关键词: 干扰对齐, 发射天线选择, 低复杂度, 容量

Abstract:

Starting from the investigation of the optimal transmit antenna selection (TAS) algorithm based on the exhaustive search and distributed interference alignment (IA), a low complexity TAS algorithm is proposed for multi-cell IA systems. The proposed algorithm utilizes the greedy search strategy and the distributed IA with partial iterations to reduce the computational complexity. In the proposed algorithm, the TAS scheme for each base station is optimized successively in a way that the system sum capacity is increased under the condition that the TAS schemes for the other base stations remain unchanged. Complexity analysis and simulation results show that the proposed algorithm can sharply reduce the computational complexity while the performance of system sum capacity is close to that of the optimal TAS algorithm. Moreover, by properly choosing the iteration number of partial iterations, the proposed algorithm can achieve an effective tradeoff between system sum capacity and computational complexity.

Key words: interference alignment (IA), transmit antenna selection (TAS), low complexity, capacity