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The joint design of spatial channel assignment and power allocation in multiple input multiple output (MIMO) systems capable of simultaneous wireless information and power transfer is studied. Assuming availability of channel state information at both communications ends, we maximize the harvested energy at the multi-antenna receiver, while satisfying a minimum information rate requirement for the MIMO link. We first derive the globally optimal eigenchannel assignment and power allocation design, and then present a practically motivated tight closed-form approximation for the optimal design parameters. Selected numerical results verify the validity of the optimal solution and provide useful insights on the proposed designs as well as the Pareto-optimal rate-energy tradeoff.

The joint design of spatial channel assignment and power allocation in multiple input multiple output (MIMO) systems capable of simultaneous wireless information and power transfer is studied. Assuming availability of channel state information at both communications ends, we maximize the harvested energy at the multi-antenna receiver, while satisfying a minimum information rate requirement for the MIMO link. We first derive the globally optimal eigenchannel assignment and power allocation design, and then present a practically motivated tight closed-form approximation for the optimal design parameters. Selected numerical results verify the validity of the optimal solution and provide useful insights on the proposed designs as well as the Pareto-optimal rate-energy tradeoff.

Enabling technologies for energy sustainable Internet of Things (IoT) are of paramount importance since the proliferation of high data rate demands of low power network devices. In this paper, we consider a multiple input single output (MISO) multicasting system comprising of a multiantenna transmitter (TX) simultaneously transferring information and power to data hungry IoT nodes. Each IoT device is assumed to be equipped with power splitting (PS) hardware that enables energy harvesting (EH) and imposes an individual quality of service (QoS) constraint to the downlink communication. We study the joint design of TX precoding and IoT PS ratios for the considered MISO simultaneous wireless information and power transfer multicasting system with the objective of maximizing the minimum harvested energy among IoT, while satisfying their individual QoS requirements. In our novel EH fairness maximization formulation, we adopt a generic EH model capturing practical rectification operation, and resulting in a nonconvex optimization problem. For this problem, we first present an equivalent semi-definite relaxation formulation and then prove it possesses unique global optimality. We also derive tight upper and lower bounds on the globally optimal solution that are exploited in obtaining low complexity algorithmic implementations for the targeted joint design. Analytical expressions for the optimal TX beamforming directions, power allocation, and PS ratios are also presented. Representative numerical results including comparisons with benchmark designs corroborate the utility of proposed framework and provide useful insights on the interplay of key system parameters., Funding Agencies|DST [SB/S3/EECE/0248/2014]

Enabling technologies for energy sustainable Internet of Things (IoT) are of paramount importance since the proliferation of high data rate demands of low power network devices. In this paper, we consider a multiple input single output (MISO) multicasting system comprising of a multiantenna transmitter (TX) simultaneously transferring information and power to data hungry IoT nodes. Each IoT device is assumed to be equipped with power splitting (PS) hardware that enables energy harvesting (EH) and imposes an individual quality of service (QoS) constraint to the downlink communication. We study the joint design of TX precoding and IoT PS ratios for the considered MISO simultaneous wireless information and power transfer multicasting system with the objective of maximizing the minimum harvested energy among IoT, while satisfying their individual QoS requirements. In our novel EH fairness maximization formulation, we adopt a generic EH model capturing practical rectification operation, and resulting in a nonconvex optimization problem. For this problem, we first present an equivalent semi-definite relaxation formulation and then prove it possesses unique global optimality. We also derive tight upper and lower bounds on the globally optimal solution that are exploited in obtaining low complexity algorithmic implementations for the targeted joint design. Analytical expressions for the optimal TX beamforming directions, power allocation, and PS ratios are also presented. Representative numerical results including comparisons with benchmark designs corroborate the utility of proposed framework and provide useful insights on the interplay of key system parameters., Funding Agencies|DST [SB/S3/EECE/0248/2014]

The joint design of spatial channel assignment and power allocation in multiple input multiple output (MIMO) systems capable of simultaneous wireless information and power transfer is studied. Assuming availability of channel state information at both communications ends, we maximize the harvested energy at the multi-antenna receiver, while satisfying a minimum information rate requirement for the MIMO link. We first derive the globally optimal eigenchannel assignment and power allocation design, and then present a practically motivated tight closed-form approximation for the optimal design parameters. Selected numerical results verify the validity of the optimal solution and provide useful insights on the proposed designs as well as the Pareto-optimal rate-energy tradeoff.

Enabling technologies for energy sustainable Internet of Things (IoT) are of paramount importance since the proliferation of high data rate demands of low power network devices. In this paper, we consider a multiple input single output (MISO) multicasting system comprising of a multiantenna transmitter (TX) simultaneously transferring information and power to data hungry IoT nodes. Each IoT device is assumed to be equipped with power splitting (PS) hardware that enables energy harvesting (EH) and imposes an individual quality of service (QoS) constraint to the downlink communication. We study the joint design of TX precoding and IoT PS ratios for the considered MISO simultaneous wireless information and power transfer multicasting system with the objective of maximizing the minimum harvested energy among IoT, while satisfying their individual QoS requirements. In our novel EH fairness maximization formulation, we adopt a generic EH model capturing practical rectification operation, and resulting in a nonconvex optimization problem. For this problem, we first present an equivalent semi-definite relaxation formulation and then prove it possesses unique global optimality. We also derive tight upper and lower bounds on the globally optimal solution that are exploited in obtaining low complexity algorithmic implementations for the targeted joint design. Analytical expressions for the optimal TX beamforming directions, power allocation, and PS ratios are also presented. Representative numerical results including comparisons with benchmark designs corroborate the utility of proposed framework and provide useful insights on the interplay of key system parameters., Funding Agencies|DST [SB/S3/EECE/0248/2014]

The joint design of spatial channel assignment and power allocation in multiple input multiple output (MIMO) systems capable of simultaneous wireless information and power transfer is studied. Assuming availability of channel state information at both communications ends, we maximize the harvested energy at the multi-antenna receiver, while satisfying a minimum information rate requirement for the MIMO link. We first derive the globally optimal eigenchannel assignment and power allocation design, and then present a practically motivated tight closed-form approximation for the optimal design parameters. Selected numerical results verify the validity of the optimal solution and provide useful insights on the proposed designs as well as the Pareto-optimal rate-energy tradeoff.

Enabling technologies for energy sustainable Internet of Things (IoT) are of paramount importance since the proliferation of high data rate demands of low power network devices. In this paper, we consider a multiple input single output (MISO) multicasting system comprising of a multiantenna transmitter (TX) simultaneously transferring information and power to data hungry IoT nodes. Each IoT device is assumed to be equipped with power splitting (PS) hardware that enables energy harvesting (EH) and imposes an individual quality of service (QoS) constraint to the downlink communication. We study the joint design of TX precoding and IoT PS ratios for the considered MISO simultaneous wireless information and power transfer multicasting system with the objective of maximizing the minimum harvested energy among IoT, while satisfying their individual QoS requirements. In our novel EH fairness maximization formulation, we adopt a generic EH model capturing practical rectification operation, and resulting in a nonconvex optimization problem. For this problem, we first present an equivalent semi-definite relaxation formulation and then prove it possesses unique global optimality. We also derive tight upper and lower bounds on the globally optimal solution that are exploited in obtaining low complexity algorithmic implementations for the targeted joint design. Analytical expressions for the optimal TX beamforming directions, power allocation, and PS ratios are also presented. Representative numerical results including comparisons with benchmark designs corroborate the utility of proposed framework and provide useful insights on the interplay of key system parameters., Funding Agencies|DST [SB/S3/EECE/0248/2014]

The joint design of spatial channel assignment and power allocation in multiple input multiple output (MIMO) systems capable of simultaneous wireless information and power transfer is studied. Assuming availability of channel state information at both communications ends, we maximize the harvested energy at the multi-antenna receiver, while satisfying a minimum information rate requirement for the MIMO link. We first derive the globally optimal eigenchannel assignment and power allocation design, and then present a practically motivated tight closed-form approximation for the optimal design parameters. Selected numerical results verify the validity of the optimal solution and provide useful insights on the proposed designs as well as the Pareto-optimal rate-energy tradeoff.

Enabling technologies for energy sustainable Internet of Things (IoT) are of paramount importance since the proliferation of high data rate demands of low power network devices. In this paper, we consider a multiple input single output (MISO) multicasting system comprising of a multiantenna transmitter (TX) simultaneously transferring information and power to data hungry IoT nodes. Each IoT device is assumed to be equipped with power splitting (PS) hardware that enables energy harvesting (EH) and imposes an individual quality of service (QoS) constraint to the downlink communication. We study the joint design of TX precoding and IoT PS ratios for the considered MISO simultaneous wireless information and power transfer multicasting system with the objective of maximizing the minimum harvested energy among IoT, while satisfying their individual QoS requirements. In our novel EH fairness maximization formulation, we adopt a generic EH model capturing practical rectification operation, and resulting in a nonconvex optimization problem. For this problem, we first present an equivalent semi-definite relaxation formulation and then prove it possesses unique global optimality. We also derive tight upper and lower bounds on the globally optimal solution that are exploited in obtaining low complexity algorithmic implementations for the targeted joint design. Analytical expressions for the optimal TX beamforming directions, power allocation, and PS ratios are also presented. Representative numerical results including comparisons with benchmark designs corroborate the utility of proposed framework and provide useful insights on the interplay of key system parameters., Funding Agencies|DST [SB/S3/EECE/0248/2014]