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| Partial a Posteriori Probabilities Based Soft Detection for Turbo-MIMO Systems |
| You Ming-hou①②; Tao Xiao-feng①②; Cui Qi-mei①②; Zhang Ping①② |
| ①Wireless Technology Innovation Institute, Beijing University of Posts and Telecommunications, Beijing 100876, China; ②Key Laboratory of Universal Wireless Communications, (Beijing University of Posts and Telecommunications |
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Abstract Iterative Tree Search (ITS) is an efficient M-algorithm based soft MIMO detection scheme. However, ITS often faces the problem that Log-Likelihood Ratio (LLR) values of some detected bits can not be evaluated. Although it can be somewhat solved by setting the LLR magnitude for these bits to a constant value—LLR clipping, the system performance would be degraded. To overcome this problem, this paper presents a new M-algorithm based soft detection scheme. The scheme recursively calculates the a posterior probabilities of partial symbol sequences at each stage of the tree, based on which the LLRs of those bits from the first stage to the current one are approximately computed，and then, by using M-algorithm, retains partial symbol sequences and extends them to the next stage. The scheme can ensure that the LLR of each bit can be calculated, and provide highly reliable LLRs. Considering that the LLRs of some bits may be evaluated several times, a reduced-complexity implementation method is given in the paper. In addition, the paper suggests a simple approach for calculating the a posterior probabilities of symbol sequences. Finally, simulation results show that the proposed algorithm can obtain better performance than ITS and achieve good performance-complexity trade-off.
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Received: 24 July 2009
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Corresponding Authors:
You Ming-hou
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2010, Vol. 32 
