Technical Session: Poster
Signal Processing for Wireless Communications
10:15 - 11:30 | Wed 6 Jul | Salisbury B | S11
Interference Alignment (IA) is a signal processing method that, in a large sense, makes use of the increasing signal dimensions available in the system through MIMO and OFDM technologies in order to globally reduce the interference suffered by users in a network. In this paper, we address the problem of downlink cellular networks, so-called interfering broadcast channels, where mobile users at cell edges may suffer from high interference and thus poor performance. Starting from the downlink IA scheme proposed by Suh et al., a new approach is proposed where each user feeds back multiple selected received signal directions with high signal-to-interference gain. A scheduler selects a subset of users to be served simultaneously balancing between sum-rate performance and fairness. The performance of such an approach with an exhaustive search is shown to be good in small dimension systems, but may become untractable in dense network scenarios where many users send simultaneous requests. Therefore, we develop a sub-optimal scheduler that greatly decreases the complexity while preserving a near-optimal data rate gain. Simulation results highlight the efficiency of our proposed scheme, and show a significant spectral efficiency gain over reference schemes in practical scenarios of interest.
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