Joint Beamforming Design and Bit Allocation in Massive MIMO with Resolution-Adaptive ADCs
Mengyuan Ma, Nhan Thanh Nguyen, Italo Atzeni, and Markku Juntti

TL;DR
This paper proposes a joint beamforming and bit allocation strategy for massive MIMO systems with resolution-adaptive ADCs, improving spectral and energy efficiency while reducing ADC bit usage.
Contribution
It introduces a closed-form approximation for quantization distortion covariance and develops an efficient algorithm for joint optimization of beamforming and ADC resolution.
Findings
Achieves 6% improvement in SE and EE with fewer ADC bits.
Demonstrates benefits of low-resolution ADCs for multiple data streams.
Provides a low-complexity heuristic for mixed-integer optimization.
Abstract
Low-resolution analog-to-digital converters (ADCs) have emerged as a promising technology for reducing power consumption and complexity in massive multiple-input multiple-output (MIMO) systems while maintaining satisfactory spectral and energy efficiencies (SE/EE). In this work, we first identify the essential properties of optimal quantization and leverage them to derive a closed-form approximation of the covariance matrix of the quantization distortion. The theoretical finding facilitates the system SE analysis in the presence of low-resolution ADCs. We then focus on the joint optimization of the transmit-receive beamforming and bit allocation to maximize the SE under constraints on the transmit power and the total number of active ADC bits. To solve the resulting mixed-integer problem, we first develop an efficient beamforming design for fixed ADC resolutions. Then, we propose a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced MIMO Systems Optimization · Advanced Wireless Communication Techniques · Antenna Design and Optimization
MethodsFocus
