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Fast method for precoding and decoding of distributive multi-input multi-output channels in relay-based decode-and-forward cooperative wireless networks

Fast method for precoding and decoding of distributive multi-input multi-output channels in relay-based decode-and-forward cooperative wireless networks

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It is well-known that the performance of the relay-based decode-and-forward (DF) cooperative networks outperforms the performance of the amplify-and-forward cooperative networks. However, this performance improvement is accomplished at the expense of adding more signal processing complexity (precoding/decoding) at each relay node. In this study, the authors tackle this signal processing complexity issue by proposing a Jacket-based fast method for reducing the precoding/decoding complexity in terms of time computation. Jacket transforms have shown to find applications in signal processing and coding theory. Jacket transforms are defined to be n×n matrices A=(ajk) over a field ℱ with the property AA=nIn, where A is the transpose matrix of the element-wise inverse of A, that is, A=(akj−1), which generalise Hadamard transforms and centre weighted Hadamard transforms. In particular, exploiting the Jacket transform properties, the authors propose a new eigenvalue decomposition (EVD) method with application in precoding and decoding of distributive multi-input multi-output channels in relay-based DF cooperative wireless networks in which the transmission is based on using single-symbol decodable space-time block codes. The authors show that the proposed Jacket-based method of EVD has significant reduction in its computational time as compared to the conventional-based EVD method. Performance in terms of computational time reduction is evaluated quantitatively through mathematical analysis and numerical results.

http://iet.metastore.ingenta.com/content/journals/10.1049/iet-com.2008.0712
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