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Energy-Efficient Hybrid Beamforming with Dynamic On-off Control for Integrated Sensing, Communications, and Powering

Zeyu Hao, Yuan Fang, Xianghao Yu, Jie Xu, Ling Qiu, Lexi Xu, Shuguang Cui

TL;DR

The proposed design achieves an improved energy efficiency for ISCAP than other benchmark schemes without joint design of hybrid beamforming and dynamic on-off control, which validates the benefit of dynamic on-off control in energy reduction, especially when the multi-functional performance requirements become less stringent.

Abstract

This paper investigates the energy-efficient hybrid beamforming design for a multi-functional integrated sensing, communications, and powering (ISCAP) system. In this system, a base station (BS) with a hybrid analog-digital (HAD) architecture sends unified wireless signals to communicate with multiple information receivers (IRs), sense multiple point targets, and wirelessly charge multiple energy receivers (ERs) at the same time. To facilitate the energy-efficient design, we present a novel HAD architecture for the BS transmitter, which allows dynamic on-off control of its radio frequency (RF) chains and analog phase shifters (PSs) through a switch network. We also consider a practical and comprehensive power consumption model for the BS, by taking into account the power-dependent non-linear power amplifier (PA) efficiency, and the on-off non-transmission power consumption model of RF chains and PSs. We jointly design the hybrid beamforming and dynamic on-off control at the BS, aiming to minimize its total power consumption, while guaranteeing the performance requirements on communication rates, sensing Cramér-Rao bound (CRB), and harvested power levels. The formulation also takes into consideration the per-antenna transmit power constraint and the constant modulus constraints for the analog beamformer at the BS. The resulting optimization problem for ISCAP is highly non-convex. Please refer to the paper for a complete abstract.

Energy-Efficient Hybrid Beamforming with Dynamic On-off Control for Integrated Sensing, Communications, and Powering

TL;DR

The proposed design achieves an improved energy efficiency for ISCAP than other benchmark schemes without joint design of hybrid beamforming and dynamic on-off control, which validates the benefit of dynamic on-off control in energy reduction, especially when the multi-functional performance requirements become less stringent.

Abstract

This paper investigates the energy-efficient hybrid beamforming design for a multi-functional integrated sensing, communications, and powering (ISCAP) system. In this system, a base station (BS) with a hybrid analog-digital (HAD) architecture sends unified wireless signals to communicate with multiple information receivers (IRs), sense multiple point targets, and wirelessly charge multiple energy receivers (ERs) at the same time. To facilitate the energy-efficient design, we present a novel HAD architecture for the BS transmitter, which allows dynamic on-off control of its radio frequency (RF) chains and analog phase shifters (PSs) through a switch network. We also consider a practical and comprehensive power consumption model for the BS, by taking into account the power-dependent non-linear power amplifier (PA) efficiency, and the on-off non-transmission power consumption model of RF chains and PSs. We jointly design the hybrid beamforming and dynamic on-off control at the BS, aiming to minimize its total power consumption, while guaranteeing the performance requirements on communication rates, sensing Cramér-Rao bound (CRB), and harvested power levels. The formulation also takes into consideration the per-antenna transmit power constraint and the constant modulus constraints for the analog beamformer at the BS. The resulting optimization problem for ISCAP is highly non-convex. Please refer to the paper for a complete abstract.
Paper Structure (14 sections, 1 theorem, 66 equations, 6 figures)

This paper contains 14 sections, 1 theorem, 66 equations, 6 figures.

Table of Contents

  1. Introduction
  2. System Model and Problem Formulation
  3. Communication Model
  4. Sensing Model
  5. WPT Model
  6. Power Consumption Model
  7. Problem Formulation
  8. Proposed Solution to Problem (P1) Based on Alternating Optimization
  9. Optimization of Digital Beamformer and Sensing Covariance in (P2) with Given Analog Beamformer
  10. Optimization of Analog Beamformer in (P2) with Given Digital Beamformer and Sensing Covariance
  11. On-off Control based on Beamforming Weights
  12. Numerical Results
  13. Conclusion
  14. Proof of Proposition 1

Key Result

Proposition 1

The optimal solution to problems (SDR3) and (P3) is given by

Figures (6)

  • Figure 1: The ISCAP system with an HAD multi-functional BS.
  • Figure 2: The total power consumption w.r.t SINR requirements with $\Gamma_{\textrm{S}}=0.1$ and $\Gamma_{j}^{\textrm{DC}}=-2\,\textrm{dBm},\forall j\in\mathcal{K}_{\textrm{ER}}$.
  • Figure 3: The total power consumption w.r.t CRB threshold with $\Gamma_{k}^{\textrm{IR}}=6\,\textrm{dB},\forall k\in\mathcal{K}_{\textrm{IR}},$ and $\Gamma_{j}^{\textrm{DC}}=-2\,\textrm{dBm},\forall j\in\mathcal{K}_{\textrm{ER}}$.
  • Figure 4: The total power consumption w.r.t EH constraint with $\Gamma_{k}^{\textrm{IR}}=6\,\textrm{dB},\forall k\in\mathcal{K}_{\textrm{IR}},$ and $\Gamma_{\textrm{S}}=0.1$.
  • Figure 5: The optimized transmit power allocation across various antennas, with $\Gamma_{\textrm{S}}=0.08$ and $\Gamma_{j}^{\textrm{DC}}=0\,\textrm{dBm},\forall j\in\mathcal{K}_{\textrm{ER}}$.
  • ...and 1 more figures

Theorems & Definitions (1)

  • Proposition 1