Maximizing Energy-Efficiency in Multi-Relay OFDMA Cellular Networks

This contribution presents a method of obtaining the optimal power and subcarrier allocations that maximize the energy-efficiency (EE) of a multi-user, multi-relay, orthogonal frequency division multiple access (OFDMA) cellular network. Initially, the objective function (OF) is formulated as the ratio of the spectral-efficiency (SE) over the power consumption of the network. This OF is shown to be quasi-concave, thus Dinkelbach's method can be employed for solving it as a series of parameterized concave problems. We characterize the performance of the aforementioned method by comparing the optimal solutions obtained to those found using an exhaustive search. Additionally, we explore the relationship between the achievable SE and EE in the cellular network upon increasing the number of active users. In general, increasing the number of users supported by the system benefits both the SE and EE, and higher SE values may be obtained at the cost of EE, when an increased power may be allocated.Comment: 6 pages, 5 figures, 1 table, to appear in Proc. IEEE 2013 56th Global Communications Conference (GLOBECOM 2013), Atlanta, USA, December, 201

Energy-efficiency for MISO-OFDMA based user-relay assisted cellular networks

The concept of improving energy-efficiency (EE) without sacrificing the service quality has become important nowadays. The combination of orthogonal frequency-division multiple-access (OFDMA) multi-antenna transmission technology and relaying is one of the key technologies to deliver the promise of reliable and high-data-rate coverage in the most cost-effective manner. In this paper, EE is studied for the downlink multiple-input single-output (MISO)-OFDMA based user-relay assisted cellular networks. EE maximization is formulated for decode and forward (DF) relaying scheme with the consideration of both transmit and circuit power consumption as well as the data rate requirements for the mobile users. The quality of-service (QoS)-constrained EE maximization, which is defined for multi-carrier, multi-user, multi-relay and multi-antenna networks, is a non-convex and combinatorial problem so it is hard to tackle. To solve this difficult problem, a radio resource management (RRM) algorithm that solves the subcarrier allocation, mode selection and power allocation separately is proposed. The efficiency of the proposed algorithm is demonstrated by numerical results for different system parameter

Sum Rate Maximized Resource Allocation in Multiple DF Relays Aided OFDM Transmission

In relay-aided wireless transmission systems, one of the key issues is how to decide assisting relays and manage the energy resource at the source and each individual relay, to maximize a certain objective related to system performance. This paper addresses the sum rate maximized resource allocation (RA) problem in a point to point orthogonal frequency division modulation (OFDM) transmission system assisted by multiple decode-and-forward (DF) relays, subject to the individual sum power constraints of the source and the relays. In particular, the transmission at each subcarrier can be in either the direct mode without any relay assisting, or the relay-aided mode with one or several relays assisting. We propose two RA algorithms which optimize the assignment of transmission mode and source power for every subcarrier, as well as the assisting relays and the power allocation to them for every {relay-aided} subcarrier. First, it is shown that the considered RA problem has zero Lagrangian duality gap when there is a big number of subcarriers. In this case, a duality based algorithm that finds a globally optimum RA is developed. Second, a coordinate-ascent based iterative algorithm, which finds a suboptimum RA but is always applicable regardless of the duality gap of the RA problem, is developed. The effectiveness of these algorithms has been illustrated by numerical experiments.Comment: 13 pages in two-column format, 10 figures, to appear in IEEE Journal on Selected Areas in Communication

Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory

Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization