Asymptotic analysis of distributed multi-cell beamforming

Abstract

We consider the problem of multi-cell downlink beamforming with N cells and K terminals per cell. Cooperation among base stations (BSs) has been found to increase the system throughput in a multi-cell set up by mitigating inter-cell interference. Most of the previous works assume that the BSs can exchange the instantaneous channel state information (CSI) of all their user terminals (UTs) via high speed backhaul links. However, this approach quickly becomes impractical as N and K grow large. In this work, we formulate a distributed beamforming algorithm in a multi-cell scenario under the assumption that the system dimensions are large. The design objective is the minimize the total transmit power across all BSs subject to satisfying the user SINR constraints while implementing the beamformers in a distributed manner. In our algorithm, the BSs would only need to exchange the channel statistics rather than the instantaneous CSI. We make use of tools from random matrix theory to formulate the distributed algorithm. The simulation results illustrate that our algorithm closely satisfies the target SINR constraints when the number of UTs per cell grows large, while implementing the beamforming vectors in a distributed manner.

Message Passing Algorithm for Distributed Downlink Regularized Zero-Forcing Beamforming with Cooperative Base Stations

“…Additionally, comparing to BP-RZFBF, AMP-RZFBF and CCoI-aided AMP-RZFBF only slightly degrades the convergence rate. This result is quite different from several earlier designs based on CCoI, e.g., [31,32]. Usually, when some calculations are approximated by the CCoI, an obvious degradation in performance would be observed but this is not the case in our scheme.…”

“…Simulation results show that CCoI-aided AMP-RZFBF achieves promising results, which are different from earlier results based on the CCoI, e.g., [31,32], where a performance degeneration is usually expected.…”

Energy Efficient Coordinated Beamforming for Multicell System: Duality-Based Algorithm Design and Massive MIMO Transition

“…Furthermore, the differential of the Stieltjes transform of the matrix AA H can be calculated with the method used in [33].…”

“…In [27], [28], the signal to interference plus noise ratio (SINR) balancing problem for the multicell massive MIMO system was solved by deriving the asymptotic expression of the achievable SINR based on large-dimension random matrix theory (RMT) [29]- [32]. Furthermore, the asymptotic properties of the SINR were also used to address the power minimization problem subject to some predefined SINR constraints [33]- [35]. More recently, energy-efficient transmission design for massive MIMO systems has also drawn much attention.…”

On Queue-Aware Power Control in Interfering Wireless Links: Heavy Traffic Asymptotic Modelling and Application in QoS Provisioning

“…For the case of multiple antenna transmitters, each transmitter can acquire the channel realization of its respective receiver. See [7] for an algorithm requiring little information exchange between transmitters and [27] for a decentralized algorithm to achieve the desired equilibrium rates.…”