Relax, but Do Not Sleep: A new perspective on Green Wireless Networking

Gao, Chenfei; Zhang, Weiyi; Tang, Jian; Wang, Chonggang; Zou, Shihong; Sen, Sandip

doi:10.1109/infocom.2014.6848019

Cited by 9 publications

(10 citation statements)

References 22 publications

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“…Thus the power consumption of the BS and relay i can be expressed as P B = p B +∆p B and P i = p i +∆p i , respectively. Since the BS dominates the energy consumption in cellular networks [36], its required energy can be taken not only from the renewable energy generator but also from the power grid. Due to the investment cost each RS is only powered by grid.…”

Section: Energy Management Modelmentioning

confidence: 99%

Energy-Efficient Resource Allocation for Time-Varying OFDMA Relay Systems With Hybrid Energy Supplies

Yang

Shen

Han

et al. 2018

IEEE Systems Journal

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Abstract-This paper investigates the energy efficient resource allocation for orthogonal frequency division multiple access (OFDMA) relay systems, where the system is supplied by the conventional utility grid and a renewable energy generator equipped with a storage device. The optimal usage of radio resource depends on the characteristics of the renewable energy generation and the mobile traffic, which exhibit both temporal and spatial diversities. Lyapunov optimization method is used to decompose the problem into the joint flow control, radio resource allocation and energy management without knowing a priori knowledge of system statistics. It is proven that the proposed algorithm can result in close-to-optimal performance with capacity limited data buffer and storage device. Simulation results show that the flexible tradeoff between the system utility and the conventional energy consumption can be achieved. Compared with other schemes, the proposed algorithm demonstrates better performance.

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Section: Energy Management Modelmentioning

confidence: 99%

Energy-Efficient Resource Allocation for Time-Varying OFDMA Relay Systems With Hybrid Energy Supplies

Yang

Shen

Han

et al. 2018

IEEE Systems Journal

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“…Year CSO type / architecture Realistic Coverage aspects Complexity and ICI model feasibility analysis [9] 2016 Snapshot / Semi-distributed Full-load Downlink [10] 2016 Traffic profiling / Centralized Full-load Downlink Partially [11] 2016 Traffic profiling / Semi-distributed Load-coupling Downlink Partially [12] 2015 Snapshot / Centralized Full-load Downlink Partially [13] 2015 Snapshot / Centralized Full-load Downlink Partially [14] 2014 Snapshot / Centralized Constant Downlink × [15] 2014 Traffic profiling / Semi-distributed Full-load Downlink [16] 2014 Snapshot / Centralized Constant Downlink × [17] 2013 Snapshot / Centralized Full-load Downlink × [18] 2013 Traffic profiling / Centralized Load-coupling Downlink × [19] 2013 Snapshot / Centralized Constant × Partially [20] 2013 Snapshot / Centralized Full-load Downlink Partially [21] 2013 Snapshot / Centralized Full-load Downlink × [22] 2012 Snapshot / Centralized Constant × × [23] 2012 Snapshot / Centralized Full-load Downlink × [24] 2011 Traffic profiling / Semi-distributed Full-load Downlink Partially [25] 2010 Snapshot / Centralized Full-load Downlink × [26] 2010 Snapshot / Centralized Constant Downlink × [27] 2010 Traffic profiling / Semi-distributed Full-load × × [28] 2009 Snapshot / Both Full-load × × type of solution provides the ultimate performance in terms of energy savings. However, feasibility becomes a serious issue as it will be shown later on.…”

Section: Refmentioning

confidence: 99%

“…Thus, in the comparative perspective shown in Table I, the following criteria have been considered: • CSO type / architecture: CSO solutions can be classified as 'snapshot' or 'traffic profiling' CSO depending on the approach followed to take the on/off decisions. In snapshot CSO (e.g., [14,16,17,19]), decisions involve the analysis of discrete realizations of users, i.e., whenever a CSO decision is required, information of every single user in the network needs to be available at a central unit where an heuristic or optimization procedure is performed. Given its nature, this…”

mentioning

confidence: 99%

A Novel Multiobjective Cell Switch-Off Framework for Cellular Networks

et al. 2016

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Cell Switch-Off (CSO) is recognized as a promising approach to reduce the energy consumption in next-generation cellular networks. However, CSO poses serious challenges not only from the resource allocation perspective but also from the implementation point of view. Indeed, CSO represents a difficult optimization problem due to its NP-complete nature. Moreover, there are a number of important practical limitations in the implementation of CSO schemes, such as the need for minimizing the real-time complexity and the number of on-off/off-on transitions and CSO-induced handovers. This article introduces a novel approach to CSO based on multiobjective optimization that makes use of the statistical description of the service demand (known by operators). In addition, downlink and uplink coverage criteria are included and a comparative analysis between different models to characterize intercell interference is also presented to shed light on their impact on CSO. The framework distinguishes itself from other proposals in two ways: 1) The number of on-off/off-on transitions as well as handovers are minimized, and 2) the computationally-heavy part of the algorithm is executed offline, which makes its implementation feasible. The results show that the proposed scheme achieves substantial energy savings in small cell deployments where service demand is not uniformly distributed, without compromising the Quality-of-Service (QoS) or requiring heavy real-time processing.

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“…Despite the support of the server, the eNodeB needs to exchange the control message with neighbors since RRC management remains in each eNodeB. Another method in Figure 3(c) that uses relay stations and reduces the power instead of putting the eNodeB in sleep mode, named Relax is presented in [18]. In this method, they use the information of each user such as the distance from a certain eNodeB to the users and energy consumption between a certain eNodeB and users.…”

Section: Description Of Previous Studies: a Distributed Algorithmmentioning

confidence: 99%

“…Relax shows the most rapid increase because the number of users is considered in order to optimize the placement of the relay station. Here, relay stations are considered as eNodeBs, and the total number of users followed the example in [18] since we do not consider the number of users in analysis. Siesta shows the lowest number of message exchanges since the control messages are not exchanged between eNodeBs as described in Figure 4(a).…”

Section: Description Of Previous Studies: a Distributed Algorithmmentioning

confidence: 99%

Siesta: Software-Defined Energy Efficient Base Station Control for Green Cellular Networks

Shin

Choi

Song

2015

2015 24th International Conference on Computer Communication and Networks (ICCCN)

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In order to tackle the issues of mounting deployments and large energy consumption of base stations, it is integral to devise schemes to improve energy efficiency in cellular networks. We propose a virtualized network function of cell management on an SDN architecture. We develop a cell management algorithm on the architecture that can effectively control the sleep and awake modes of base stations and perform handover operations in a cellular network. It provides significant benefits over current cellular networks that suffer from inflexible management and complex control. Our extensive trace-driven evaluation results show that the proposed control architecture and the cell management algorithm achieve significant energy savings, and incur less control message exchanges, more cells in a sleep mode for longer durations, and less cell status changes than existing energy saving approaches for cellular networks.

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Relax, but Do Not Sleep: A new perspective on Green Wireless Networking

Cited by 9 publications

References 22 publications

Energy-Efficient Resource Allocation for Time-Varying OFDMA Relay Systems With Hybrid Energy Supplies

Energy-Efficient Resource Allocation for Time-Varying OFDMA Relay Systems With Hybrid Energy Supplies

A Novel Multiobjective Cell Switch-Off Framework for Cellular Networks

Siesta: Software-Defined Energy Efficient Base Station Control for Green Cellular Networks

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