A comparative analysis of spatial multiplexing techniques for outdoor MIMO-OFDM systems with a limited feedback constraint

• In this paper, we analyze spatial multiplexing techniques for the downlink of a multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) system. Our study is focused on outdoor environments characterized by a moderate angular spread. We consider two techniques that are able to separate the downlink data streams associated with different users and to guarantee a fixed error probability by exploiting limited feedback from each user. The grid of beams (GoBs) and the proposed adaptive GoB (AGoB) differ in the way the precoders are designed (by adaptive or fixed processing) and in their scheduling policy. The new AGoB is able to harness partial knowledge of the downlink channel spatial structure to better select the users and adjust their precoders for downlink transmission. The performances of GoB and AGoB are compared in this paper in terms of throughput and cell coverage capability. The radio interface is adapted to fit the requirements for the adaptive modulation and coding with advanced antenna system (AMC-AAS) mode of the IEEE 802.16-2005 standard. Numerical results show that, as long as the channel exhibits a limited angular spread at the base station, the AGoB technique is able to provide significant throughput gains compared with the fixed GoB approach. On the other hand, large angular spreads are proved to have a substantial impact on system performance as the benefits of adaptation are significantly reduced.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)

Nyckelord

MIMO-OFDM systems

multiuser diversity

spatial multiplexing

zero-forcing beamforming

Signal processing

Signalbehandling

Elektroteknik med inriktning mot signalbehandling

Electrical Engineering with specialization in Signal Processing

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