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Open Access research with a European policy impact...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by Strathclyde researchers, including by researchers from the European Policies Research Centre (EPRC).

EPRC is a leading institute in Europe for comparative research on public policy, with a particular focus on regional development policies. Spanning 30 European countries, EPRC research programmes have a strong emphasis on applied research and knowledge exchange, including the provision of policy advice to EU institutions and national and sub-national government authorities throughout Europe.

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Training based channel estimation algorithms for dual hop MIMO OFDM relay systems

Millar, Andrew P. and Weiss, Stephan and Stewart, Robert W. (2015) Training based channel estimation algorithms for dual hop MIMO OFDM relay systems. IEEE Transactions on Communications, 63 (12). pp. 4711-4726. ISSN 0090-6778

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In this paper we consider minimum mean square error (MMSE) training based channel estimation for two-hop multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) relaying systems. The channel estimation process is divided into two main phases. The relay-destination channel is estimated in the first phase and can be obtained using well known point-to-point MIMO OFDM estimation methods. In the second phase, the source-relay channel is estimated at the destination with the use of a known training sequence that is transmitted from the source and forwarded to the destination by a non-regenerative relay. To obtain an estimate of the source-relay channel, the source training sequence, relay precoder, and destination processor, require to be optimised. To solve this problem we derive an iterative algorithm that involves sequentially solving a number of convex optimisation problems to update the source, relay, and destination design variables. Since the iterative algorithm may be too computationally expensive for practical implementation we then derive simplified solutions that have reduced computational complexity. Simulation results demonstrate the effectiveness of the proposed algorithms.