A Simple Channel Simulator for Multiuser MIMO Broadcast Channel Systems

This paper presents an efiort to construct a multiuser (MU) multiple-input multiple- output (MIMO) broadcast channel (BC) model. Our method is able to adequately build in the correlation and mutual coupling, which are important factors afiecting the multi-antenna arrays. This helps to decrease the need for complex mathematical analysis and allows an easy simulation of the MU MIMO BC performance. The charac-terizations of MU MIMO systems are done and the impact of varying the number of transmitting and receiving antennas is explored. These insights are useful in physical realization of the systems. 1. INTRODUCTION In recent years, as demands for increasing capacity networks rises, researches in antenna array communication are of much greater interest. Multiple-input-multiple-output (MIMO) systems are hence a natural extension of developments (1) since MIMO systems are able to turn multipath propagation, which is usually a pitfall in wireless transmission, into a beneflt. By doing so, the performance and capacity of the MIMO systems are increased tremendously. The capacity of single-user MIMO Gaussian channels was flrst studied by Foschini and Gans (2), and Telatar (3). The researches on MIMO systems are also extended to the multiuser cases which can be classifled as MIMO multiple access channel (MAC) and MIMO broadcast channels (BC). The sum rate of MIMO MAC system is easy to be obtained due to its convex property (4{7). The sum rate of the MU MIMO BC achieved with Dirty Paper Coding (DPC) (8), however, is not of the convex form. Based on the duality between MIMO MAC and BC systems, sum rate of MU MIMO BC can be obtained (6,7). Also, in (9), Weingarten showed that the capacity region achieved by using the DPC is exactly the same as that of the MU MIMO BC, given that the transmit powers are equal. Here, the method to calculate the (DPC) sum-rate capacity of the BC is the sum power iterative water fllling method proposed in (7). In this paper, our efiort will be focused on modelling the MU MIMO BC system. E-cient and accurate channel modeling is important to help predict the performance of MIMO communication systems. However, due to the large number of parameters that are involved in channel modeling, an analytical approach is usually too di-cult. This leads to the use of computer simulations. The challenge is to employ a method that is able to take all the parameters into account, and is also able to apply to most applications. Various methods are available for the simulation of the capacity of single user MIMO systems (10). Such simulation is lacking in MU MIMO system where extensive researches on its performance are still very much ongoing. In this paper, an e-cient simulation algorithm to simulate the MU MIMO system is presented. The method of modelling a single user MIMO system was proposed by Hui and Wang (11) which involves having scatterers around both the transmitting and receiving antennas to introduce random scattering events. This work is extended in this paper to include the MU MIMO system, where instead of only one single user in the receiving end, two users were implemented. Various MU MIMO systems will be built and characterizations can be done. From there, the impact of varying the number of transmitting antennas and receiving antennas will be examined. In this paper, we consider a two user BC system, where each user j and k has Rj = Rk > 1 re- ceiving antennas and the broadcast transmitter has T ‚ 1transmitting antennas. The transmitting antennas are surrounded by P scatterers where P is flxed at 50 in the far fleld, and this provides the scattering events. On the receiving side, both users are surrounded by Q scatterers which is varied when appreciate to investigate the efiects of scattering on the capacity. Between the two antennas, the paths of the signals are assumed to be completely random and that each propagation paths are associated with a loss factor which follows a Gaussian distributed random number which has a mean of 0 and a variance of 1. The model of the MU BC MIMO system is summarised in Fig. 1. As shown in Fig. 1, the signals follow a propagation path when travelling from the transmitter to the receivers. The loss factor associate with the path will cause the E-fleld that is received in the scatterers at the receiving end, which in turns afiects the current