Quasi maximum posterior probability detection method for layer space hour code system and system thereof

Abstract

The present invention relates to a quasi-maximum posteriori probability detection method for hierarchical space-time code system and its system. Said detection method can utilize QR of hierarchical space-time code system to decompose an interference deletion structure, and includes the following steps: calculating partial vector posteriori probability, only remaining maximum one or one group of partial vector, deleting other partial vectors, width priority search to obtain one or one group of vectors with maximum posteriori probability, using one vector with maximum posteriori probability as estimated value of transmitting signal vector. Said detection can greatly reduce complexity of detection, at the same time can retain higher performance.

Description

technical field [0001] The invention relates to a quasi-maximum a posteriori probability detection method and system for a layered space-time code system, and belongs to the technical field of signal detection and estimation of a wireless communication system. Background technique [0002] Now, the spectrum resource of the wireless channel is already very limited, but the wireless communication system is required to be able to transmit data at a higher rate. Since the channel capacity of multiple-input multiple-output (MIMO) is linearly related to the minimum number of transmitting and receiving antennas, the academic community generally believes that the multi-antenna technology is the main solution for future broadband wireless communication systems. Among them, the hierarchical space-time code structure has received more attention because it can obtain the highest multiplexing gain. [0003] The existing detection methods of layered space-time codes mainly include linear...

AI Technical Summary

Problems solved by technology

However, there are still deficiencies in the sphere decoding algorithm: (1) the complexity of the sphere decoding has a cubic relationship with the number of transmitting antennas, which is still relatively high; (2) the sphere decoding algorithm uses depth-first search in the symbol vector tree diagram, because There is a backtracking process in the depth-first search, so the nodes in the tree diagram may be visited multiple times, which makes the search process more cumbersome; (3) the sphere decoding algorithm needs to select the search radius before searching. If the search radius is not selected properly, the complexity will be unacceptable. control

For example, if the selected search radius is too large, it is necessary to visit almost all nodes in the symbolic vector tree diagram, and the complexity is too high; if the selected search radius is too small, there may not be a path within the search radius after the search ends , causing the algorithm not to converge, it is necessary to increase the search radius and then search again, which will result in multiple repeated searches and higher complexity

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