System Capacity Analysis and Antenna Placement Optimization for Downlink Transmission in Distributed Antenna Systems

System capacity and antenna placement play crucial roles in wireless communication systems, and they are of great value to network planning. In this paper, we are motivated to analyze the system capacity and optimize the antenna placement in distributed antenna systems. This paper establishes a composite channel model which takes path loss, lognormal shadowing and Rayleigh fading into consideration. To reduce the computational complexity, an approximate theoretical expression of system capacity is derived with selective transmission at the transmitter and maximal ratio combining at the receiver. An antenna placement optimization problem is formulated, and then a genetic algorithm (GA) based searching scheme is proposed to solve the proposed optimization problem. The computational complexity analysis indicates that the proposed GA-based searching scheme is computationally efficient in terms of both running time and storage space. Numerical results show that the approximate theoretical expression of system capacity can provide a very good approximation to the simulation results, and the proposed GA-based searching scheme for solving the antenna placement optimization problem can consistently offer a large capacity gain over other existing schemes.