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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 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%.

  • 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).
    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.

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