This paper focuses on the linear transceiver design for multiple input multiple output（MIMO） interference channel（IC）, in which a bounded channel error model is assumed. Two optimization problems are formulated as...This paper focuses on the linear transceiver design for multiple input multiple output（MIMO） interference channel（IC）, in which a bounded channel error model is assumed. Two optimization problems are formulated as minimizing maximum per-user mean square error（MSE） and sum MSE with the per-transmitter power constraint. Since these optimization problems are not jointly convex on their variable matrices, the transmitter and receiver can be optimized alternately respectively. For each matrix, an approximated approach is presented where the upper bound of constraint is derived so that it has less semidefinite, thus the problem can be viewed as second-order-cone programming（SOCP） and gets less computational complexity. Compared with the conventional S-procedure method, the proposed approach achieves similar performance, but reduces the complexity significantly, especially for the system with large scale number of antennas.展开更多
基金supported by the National Natural Science Foundation of China (61401270, 61271283)
文摘This paper focuses on the linear transceiver design for multiple input multiple output（MIMO） interference channel（IC）, in which a bounded channel error model is assumed. Two optimization problems are formulated as minimizing maximum per-user mean square error（MSE） and sum MSE with the per-transmitter power constraint. Since these optimization problems are not jointly convex on their variable matrices, the transmitter and receiver can be optimized alternately respectively. For each matrix, an approximated approach is presented where the upper bound of constraint is derived so that it has less semidefinite, thus the problem can be viewed as second-order-cone programming（SOCP） and gets less computational complexity. Compared with the conventional S-procedure method, the proposed approach achieves similar performance, but reduces the complexity significantly, especially for the system with large scale number of antennas.
