Beam-Based Solutions
for Cost-Efficient Massive MIMO Systems

Bridging the Gap of Massive MIMO

Massive MIMO technologies play a pivotal role in future wireless systems, not only for capacity enhancement but also for reliability improvement. However, the real-world implementation of massive MIMO faces with severe challenges, including prohibitive hardware cost and power consumption, enormous computational and pilot overhead, etc. In view of this, the key problem we solve is: how to achieve cost-efficient massive MIMO without performance degradation?

A Systematic Beam-Based Solution

1. Optimal Beam-Domain Signal Compression by Low-Resolution Phase Shifters[1]

Cost1

A beam combination module is proposed, which consists of a small number of low-resolution digital phase shifters after the beamspace transformation module to reduce the number of RF chains beyond beamspace signal sparsity. The optimum discrete beam combination weights for the uplink are obtained based on the branch-and-bound (BB) approach whose sub-problem is solved in a closed-form. Link-level simulations show that the proposed scheme can reduce the number of RF chains by up to 25% with a one-bit digital phase-shifter-network.

2. Joint Beam-User Scheduling for Throughput Maximization[2]

Cost2
We formulate the joint user scheduling and beam selection problem based on the Lyapunov-drift optimization framework and obtain the optimal scheduling policy in a closed-form. The scheduling scheme is based only upon statistical channel state information. To address the weighted sum rate maximization problem in the Lyapunov optimization, an algorithm based on block coordinated update is proposed and proved to converge to the optimum. Simulation results show that joint scheduling improves throughput compared with state-of-the-arts.

3. 3. Scalable CSI Acquisition for FDD Systems[3,4]

Cost3
We propose a superposition signaling of pilots and data scheme (SPD) for beam-based frequency-division-duplex (FDD) massive MIMO systems, which allows pilots and data to be transmitted simultaneously in the downlink. The proposed SPD scheme leverages spatial channel correlations to reduce the dimensionality loss, and more importantly, addresses the problem of uneven user channel correlations by superposition signaling of pilots and information bearing data symbols.


[1] Z. Jiang, S. Zhou, and Z. Niu, “Optimal discrete spatial compression for beamspace massive MIMO signals”, IEEE Trans. Signal Process., 66(9): 2480-2493, May 2018.
[2] Z. Jiang, S. Chen, S. Zhou, and Z. Niu, “Joint user scheduling and beam selection optimization for beam-based massive MIMO Downlinks,” IEEE Trans. Wireless Commun., 2018 (accepted with early access).
[3] Z. Jiang, A. Molisch, G. Caire, and Z. Niu, “Achievable rates of FDD massive MIMO systems with spatial channel correlation,” IEEE Trans. Wireless Commun., 14(5): 2868-2882, May 2015.
[4] Z. Jiang, S. Zhou, R. Deng, Z. Niu, and S. Cao, “Pilot-data superposition for beam-based FDD massive MIMO downlinks,” IEEE Commun. Lett., 21(6): 1357–1360, June 2017.