Low-Complexity Coordinated Interference-Aware Beamforming for MIMO Broadcast Channels

Abstract

A novel Coordinated Interference-aware Beamforming (CIB) technique for Multiple-Input-Multiple-Output (MIMO) Broadcast Channels (BC) is introduced. The CIB technique uses a method based on maximization of the Signal to Interference and Noise Ratio (SINR) at the front end of each receiver to balance the signal strength and the multi-user interference plus noise. This results in a closed form solution that can be used with any number of transmit and receive antennas. The resulting computational complexity is not more than well known non-iterative linear beamforming techniques. The new technique, even when equal power is assigned to each data stream, outperforms the sum rate achieved by the non-iterative linear beamforming techniques when employing waterfilling power allocation. Optimality of CIB is analyzed in some extreme cases of Signal to Noise Ratio (SNR) and the number of users. In contract to the intuition that Block Diagonalization Zero Forcing (BDZF) and other ZF techniques perform very well in large number of users since they are designed for canceling interuser interference, the sum rate of the proposed CIB grows faster than ZF. Additionally, the CIB provides more flexibility when employing further upper layer scheduling algorithms by supporting both diversity and spatial multiplexing for each user.

Multicell Coordination via Joint Scheduling, Beamforming, and Power Spectrum Adaptation

“…For example, joint power allocation and scheduling is considered in [1], [2], [3] and the use of joint zero-forcing beamforming and user scheduling is considered in [4], [5], [6], [7]. In addition to zero-forcing beamforming, eigen-mode beamforming [8], gradient-based beamforming [9], and other heuristic interference-aware beamforming designs [10], [11] have also been considered in the literature. From a more rigorous perspective, a concept known as uplink-downlink duality has emerged as a key solution to the problem of finding the optimal beamforming vectors to minimize transmit power subject to signal-to-interference-andnoise-ratio (SINR) constraints [12], [13], [14], [15], [16], [17], [18], [19], [20].…”

Chip-Level Coordinated Interference-Aware Beamforming for MIMO-CDMA in Frequency-Selective Broadcast Channels

“…Let us denote by h7m, and hm the mth columns of HTX,k and HRX,k, respectively. Assuming all users are using chip-level MMSE receivers, the SINR of the mth entry can be expressed, as in [6], Vm = 1, ..., RG (6) wim th t N ZcHkhm with (q,j)=(RGUK) 4?k(m = (k1,1 (q,j) = (l,1) (q,j)7A(m, k) and Rx k Tx,khk Globally maximization of every r4m is difficult due to the dependency among all hX Zs. Using the approximation and the inequalities introduced in [6], the approximate on a lower bound of that SINR is > hTx k kkTx,k…”

“…In such cases, when some fairness needs to be considered by the operator, simultaneous transmission to multiple users at one time may be required. The proposed technique, similar to Coordinated Interference-aware Beamforming (CIB), for flat-fading channels [5] and [6], can provide means to schedule multiple users to be active. Chip-level receivers are well understood and discussed in [7], [8], [9].…”

Linear Beamforming for Multiuser MIMO Downlink Systems with Channel Orthogonalization

“…However, the convergence of these iterative algorithms cannot be guaranteed [12]. In order to circumvent the iterative nature of the conventional CBF, a suboptimal beamforming method was introduced in [13]. Also the author in [14] proposed a zero-forcing solution valid for two transmit antenna systems.…”