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Mitigating Mixed-field Interference in Near-field and Far-field Communications: An Antenna Selection Approach

Tianyu Liu, Changsheng You, Chao Zhou, Mingjiang Wu, Ming-Min Zhao, Zhaocheng Wang

TL;DR

An antenna selection-based transmission framework to effectively suppress mixed-field interference without mechanically altering antenna structures is proposed and analytically shows that the strong mixed-field interference can be substantially mitigated by deactivating only a small portion of antennas, yet without compromising array gains too much.

Abstract

In mixed near-field and far-field systems, the nonorthogonality between near-field and far-field channels may cause severe inter-user interference and hence degrade rate performance, when the analog beamforming is designed based on the low-complexity full-array maximum ratio transmission (MRT). To tackle this issue, we propose in this paper an antenna selection-based transmission framework to effectively suppress mixed-field interference without mechanically altering antenna structures. To this end, an optimization problem is formulated to maximize the sum-rate of mixed-field systems, by jointly designing antenna selection and power allocation under the MRT-based analog beamforming. As the problem is non-convex and generally difficult to solve optimally, we first consider a typical two-user scenario to obtain useful insights. Interestingly, we analytically show that the strong mixed-field interference can be substantially mitigated by deactivating only a small portion of antennas, yet without compromising array gains too much. Moreover, an inherent tradeoff is revealed in antenna selection between interference suppression and array-gain enhancement, based on which a suboptimal number of deactivated antennas for achieving the maximum sum-rate is obtained. Next, for the general multi-user case, we develop an efficient penalty dual decomposition (PDD)-based two-layer framework to obtain its high quality solution by using the block coordinate descent (BCD) and successive convex approximation (SCA) techniques. To further reduce the computational complexity, a low-complexity antenna deactivation strategy is proposed capitalizing on an interference suppression criterion. Last, numerical results demonstrate that the proposed scheme achieves a favorable trade-off between interference suppression and array gain loss, hence achieving significant performance gains over various baseline schemes.

Mitigating Mixed-field Interference in Near-field and Far-field Communications: An Antenna Selection Approach

TL;DR

An antenna selection-based transmission framework to effectively suppress mixed-field interference without mechanically altering antenna structures is proposed and analytically shows that the strong mixed-field interference can be substantially mitigated by deactivating only a small portion of antennas, yet without compromising array gains too much.

Abstract

In mixed near-field and far-field systems, the nonorthogonality between near-field and far-field channels may cause severe inter-user interference and hence degrade rate performance, when the analog beamforming is designed based on the low-complexity full-array maximum ratio transmission (MRT). To tackle this issue, we propose in this paper an antenna selection-based transmission framework to effectively suppress mixed-field interference without mechanically altering antenna structures. To this end, an optimization problem is formulated to maximize the sum-rate of mixed-field systems, by jointly designing antenna selection and power allocation under the MRT-based analog beamforming. As the problem is non-convex and generally difficult to solve optimally, we first consider a typical two-user scenario to obtain useful insights. Interestingly, we analytically show that the strong mixed-field interference can be substantially mitigated by deactivating only a small portion of antennas, yet without compromising array gains too much. Moreover, an inherent tradeoff is revealed in antenna selection between interference suppression and array-gain enhancement, based on which a suboptimal number of deactivated antennas for achieving the maximum sum-rate is obtained. Next, for the general multi-user case, we develop an efficient penalty dual decomposition (PDD)-based two-layer framework to obtain its high quality solution by using the block coordinate descent (BCD) and successive convex approximation (SCA) techniques. To further reduce the computational complexity, a low-complexity antenna deactivation strategy is proposed capitalizing on an interference suppression criterion. Last, numerical results demonstrate that the proposed scheme achieves a favorable trade-off between interference suppression and array gain loss, hence achieving significant performance gains over various baseline schemes.
Paper Structure (29 sections, 5 theorems, 54 equations, 12 figures, 1 table)

This paper contains 29 sections, 5 theorems, 54 equations, 12 figures, 1 table.

Table of Contents

  1. Introduction
  2. Motivations and Contributions
  3. Organization and Notations
  4. System Model
  5. Considered Hardware Architecture and Problem Formulation
  6. Existing Hybrid Beamforming Architecture
  7. Considered Hardware Architecture
  8. Problem Formulation
  9. Two-user Case: Interference Analysis and Antenna-selection Design
  10. Inner Problem: Antenna-selection Design for Interference Suppression
  11. Model selection
  12. Model evaluation
  13. Outer Problem: Optimization for Deactivated Antennas
  14. General Case: Proposed Algorithm for Solving Problem (P1)
  15. Proposed PDD-based Algorithm
  16. ...and 14 more sections

Key Result

Lemma 1

Supposing that $\ell$ antennas have been deactivated and $\ell \ll N$, the reduction of interference coupling factor during the $(\ell+1)$-th deactivation can be approximated as where $\theta_{\Delta}^{(\ell+1)} = \angle s^{(\ell)} - \angle c_{ n^{(\ell+1)}}$.

Figures (12)

  • Figure 1: Different beamforming architectures for the considered mixed-field communication system.
  • Figure 2: Mixed-field channel correlation and achievable sum-rate vs. angular difference in the two-user case.
  • Figure 3: Interference coupling factor vs. number of deactivated antennas.
  • Figure 4: Illustration of the performance obtained by the proposed antenna deactivation scheme with optimized power allocation.
  • Figure 5: Total interference during greedy deactivation in a five-user system: 2 near-field users at $(-0.30, 5.82\,\text{m})$ and $(0.17, 6.21\,\text{m})$, and 3 far-field users at $(-0.22, 150\,\text{m})$, $(0.09, 175\,\text{m})$, and $(0.25, 200\,\text{m})$.
  • ...and 7 more figures

Theorems & Definitions (8)

  • Definition 1
  • Lemma 1
  • proof
  • Lemma 2
  • proof
  • Lemma 3
  • Lemma 4
  • Lemma 5