This paper studies the problem of self-organizing heterogeneous LTE systems. We propose a model that jointly considers several important characteristics of heterogeneous LTE system, including the usage of orthogonal frequency division multiple access (OFDMA), the frequency-selective fading for each link, the interference among different links, and the different transmission capabilities of different types of base stations. We also consider the cost of energy by taking into account the power consumption, including that for wireless transmission and that for operation, of base stations and the price of energy. Based on this model, we aim to propose a distributed protocol that improves the spectrum efficiency of the system, which is measured in terms of the weighted proportional fairness among the throughputs of clients, and reduces the cost of energy. We identify that there are several important components involved in this problem. We propose distributed strategies for each of these components. Each of the proposed strategies requires small computational and communicational overheads. Moreover, the interactions between components are also considered in the proposed strategies. Hence, these strategies result in a solution that jointly considers all factors of heterogeneous LTE systems. Simulation results also show that our proposed strategies achieve much better performance than existing ones.
On the other hand, techniques for improving cellular radio energy efficiency have recently attracted much attention. @cite_10 has investigated the amount of power consumptions for various types of base stations. @cite_0 has discussed various techniques for improving energy efficiency. @cite_20 has proposed to turn base stations to sleep mode when the network traffic is small to save energy. @cite_19 , @cite_22 , and Gong, Zhou, and Niu @cite_18 have proposed various policies of allocating clients so that clients are mostly allocated to a few base stations. As a result, many base stations that do not have any clients can be turned to sleep mode to save energy. However, these studies require the knowledge of traffic of each client, and cannot be applied to scenarios where clients' traffic is elastic. @cite_21 has studied the trade-off between spectrum efficiency and energy efficiency. @cite_13 and @cite_3 have provided extensive surveys on energy-efficient wireless communications. However, they do not consider the interference and interactions between base stations, and are hence not applicable to self-organizing networks.
@cite_13 @cite_18 @cite_22 @cite_21 @cite_3 @cite_0 @cite_19 @cite_10 @cite_20
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Since battery technology has not progressed as rapidly as semiconductor technology, power efficiency has become increasingly important in wireless networking, in addition to the traditional quality and performance measures, such as bandwidth, throughput, and fairness. Energy-efficient design requires a cross layer approach as power consumption is affected by all aspects of system design, ranging from silicon to applications. This article presents a comprehensive overview of recent advances in cross-layer design for energy-efficient wireless communications. We particularly focus on a system-based approaches toward energy optimal transmission and resource management across time, frequency, and spatial domains. Details related to energy-efficient hardware implementations are also covered. Copyright © 2008 John Wiley & Sons, Ltd. The energy consumption of the information and communication technology (ICT) industry, which has become a serious problem, is mostly due to the network infrastructure rather than the mobile terminals. In this paper, we focus on reducing the energy consumption of base stations (BSs) by adjusting their working modes (active or sleep). Specifically, the objective is to minimize the energy consumption while satisfying quality of service (QoS, e.g., blocking probability) requirement and, at the same time, avoiding frequent mode switching to reduce signaling and delay overhead. The problem is modeled as a dynamic programming (DP) problem, which is NP-hard in general. Based on cooperation among neighboring BSs, a low-complexity algorithm is proposed to reduce the size of state space as well as that of action space. Simulations demonstrate that, with the proposed algorithm, the active BS pattern well meets the time variation and the non-uniform spatial distribution of system traffic. Moreover, the tradeoff between the energy saving from BS sleeping and the cost of switching is well balanced by the proposed scheme. The explosive development of ICT (information and communication technology) industry has emerged as one of the major sources of world energy consumption. Therefore, this paper concerns about the BS (base station) energy saving issue, for most energy consumption of the communication network comes from the BSs and the core network. Particularly, we consider dynamically turning off certain BSs when the network traffic is low. Centralized and decentralized implementations are investigated. Simulations demonstrate the energy efficiency of the proposed algorithms and the tradeoff between energy saving and coverage guarantee. Traditional mobile wireless network mainly design focuses on ubiquitous access and large capacity. However, as energy saving and environmental protection become global demands and inevitable trends, wireless researchers and engineers need to shift their focus to energy-efficiency-oriented design, that is, green radio. In this article, we propose a framework for green radio research and integrate the fundamental issues that are currently scattered. The skeleton of the framework consists of four fundamental tradeoffs: deployment efficiency-energy efficiency, spectrum efficiency-energy efficiency, bandwidth-power, and delay-power. With the help of the four fundamental trade-offs, we demonstrate that key network performance cost indicators are all strung together. With explosive growth of high-data-rate applications, more and more energy is consumed in wireless networks to guarantee quality of service. Therefore, energy-efficient communications have been paid increasing attention under the background of limited energy resource and environmental- friendly transmission behaviors. In this article, basic concepts of energy-efficient communications are first introduced and then existing fundamental works and advanced techniques for energy efficiency are summarized, including information-theoretic analysis, OFDMA networks, MIMO techniques, relay transmission, and resource allocation for signaling. Some valuable topics in energy-efficient design are also identified for future research. The last ten years have witnessed explosive growth in the number of subscribers for mobile telephony. The technology has evolved from early voice only services to today's mobile wireless broadband (Internet) data delivery. The increasing use of wireless connectivity via smartphones and laptops has led to an exponential surge in network traffic. Meeting traffic demands will cause a significant increase in operator energy cost as an enlarged network of radio base stations will be needed to support mobile broadband effectively and maintain operational competitiveness. This article explores approaches that will assist in delivering significant energy efficiency gains in future wireless networks, easing the burden on network operators. It investigates three approaches to saving energy in future wireless networks. These include sleep mode techniques to switch off radio transmissions whenever possible; femtocell and relay deployments; and multiple antenna wireless systems. The impact of these approaches on achieving energy-efficient wireless communication systems is discussed. Energy-efficiency, one of the major design goals in wireless cellular networks, has received much attention lately, due to increased awareness of environmental and economic issues for network operators. In this paper, we develop a theoretical framework for BS energy saving that encompasses dynamic BS operation and the related problem of user association together. Specifically, we formulate a total cost minimization that allows for a flexible tradeoff between flow-level performance and energy consumption. For the user association problem, we propose an optimal energy-efficient user association policy and further present a distributed implementation with provable convergence. For the BS operation problem (i.e., BS switching on off), which is a challenging combinatorial problem, we propose simple greedy-on and greedy-off algorithms that are inspired by the mathematical background of submodularity maximization problem. Moreover, we propose other heuristic algorithms based on the distances between BSs or the utilizations of BSs that do not impose any additional signaling overhead and thus are easy to implement in practice. Extensive simulations under various practical configurations demonstrate that the proposed user association and BS operation algorithms can significantly reduce energy consumption. In order to quantify the energy efficiency of a wireless network, the power consumption of the entire system needs to be captured. In this article, the necessary extensions with respect to existing performance evaluation frameworks are discussed. The most important addenda of the proposed energy efficiency evaluation framework (E3F) are a sophisticated power model for various base station types, as well as large-scale long-term traffic models. The BS power model maps the RF output power radiated at the antenna elements to the total supply power of a BS site. The proposed traffic model emulates the spatial distribution of the traffic demands over large geographical regions, including urban and rural areas, as well as temporal variations between peak and off-peak hours. Finally, the E3F is applied to quantify the energy efficiency of the downlink of a 3GPP LTE radio access network. In this article, we consider the adoption of sleep modes for the base stations of a cellular access network, focusing on the design of base station sleep and wake-up transients.. We discuss the main issues arising with this approach, and we focus on the design of base station sleep and wake-up transients, also known as cell wilting and blossoming. The performance of the proposed procedures is evaluated in a realistic test scenario, and the results show that sleep and wake-up transients are short, lasting at most 30 seconds.