Evaluation of Energy-Efficiency Problem in Orthogonal Frequency Division Multiple Access Cellular Networks

Celal Bayar University Journal of Science Volume 15, Issue 1, 2019, p 9-15 Doi: 10.18466/cbayarfbe.416583 İ. Baştürk Evaluation of Energy-Efficiency Problem in Orthogonal Frequency Division Multiple Access Cellular Networks İlhan Baştürk* Department of Electrical-Electronics Engineering, Aydın Adnan Menderes University, Aydın, Turkey * Received: 18 April 2018 Accepted: 29 January 2019 DOI: 10.18466/cbayarfbe.416583 Abstract In this study, the energy-efficiency (EE) problem is investigated for downlink Orthogonal Frequency Division Multiple Access (OFDMA) cellular networks. The EE maximization problem is defined under certain prescribed per-user quality-of-service (QoS) demands and maximum system power limit. EE metric that aims to maximize the system data rate and minimize the total power consumption at the same time is used as the objective function of the defined problem. In this form the optimization problem belongs to a broad class of problems called mixed-integer non-linear programming problem (MINLP), that is difficult to solve in its original form in such a multi-carrier, multi-user networks. Hence, we have decomposed the original problem into two parts and presented a solution that performs subchannel allocation and power allocation parts separately. Simulation results are obtained to confirm the performance of the presented scheme in terms of energy-efficiency and total data rate. Keywords: Energy-Efficiency, OFDMA, Cellular Networks. one of the new obligatory evaluation metrics in 5th generation (5G) systems [6]. 1. Introduction The number of mobile users and mobile devices are increasing enormously and according to some researches, by the last quarter of 2017, total mobile subscriptions reached to 7.8 billion and they are growing around 4 percent year-on-year [1]. Not only the number of mobile broadband subscriptions is increasing but also the expectation of these users about ubiquitous access to the high-data rate wireless services such as video streaming, online gaming etc. is increasing. This case causes rapidly booming energy consumption which is a big problem for the next generation wireless networks. It is also reported that mobile operators are already among the top energy consumers that is about 3% of the worldwide energy consumption and contributed to about 2% of the global carbon dioxide emissions [2]. Thus, energy-efficient communication, also well-known as Green Communication has thereby been proposed as an effective solution and is becoming the mainstream for future wireless network design. To reach the targets of the Green Communication, two different and effective ways are used in the literature. The first way is harvesting energy from the surrounding environment including solar, wind and radio frequency (RF) signals [3,4]. The second way is designing energyefficient communication systems to maximize the number of transmitted information bits per unit of energy [5]. The second way, in which system capacity should be enlarged and system energy consumption should be reduced at the same time has been adopted as OFDMA is one of the key technologies used to meet the mobile users’ increasing expectations for ubiquitous access to the high-data rate wireless services. The main advantages of the OFDMA can be listed as robustness against frequency-selective fading, high spectral efficiency and flexible resource allocation. In OFDMA, the frequency spectrum is divided into a number of subcarriers and then subsets of these subcarriers also called subchannels are allocated to different users by exploiting multiuser diversity. It is popularly used in 4th generation (4G) wireless systems of broadband communications such as 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE), LTE Advanced, Worldwide Interoperability for Microwave Access (WiMAX). Radio resource management (RRM) schemes such as subchannel allocation and power allocation can be used to meet the certain demands of the users and service providers. Once the optimization problem has been established according to the different objective functions (rate maximization, power minimization, energy-efficiency maximization) and different optimization constraints, the problem can be solved optimally or in a heuristic manner. The RRM problem who aims rate maximization and power minimization in OFDMA based cellular networks is studied in many works [7-12]. However, these works disregarded the energy consumption of the system which is being a huge problem for the information and communication 9 Celal Bayar University Journal of Science Volume 15, Issue 1, 2019, p 9-15 Doi: 10.18466/cbayarfbe.416583 İ. Baştürk since it is known that the BSs are placed to the regions where more users are. The BS communicates with the mobile devices through a direct link by using the allocated subchannels which composed of a set of adjacent Orthogonal Frequency Division Multiplexing (OFDM) subcarriers. There are 𝑁 subchannels to be allocated in the BS as illustrated in Figure 1. It is assumed that one subchannel is exclusively allocated to maximum one user in order to avoid intra-cell interference. Each subchannel has a bandwidth 𝛶 and total system bandwidth is 𝐵 = 𝑁 × 𝛶. The resource allocation such as subchannel allocation and power allocation is performed at the BS so all channel state information (CSI) between the BS and each mobile device is perfectly known at the BS. technology industries. Thus, recently, more attention has been paid to RRM problems whose target is maximizing the EE in OFDMA cellular networks [1318]. Contrary to rate maximization and power minimization problems, EE maximization problems belong to a class of optimization problems called fractional programs which make them difficult to solve. In [13], energy-efficiency and spectral-efficiency tradeoff is discussed for the downlink OFDMA networks. In [14], while the weighted EE maximization problem is explored for the downlink transmission, the minimum individual EE maximization problem is studied for the uplink transmission. In [15], the authors focused on system fairness issue in energy-efficient design for downlink OFDMA systems, and proposed energyefficient downlink resource allocation by taking instantaneous fairness into account. Contrary to [13-15], in [16] a different EE metric that is defined as the ratio of total consumed power to the total data rate is used. In [17], instead of traditional energy-efficiency definition, a metric called effective energy efficiency (EEE) is defined. In this metric, effective capacity concept which characterizes the maximum throughput of a system subject to statistical delay-QoS requirements is used instead of Shannon's channel capacity. In [18], the authors investigated the EE resource allocation problem of the downlink transmission of OFDMA while considering discrete power levels. In the literature, the EE problem is examined in different forms under different assumptions. According to the de (...truncated)