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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With the exponential increase in mobile internet traffic driven by a new generation of wireless devices, future cellular networks face a great challenge to meet this overwhelming demand of network capacity. At the same time, the demand for higher data rates and the ever-increasing number of wireless users led to rapid increases in power consumption and operating cost of cellular networks. One potential solution to address these issues is to overlay small cell networks with macrocell networks as a means to provide higher network capacity and better coverage. However, the dense and random deployment of small cells and their uncoordinated operation raise important questions about the energy efficiency implications of such multi-tier networks. Another technique to improve energy efficiency in cellular networks is to introduce active sleep (on off) modes in macrocell base stations. In this paper, we investigate the design and the associated tradeoffs of energy efficient cellular networks through the deployment of sleeping strategies and small cells. Using a stochastic geometry based model, we derive the success probability and energy efficiency in homogeneous macrocell (single-tier) and heterogeneous K-tier wireless networks under different sleeping policies. In addition, we formulate the power consumption minimization and energy efficiency maximization problems, and determine the optimal operating regimes for macrocell base stations. Numerical results confirm the effectiveness of switching off base stations in homogeneous macrocell networks. Nevertheless, the gains in terms of energy efficiency depend on the type of sleeping strategy used. In addition, the deployment of small cells generally leads to higher energy efficiency but this gain saturates as the density of small cells increases. In a nutshell, our proposed framework provides an essential understanding on the deployment of future green heterogeneous networks. The issue of energy efficiency (EE) in Orthogonal Frequency-Division Multiple Access (OFDMA) wireless networks is discussed in this paper. Our interest is focused on the promising concept of base station (BS) sleep mode, introduced recently as a key feature in order to dramatically reduce network energy consumption. The proposed technical approach fully exploits the properties of stochastic geometry, where the number of active cells is reduced in a way that the outage probability, or equivalently the signal to interference plus noise (SINR) distribution, remains the same. The optimal EE gains are then specified with the help of a simplified but yet realistic BS power consumption model. Furthermore, the authors extend their initial work by studying a non-singular path loss model in order to verify the validity of the analysis and finally, the impact on the achieved user capacity is investigated. In this context, the significant contribution of this paper is the evaluation of the theoretically optimal energy savings of sleep mode, with respect to the decisive role that the BS power profile plays. This paper addresses the problem of energy-efficient resource allocation in the downlink of a cellular orthogonal frequency division multiple access system. Three definitions of energy efficiency are considered for system design, accounting for both the radiated and the circuit power. User scheduling and power allocation are optimized across a cluster of coordinated base stations with a constraint on the maximum transmit power (either per subcarrier or per base station). The asymptotic noise-limited regime is discussed as a special case. Results show that the maximization of the energy efficiency is approximately equivalent to the maximization of the spectral efficiency for small values of the maximum transmit power, while there is a wide range of values of the maximum transmit power for which a moderate reduction of the data rate provides large savings in terms of dissipated energy. In addition, the performance gap among the considered resource allocation strategies is reduced as the out-of-cluster interference increases. In this paper, traffic-aware sleeping control (SC) and power matching (PM) of a single base station (BS) in cellular networks are studied. The objective is to find the sleeping control and power matching configurations that achieve the Pareto optimal tradeoff between total power consumption and average delay. Two types of sleeping control schemes are considered: The BS goes to sleep whenever there is no active user, and wakes up when N users are assembled or after a period of multiple or single vacation time. We first discuss when to incorporate sleeping control into power matching energy efficiently. The explicit relationship between total power consumption and average delay with varying service rate is analyzed theoretically, indicating that sacrificing delay cannot always be traded for energy saving, and we also provide conditions under which the energy-optimal rate exists. Moreover, the optimal pair of sleeping parameter and service rate to achieve the optimal energy-delay tradeoff, and the energy consumption lower bound are also derived. Both the analytical and simulation results show that tolerable sacrifice of delay performance can be traded for substantial amount of energy saving given that careful designs were made according to our analysis.