The sum rate maximization beamforming problem for a multi-cell multi-user multiple-input single-output interference channel(MISO-IC)system is considered.Conventionally,the centralized and distributed beamforming solut...The sum rate maximization beamforming problem for a multi-cell multi-user multiple-input single-output interference channel(MISO-IC)system is considered.Conventionally,the centralized and distributed beamforming solutions to the MISO-IC system have high computational complexity and bear a heavy burden of channel state information exchange between base stations(BSs),which becomes even much worse in a large-scale antenna system.To address this,we propose a distributed deep reinforcement learning(DRL)based approach with lim⁃ited information exchange.Specifically,the original beamforming problem is decomposed of the problems of beam direction design and power allocation and the costs of information exchange between BSs are significantly reduced.In particular,each BS is provided with an inde⁃pendent deep deterministic policy gradient network that can learn to choose the beam direction scheme and simultaneously allocate power to users.Simulation results illustrate that the proposed DRL-based approach has comparable sum rate performance with much less information exchange over the conventional distributed beamforming solutions.展开更多
Large-scale array aided beamforming improves the spectral efficiency(SE) as a benefit of high angular resolution.When dual-beam downlink beamforming is applied to the train moving towards cell edge,the inter-beam ambi...Large-scale array aided beamforming improves the spectral efficiency(SE) as a benefit of high angular resolution.When dual-beam downlink beamforming is applied to the train moving towards cell edge,the inter-beam ambiguity(IBA) increases as the directional difference between beams becomes smaller.An adaptive antenna activation based beamforming scheme was proposed to mitigate IBA.In the district near the base station(BS),all antenna elements(AEs) were activated to generate two beams.As the distance from the train to the BS increased,only the minimum number of AEs satisfying the resolution criterion would be activated.At the cell edge,one beam was switched off due to intolerable IBA.The proposed scheme can achieve SE gain to the non-adaptive scheme and show more robustness against the direction-of-arrival(DOA) estimation error.展开更多
基金supported by the joint research project with ZTE Corporation under Grant No.HC-CN-2020120002.
文摘The sum rate maximization beamforming problem for a multi-cell multi-user multiple-input single-output interference channel(MISO-IC)system is considered.Conventionally,the centralized and distributed beamforming solutions to the MISO-IC system have high computational complexity and bear a heavy burden of channel state information exchange between base stations(BSs),which becomes even much worse in a large-scale antenna system.To address this,we propose a distributed deep reinforcement learning(DRL)based approach with lim⁃ited information exchange.Specifically,the original beamforming problem is decomposed of the problems of beam direction design and power allocation and the costs of information exchange between BSs are significantly reduced.In particular,each BS is provided with an inde⁃pendent deep deterministic policy gradient network that can learn to choose the beam direction scheme and simultaneously allocate power to users.Simulation results illustrate that the proposed DRL-based approach has comparable sum rate performance with much less information exchange over the conventional distributed beamforming solutions.
基金supported partially by the 973 Program under the Grant 2012CB316100
文摘Large-scale array aided beamforming improves the spectral efficiency(SE) as a benefit of high angular resolution.When dual-beam downlink beamforming is applied to the train moving towards cell edge,the inter-beam ambiguity(IBA) increases as the directional difference between beams becomes smaller.An adaptive antenna activation based beamforming scheme was proposed to mitigate IBA.In the district near the base station(BS),all antenna elements(AEs) were activated to generate two beams.As the distance from the train to the BS increased,only the minimum number of AEs satisfying the resolution criterion would be activated.At the cell edge,one beam was switched off due to intolerable IBA.The proposed scheme can achieve SE gain to the non-adaptive scheme and show more robustness against the direction-of-arrival(DOA) estimation error.
