A new effective branch-and-bound algorithm to the high order MIMO detection problem

Ye Tian, Ke Li, Wei Yang and Zhiyong Li ()
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Ye Tian: Southwestern University of Finance and Economics
Ke Li: Southwestern University of Finance and Economics
Wei Yang: Southwestern University of Finance and Economics
Zhiyong Li: Southwestern University of Finance and Economics

Journal of Combinatorial Optimization, 2017, vol. 33, issue 4, No 14, 1395-1410

Abstract: Abstract This paper develops a branch-and-bound method based on a new convex reformulation to solve the high order MIMO detection problem. First, we transform the original problem into a $$\{-1,1\}$$ { - 1 , 1 } constrained quadratic programming problem with the smallest size. The size of the reformulated problem is smaller than those problems derived by some traditional transformation methods. Then, we propose a new convex reformulation which gets the maximized average objective value as the lower bound estimator in the branch-and-bound scheme. This estimator balances very well between effectiveness and computational cost. Thus, the branch-and-bound algorithm achieves a high total efficiency. Several simulations are used to compare the performances of our method and other benchmark methods. The results show that this proposed algorithm is very competitive for high accuracy and relatively good efficiency.

Keywords: MIMO detection problem; Quadratic Programming; New convex reformulation; Branch-and-Bound algorithm (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s10878-016-0045-5

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