Joint Transmit Beamforming and Receive Power Splitting for MISO SWIPT Systems (1304.0062v3)

Abstract: This paper studies a multi-user multiple-input single-output (MISO) downlink system for simultaneous wireless information and power transfer (SWIPT), in which a set of single-antenna mobile stations (MSs) receive information and energy simultaneously via power splitting (PS) from the signal sent by a multi-antenna base station (BS). We aim to minimize the total transmission power at BS by jointly designing transmit beamforming vectors and receive PS ratios for all MSs under their given signal-to-interference-plus-noise ratio (SINR) constraints for information decoding and harvested power constraints for energy harvesting. First, we derive the sufficient and necessary condition for the feasibility of our formulated problem. Next, we solve this non-convex problem by applying the technique of semidefinite relaxation (SDR). We prove that SDR is indeed tight for our problem and thus achieves its global optimum. Finally, we propose two suboptimal solutions of lower complexity than the optimal solution based on the principle of separating the optimization of transmit beamforming and receive PS, where the zero-forcing (ZF) and the SINR-optimal based transmit beamforming schemes are applied, respectively.

• The paper introduces a joint optimization framework that minimizes transmit power while ensuring SINR and energy harvesting constraints in MISO SWIPT systems.
• It employs semidefinite relaxation to convert the non-convex beamforming and power splitting problem into a tractable form with proven global optimality.
• Suboptimal algorithms based on zero-forcing and SINR-optimal beamforming achieve near-optimal performance with reduced computational complexity.

Joint Transmit Beamforming and Receive Power Splitting for MISO SWIPT Systems

The paper "Joint Transmit Beamforming and Receive Power Splitting for MISO SWIPT Systems" by Qingjiang Shi et al. investigates the complex interplay between simultaneous wireless information and power transfer (SWIPT) in multi-user multiple-input single-output (MISO) downlink systems. The focus is on optimizing the transmit beamforming vectors and receive power splitting (PS) ratios to minimize total transmission power while adhering to specific SINR and power constraints at single-antenna mobile stations (MSs).

Core Concepts and Contributions

1. System Configuration and Challenges: The research targets a system where a multi-antenna base station (BS) serves multiple single-antenna MSs. The challenge lies in simultaneously optimizing information transmission (in terms of SINR) and energy harvesting, given the coupling in the receiver's processing ability.
2. Optimization Formulation: The paper frames the optimization problem as non-convex due to coupled beamforming vectors and PS ratios. A primary aim is to ensure feasibility under SINR and energy constraints, while minimizing BS power output.
3. Solution via Semidefinite Relaxation (SDR): By employing SDR, the authors are able to effectively transform and solve the problem, proving the tightness of SDR for this context. This approach ensures achieving the global optimum for the joint design problem by relaxing the rank constraints.
4. Suboptimal Algorithms: Despite the effectiveness of SDR, the computational complexity drives the need for suboptimal solutions. The authors propose two algorithms:
   • Zero-Forcing (ZF) Beamforming: Applicable when the number of transmit antennas exceeds the number of users. ZF effectively nullifies interference, albeit with a potential loss in performance at higher complexities.
   • SINR-Optimal Beamforming: This algorithm provides flexibility in configurations with any antenna-user ratio, adjusting beamforming to optimize SINR foremost and then PS ratios.

Key Findings

• Feasibility Conditions: A pivotal result is the elucidation that feasibility only depends on the SINR constraints, independent of energy harvesting requirements.
• SDR Effectiveness: The application of SDR justified optimality, where the derived rank-one solutions precisely match the original problem specifications.
• Algorithmic Performance: The suboptimal algorithms demonstrate near-optimal performance at reduced computational cost, especially as SINR targets increase.

Implications and Future Directions

This work advances practical system configurations for SWIPT by refining the trade-off between power and data transmission using advanced beamforming techniques. The findings hold significant implications for efficient resource allocation in modern communication systems, particularly for Internet of Things (IoT) applications and emerging cellular networks.

Future research might explore:

• The impact of channel state information (CSI) imperfections on the optimization framework.
• Extensions to more complex receiver architectures accommodating heterogeneous SINR and power requirements.
• Cross-layer optimization strategies incorporating MAC layer considerations and network-wide resource constraints.

The paper provides a methodologically robust approach to optimizing power and information trade-offs in SWIPT systems, with promising directions for further development in artificial intelligence and machine learning applications in dynamic network environments.