2D Unitary ESPRIT Based Super-Resolution Channel Estimation for Millimeter-Wave Massive MIMO with Hybrid Precoding

摘要

Millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) withhybrid precoding is a promising technique for the future 5G wirelesscommunications. Due to a large number of antennas but a much smaller number ofradio frequency (RF) chains, estimating the high-dimensional mmWave massiveMIMO channel will bring the large pilot overhead. To overcome this challenge,this paper proposes a super-resolution channel estimation scheme based ontwo-dimensional (2D) u- nitary ESPRIT algorithm. By exploiting the angularsparsity of mmWave channels, the continuously distributed angle ofarrivals/departures (AoAs/AoDs) can be jointly estimated with high accuracy.Specifically, by designing the uplink training signals at both base station(BS) and mobile station (MS), we first use low pilot overhead to estimate alow-dimensional effective channel, which has the same shift-invariance of arrayresponse as the high-dimensional mmWave MIMO channel to be estimated. From thelow-dimensional effective channel, the super- resolution estimates of AoAs andAoDs can be jointly obtained by exploiting the 2D unitary ESPRIT channelestimation algorithm. Furthermore, the associated path gains can be acquiredbased on the least squares (LS) criterion. Finally, we can reconstruct thehigh-dimensional mmWave MIMO channel according to the obtained AoAs, AoDs, andpath gains. Simulation results have confirmed that the proposed scheme issuperior to conventional schemes with a much lower pilot overhead.