A Comparison of Time-Sharing, DPC, and Beamforming for MIMO Broadcast Channels With Many Users

Abstract

Abstract-In this letter, we derive the scaling laws of the sum rate for fading multiple-input multiple-output Gaussian broadcast channels using time sharing to the strongest user, dirty-paper coding (DPC), and beamforming, when the number of users (receivers) n is large. Throughout the letter, we assume a fix average transmit power and consider a block-fading Rayleigh channel. First, we show that for a system with M transmit antennas and users equipped with N antennas, the sum rate scales like M log log nN for DPC, and beamforming when M is fixed and for any N (either growing to infinity or not). On the other hand, when both M and N are fixed, the sum rate of time sharing to the strongest user scales like min(M; N ) log log n. Therefore, the asymptotic gain of DPC over time sharing for the sum rate is (M= min(M; N )) when M and N are fixed. It is also shown that if M grows as log n, the sum rate of DPC and beamforming will grow linearly in M , but with different constant multiplicative factors. In this region, the sum-rate capacity of time -sharing scales like N log log n.

On Multi-User Gain in MIMO Systems with Rate Constraints

“…The key problem is sum-power minimization given a fixed rate constraint for every user. This problem is important for delay sensitive services, such as real time video, where scheduling [4][5] [6] [7] may be difficult due to fairness issues. Several algorithms [8] [9] have been proposed to compute the minimum sum power (MSP) solution for this problem.…”

“…The feedback information for each user is also reduced to a vector (instead of a matrix). This strategy has been previously considered in [6][10] [11] for throughput maximization in MIMO broadcast channels (BCs).…”

Taking advantage of multi-user diversity in OFDM systems

“…For example, Viswanath et al [2] used opportunistic beamforming in cellular system models to achieve the gains of true beamforming without the transmitter needing to employ any further coding beyond that of single antenna transmissions. Other techniques in [3], [4] have also taken advantage of multi-user diversity.…”

Cooperation-Multiuser Diversity Tradeoff in Wireless Cellular Networks

“…Sharif and Hassibi introduced a new approach [4], [8] to search for the best SINR in the network. Their approach requires M complex numbers for feedback instead of complete CSI information, and achieves the same capacity of K log log M similar to DPC.…”