Energy‐efficient relay deployment in cellular systems using fractional frequency reuse and transmit antenna selection techniques

Abstract

To cope with the steep surge in mobile traffic, network operators are now expanding their infrastructure for mobile access networks. However, since energy costs and greenhouse gas emissions are a large burden to network operators, they are making great efforts to improve the energy efficiency (EE) of their networks by promising techniques, including relaying and multiple-input multiple-output (MIMO). Relaying technique can considerably improve the EE when the interference between base stations (BSs) and relay stations (RSs) is effectively coordinated by an elaborate relay deployment using the fractional frequency reuse (FFR) technique. Also, MIMO techniques improve the radio channel quality through diversity gains, so the system capacity and the EE can be improved. Therefore, a combination of relaying/MIMO techniques can be considered to achieve the higher performance, particularly, if the system complexity and costs of using such techniques are low. Since the transmit antenna selection (TAS), one of MIMO techniques, can provide a sufficient transmit diversity gain and satisfy the requirements for low complexity and cost (thus, practical), the TAS is recommended for use with the relaying technique. In this paper, for an energy-efficient relay deployment using FFR and TAS techniques, we derive the EE and the resource partitioning according to RS positions and the number of BS antennas by a mathematical analysis. Then, the optimal RS positions according to the number of antennas can be determined by an optimization approach. The numerical and simulation results indicate that the proposed analysis method can efficiently analyze the EE and locate the RSs. KEYWORDS energy-efficient cell planning, interference coordination and resource partitioning with fractional frequency reuse (FFR), relay deployment using multiple antennas, relaying technique with transmit antenna selection (TAS)

Optimal Radio Propagation Modeling and Parametric Tuning Using Optimization Algorithms

“…In recent years, the system design, deployment, and management of wireless radio frequency (RF) networks have become more tasking and complicated [1][2][3]. The intricacies and complications may be attributed to many dynamic factors.…”