Sande, Malcolm MakomboreroHamouda, SoumayaMaharaj, Bodhaswar Tikanath Jugpershad2018-10-032018-10-032018-04Sande, M.M., Hamouda, S. & Maharaj, B.T. 2018, 'Fast converging robust beamforming for massive MIMO in heterogeneous networks', IEEE Access , vol. 6, pp. 23918-23928.2169-3536 (online)10.1109/ACCESS.2018.2829534http://hdl.handle.net/2263/66684The use of massive multiple-input multiple-output (MIMO) base stations in heterogeneous networks (HetNets) offers an increase in throughput without increasing the bandwidth, but with reduced power consumption. In this paper, we investigate the optimization problem of signal-to-interference-plusnoise ratio balancing for the case of imperfect channel state information at the transmitter. We present a fast converging robust beamforming solution for macrocell users in a typical HetNet scenario with massive MIMO at the base station. The proposed method applies the matrix stuf ng technique and the alternative direction method of multipliers to give an ef cient solution. Simulation results of a single-cell heterogeneous network show that the proposed solution yields performance with modest accuracy, while converging in an ef cient manner, compared with optimal solutions achieved by the state-of-the-art modeling languages and interior-point solvers. This is particularly for cases when the number of antennas at the base station increases to large values. This makes the solution method attractive for practical implementation in heterogeneous networks with large-scale antenna arrays at the macrocell base station.en© 2018 IEEE. This is an Open access paper.MacrocellBeamformingMatrix stuf ngADMM algorithmMultiple-input multiple-output (MIMO)Heterogeneous network (HetNet)Signal to interference plus noise ratioReduced power consumptionMethod of multipliersMassive MIMOMacro cellsImperfect channel state informationModeling languagesComputer simulation languagesCommunication channels (information theory)Channel state informationBase stationsAlternative direction method of multipliers (ADMM)Fast converging robust beamforming for massive MIMO in heterogeneous networksArticle