Article ID 7848943.
Open this publication in new window or tab >>Joint Optimization of Base Station Deep-Sleep and DTX Micro-Sleep
2016 (English)In: 2016 IEEE Globecom Workshops, GC Wkshps 2016 - Proceedings, IEEE conference proceedings, 2016, article id 7848943Conference paper, Published 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.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2016
Keywords
Green communication, cell discontinuous transmission, BS deep-sleep, network load, energy efficiency
National Category
Engineering and Technology
Research subject
Telecommunication; Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-201696 (URN)10.1109/GLOCOMW.2016.7848943 (DOI)000401921400145 ()2-s2.0-85015968040 (Scopus ID)9781509024827 (ISBN)
Conference
2016 IEEE Globecom Workshops, GC Wkshps 2016, Washington, United States, 4 December 2016 through 8 December 2016
Note

QC 20170308

Available from: 2017-02-14 Created: 2017-02-14 Last updated: 2018-11-11Bibliographically approved
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