Implementation Strategies for High-Performance Multiuser MIMO Precoders

Implementation Strategies for High-Performance Multiuser MIMO Precoders

Maitane Barrenechea (University of Mondragón, Spain), Mikel Mendicute (University of Mondragón, Spain), Andreas Burg (École Polytechnique Fédérale de Lausanne (EPFL), Switzerland) and John S. Thompson (University of Edinburgh, UK)
DOI: 10.4018/978-1-4666-6034-2.ch006
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The multiuser MIMO environment enables the communication between a base-station and multiple users with several antennas. In such a scenario, the use of precoding techniques is required in order to detect the signal at the users' terminals without any cooperation between them. This contribution presents various designs and hardware implementations of a high-capacity precoder based on vector perturbation. To this aim, three tree-search techniques and their associated user-ordering schemes are investigated in this chapter: the well-known K-Best precoder, the fixed-complexity Fixed Sphere Encoder (FSE), and the variable complexity Single Best-Node Expansion (SBE). All of the aforementioned techniques aim at finding the most suitable perturbation vector within an infinite lattice without the high computational complexity of an exhaustive search.
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With the advent of new communication technologies, the interest in MIMO has recently evolved towards the development of multi-user schemes which consider more complex albeit realistic scenarios with multiple terminals sharing the time, space, bandwidth and power resources available in a wireless network. Consequently, a great part of the latest research on innovative wireless multi-antenna technologies has been focused on multi-user MIMO (MU-MIMO) environments.

A multi-antenna and multi-user system provides a set of advantages over point-to-point MIMO transmissions. One of the main features of MU-MIMO is its greater immunity to propagation shortcomings derived from antenna correlation. Being the antennas hosted at scattered users, the correlation coefficients are inherently low, which allows to overcome the usual problems related to channel rank loss. Another interesting property of MU-MIMO is that direct line of sight propagation, which greatly degrades the quality of the communication link in single-user MIMO systems with spatial multiplexing, does not pose a problem in a multi-user setup. Furthermore, MU-MIMO enables obtaining a spatial multiplexing gain at the base station without the requirement of multi-antenna receivers. This allows for the implementation of small, low-cost and low-power terminal devices as the computational load is transferred to the base station (Gesbert, Kountouris, Heath & Chae, 2007).

Nevertheless, the multi-user setup also poses a set of problems that do not exist in the single-user model. For example, the lack of interaction between the users forces the base station to acquire instantaneous knowledge of the channel in order to allow for independent detection of each user's information stream at the receivers. Additionally, the independence between the receive antennas may also incur in an outage situation if the sub-channel directed to a single-antenna user undergoes severe fading. Such a situation in MIMO systems can be overcome with simple diversity techniques.

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