Dynamic Spectrum Management Project

Wireless Research

Prior Research

In a wireless environment, single-user capacity can increase dramatically through the use of spatial diversity in the form of multiple transmit and receive antennas. Many results have been derived for single-user multiple-antenna systems, including linear capacity gain with linearly increasing number of antennas [i], a low-complexity DFE-like decoding scheme known as BLAST [ii], improved performance through space-time coding [iii], and the optimal capacity-achieving scheme based on multi-carrier transmission and singular value decomposition [1]. Our work in the single-user case addresses the use of space-time coding in various scenarios ([2], [3] and [4]) and investigates the improvement of low-complexity decoding schemes ([5]).

Following the single-user MIMO results, our group works on multiuser MIMO systems. In a multiuser wireless scenario, the system performance can be limited and/or highly degraded because of the presence of Co-Channel Interference (CCI). Typically beam forming is used to improve performance in such situations, thereby sacrificing some antenna diversity. We have found a sub optimal multiuser detection scheme using Singular Value Decomposition (SVD) that can separate the transmission of interest in the space domain, without loss of antenna diversity while outperforming beamforming and space-time equalization [7], [8].

An assessment of the level of improvement provided by the optimal scheme appears in [9]. This paper investigated the possibility of using 'multiuser diversity' (channel diversity stemming from independence of user locations) to improve performance. The largest gains were identified for highly correlated channel environments.

Optimization of the transmit spectrum to obtain capacity was the next concern. As explained in the Spectrum Balancing Section, we found an iterative water-filling algorithm that efficiently finds the sum capacity achieving spectrums of multi-antenna multiple access channels [10]. Utilizing the analysis in this paper, we were able to prove some interesting results. In [11], the optimal power control scheme achieving sum capacity for fading channels was investigated. This paper also showed that the total number of users that can simultaneously transmit is upper limited by a function of number of receive antennas. [12] shows that beam forming is optimal if the number of users are large enough. When users in a multi-access channel does not know anything about the channel (not even the channel distribution), uniform power allocation can be shown to be the solution [13].

Following these analysis, we designed a system with multiple antennas only at the base station side [14]. Even though each user has only one antenna, total throughput of the system is extremely high since many users exist in the system. It even works well in highly correlated channels, because multiuser diversity overcomes the correlation of channels.

(References [12], [13] and [14] are not officially published. They will be linked on this webpage after publication. All other references are linked to 'Publications on Wireless').

Ongoing and Future Research

Currently we are working on extending the theoretical understanding of MIMO systems and applying them to practical scenarios. We are looking at transmit optimization and decoding strategies that provide a good balance between spectral efficiency, complexity and robustness in WAN and LAN environments. Some specific areas of interest are: