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A Low-Complexity Solution to Decode Diversity-Oriented Block Codes in MIMO Systems with Inter-Symbol Interference



Hamid Gharavi, Chong Xu


In this paper we firstly propose a block-code based general model to combat the Inter-Symbol Interference (ISI) caused by frequency selective channels in a Multi-Input Multi- Output (MIMO) system and/or by asynchronous cooperative transmissions. The general model is not only exemplified by the Time-Reversed Space-Time Block Code (TR-STBC) scheme, but also by the Asynchronous Cooperative Liner Dispersion Codes (ACLDC) scheme. In these schemes a guard interval has to be inserted between adjacent transmission blocks to mitigate the effect of ISI. Consequently, this could degrade the effective symbol rate for a small block size. A larger block size would enhance the effective symbol rate and also substantially increase the decoding complexity. In the general model proposed in this paper, we further present a novel low-complexity breadthadjustable tree-search algorithm and compare it with Sphere-Decoding (SD) based algorithms. With simulation results we will illustrate that our algorithm is able to achieve the optimal performance in terms of Bit Error Rate (BER) with a complexity much lower than the SD-based algorithms, whether the ACLDC or TR-STBC scheme is employed. Through simulation we further demonstrate that when the block size of the ACLDC is equivalent to 20, the complexity of the proposed algorithm is only a fraction of 10−8 that of the Maximum Likelihood (ML) algorithm. This would allow us to practically enhance the effective symbol rate without any performance degradation.
IEEE Transactions on Wireless Communications


Multiput Input Multiput Output (MIMO), tansmit diversity, Space-Time Block Code (STBC)


Gharavi, H. and Xu, C. (2012), A Low-Complexity Solution to Decode Diversity-Oriented Block Codes in MIMO Systems with Inter-Symbol Interference, IEEE Transactions on Wireless Communications, [online], (Accessed December 10, 2023)
Created October 1, 2012, Updated February 19, 2017