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Interference alignment in UMTS Long Term Evolution | IEEE Conference Publication | IEEE Xplore

Interference alignment in UMTS Long Term Evolution


Abstract:

In this paper the performance of interference alignment is evaluated for the downlink of 3GPP UMTS LTE via the Vienna LTE Link Level simulator. Interference alignment is ...Show More

Abstract:

In this paper the performance of interference alignment is evaluated for the downlink of 3GPP UMTS LTE via the Vienna LTE Link Level simulator. Interference alignment is compared to closed-loop spatial multiplexing, a non-cooperative communication scheme. In order to reduce the computational complexity of solving the interference alignment problem for each subcarrier separately, the same precoding and interference suppression matrices are used for disjoint subsets of subcarriers. The performance impairment in terms of average throughput reduction of this approach is analyzed numerically. Furthermore, the performance of interference alignment is investigated for realistic fast-fading channels employing outdated precoding and interference suppression matrices.
Date of Conference: 29 August 2011 - 02 September 2011
Date Added to IEEE Xplore: 02 April 2015
Print ISSN: 2076-1465
Conference Location: Barcelona, Spain

1. Introduction

Interference alignment (IA) is a cooperative transmission strategy for the interference channel that results in a linearly scaling sum-rate with the number of users in the system in the high SNR regime [1]. IA is based only on linear precoding at the transmitters and zero-forcing at the receivers but requires extensive channel knowledge in order to sufficiently suppress the interference at all receivers simultaneously [2]. The key idea of IA is to use precoding matrices at all transmitters such that the interference aligns at each receiver and spans only a subspace of the receive space, thus providing interference free subspaces for the desired signals. In some simple scenarios there exist closed-form solutions of the IA problem [1]. For scenarios with arbitrary number of users, transmit and receive antennas as well as number of spatial streams, iterative algorithms were introduced in [3]–[5]. In [6] IA feasibility conditions were derived for certain scenarios, while they are still unknown for arbitrary scenarios.

References

References is not available for this document.