Reduced Complexity Interference Avoidance Scheme Based on User Grouping in Dense Cellular Networks

Awad, J. F., Imran, M. A. and Tafazolli, R. (2013) Reduced Complexity Interference Avoidance Scheme Based on User Grouping in Dense Cellular Networks. In: Proceedings of the 2013 19th European Wireless Conference (EW), Guildford, UK, 16-18 Apr 2013, ISBN 9783800734986

Abstract

In current day dense cellular networks, inter-cell interference presents a real obstacle to achieving high data rates and it severely limits users?? performance with the vulnerable users being the worst affected. In this paper, we propose an intercell interference avoidance scheme for the downlink of multicell OFDM systems. Using this scheme, we endeavor to reduce the interference on vulnerable users caused when transmitting to ??healthy?? users in order to improve the vulnerable users?? performance with minimal impact on the total system throughput. We first start by grouping the users into two groups based on various performance criteria then we introduce a performance metric which is dependent on these criteria. Furthermore, resource allocation techniques favoring the vulnerable users are proposed. We propose a subcarrier allocation technique that prohibits the subcarrier sharing between vulnerable users. Then, based on the previously introduced metric, a weight calculation method for the power control of the weighted sum rate maximization problem is proposed. The effectiveness of the proposed scheme is verified through simulations where it is shown that, with negligible degradation in total system throughput, as little as 2.6, the proposed scheme is able to improve the spectral efficiency of the worst 20 of users by up to 22 and also increase the fairness, especially in dense cellular systems. Index Terms ?? Interference avoidance, inter-cell interference coordination, critical users, user grouping, resource allocation, weight calculation.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Imran, Professor Muhammad
• Authors: Awad, J. F., Imran, M. A., and Tafazolli, R.
• College/School: College of Science and Engineering > School of Engineering
• ISBN: 9783800734986
• Published Online: 20 August 2013