Izvorni znanstveni članak
https://doi.org/10.24138/jcomss.v10i4.119
Reduced Complexity Tree Search Algorithms for MIMO Decoding
Gajanan R Patil
; Dept of Electronics & Telecommunication Engg. Army institute of Technology Pune, India and with the Dept of Electronics & Telecommunication Engg. Sinhgad College of Engg, Pune, India
Vishwanath K Kokate
; Dept of Electronics & Telecommunication Engg. Sinhgad College of Engg. Pune, India
Sažetak
Maximum Likelihood Decoding (MLD) is computationally complex technique for decoding received information in multiple input multiple output (MIMO) systems. Tree search algorithms such as sphere decoding (SD) and QR decomposition with M survivals (QRD-M) are used to reduce the complexity keeping the performance near ML. This paper presents two techniques for reducing the computational complexities of the tree search algorithms further. The first technique is based on selecting the initial radius for sphere decoding. The main contribution of this paper is that the greedy best first search is used to compute initial radius, instead of Babai estimate. The second contribution is, QRD-M algorithm is modified to prune the nodes in the current layer based on maximum metric of child nodes of smallest surviving node. The performance of the proposed techniques is tested for different MIMO systems in terms of bit error rates (BER) and average number of nodes visited. The proposed schemes have improved computational complexity with no degradation of performance.
Ključne riječi
Best First Search; Maximum Likelihood Decoding; MIMO; QRD-M; Sphere decoding
Hrčak ID:
180048
URI
Datum izdavanja:
20.12.2014.
Posjeta: 912 *