In this study, downlink channel estimation of three-dimensional massive multiple-input multiple-output (3D-MIMO) system operating in the frequency division duplexing (FDD) mode is considered. Inspired by the channel sparsity property, this study proposes a compressive sensing algorithm to exploit the channel sparsity structure in the angle-time domain. The proposed algorithm, named AMP-ADM, combines the multiple approximate message passing (M-AMP) algorithm with the alternative direction of multiplier (ADM) technique to efficiently exploit the sparsity structure of the 3D massive MIMO channel. First, the proposed AMP-ADM is implemented in the case of the conventional estimation for the FDD protocol where the channel is estimated individually at each user equipment. Then, building on this algorithm, a low complexity feedback AMPADM- T scheme at the transmitting base station (BS) side is proposed. In the proposed feedback AMP-ADM-T technique the users' channels are jointly estimated at the BS to fully exploit the common sparsity basis. Complexity and convergence analyses are provided for both the AMP-ADM and feedback AMP-ADM-T algorithms. Simulation results prove the improved performance of the proposed feedback AMP-ADM-T algorithm compared to different state-of-the-art joint channel estimation techniques.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Electrical and Electronic Engineering