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Simultaneous Information and Power Transfer for Broadband Wireless Systems

Kaibin Huang, Erik G. Larsson

arXiv:1211.6868v3cs.IT

TL;DR

The paper addresses how to combine microwave power transfer with wireless communication for battery-constrained devices. It proposes broadband OFDM/beamforming SWIPT with reconfigurable mobile hardware and circuit-aware power control, yielding algorithms that improve throughput and MPT efficiency across multiple configurations. Simulations show that the preferred approach depends on propagation loss and circuit power.

  • Problem

    Wireless sensors and mobile devices face finite batteries, while practical SWIPT must account for receiver circuit power and limitations of prior broadband implementations.

  • Method

    The paper combines OFDM sub-channels, multiantenna beamforming and combining, a reconfigurable mobile architecture, and power-control algorithms for multiple information-transfer and coding-rate configurations.

  • Results

    Simulations show that power control enhances SWIPT efficiency; SWIPT is preferred under less severe propagation loss or low circuit power, whereas TD-IPT can provide higher spectral efficiency otherwise.

  • Takeaways & Limitations

    Circuit-power-aware frequency-diverse power control provides a practical way to jointly support information transfer and wireless powering in broadband systems.

  • Takeaways & Limitations

    The channel assignment is fixed, and jointly assigning channels with optimal power control may further increase SWIPT efficiency.

Abstract

from arXiv · show

Far-field microwave power transfer (MPT) will free wireless sensors and other mobile devices from the constraints imposed by finite battery capacities. Integrating MPT with wireless communications to support simultaneous information and power transfer (SIPT) allows the same spectrum to be used for dual purposes without compromising the quality of service. A novel approach is presented in this paper for realizing SIPT in a broadband system where orthogonal frequency division multiplexing and transmit beamforming are deployed to create a set of parallel sub-channels for SIPT, which simplifies resource allocation. Supported by a proposed reconfigurable mobile architecture, different system configurations are considered by combining single-user/multiuser systems, downlink/uplink information transfer, and variable/fixed coding rates. Optimizing the power control for these configurations results in a new class of multiuser power-control problems featuring circuit-power constraints, specifying that the transferred power must be sufficiently large to support the operation of the receiver circuitry. Solving these problems gives a set of power-control algorithms that exploit channel diversity in frequency for simultaneously enhancing the throughput and the MPT efficiency. For the system configurations with variable coding rates, the algorithms are variants of water-filling that account for the circuit-power constraints. The optimal algorithms for those configurations with fixed coding rates are shown to sequentially allocate mobiles their required power for decoding in the ascending order until the entire budgeted power is spent. The required power for a mobile is derived as simple functions of the minimum signal-to-noise ratio for correct decoding, the circuit power and sub-channel gains.

I. INTRODUCTION

The paper develops practical broadband SWIPT by combining OFDM/OFDMA, multiantenna transmission, reconfigurable mobile hardware, and power control under circuit-power constraints. It targets applications such as hard-to-access sensors while extending prior SWIPT tradeoff studies to practical frequency-selective systems.

  • Motivation: SWIPT uses the same electromagnetic wavefield to deliver harvested energy and decoded information, avoiding separate power and information transmission.The paper motivates integrated transceiver designs and interference control, especially for multiuser systems.
  • Motivation: SWIPT can power and communicate with sensors whose batteries are difficult or impossible to replace, including RFID tags and remote industrial sensors.These applications often require modest data rates but long battery lifetimes and very low failure rates.
  • Prior Related Work: Prior information-theoretic SWIPT studies characterized capacity–harvested-energy tradeoffs, while this work adds minimum received-power constraints for fixed circuit consumption.The circuit-power constraint requires sufficient received power for receiver operation and creates a new fundamental tradeoff.
  • Prior Related Work: OFDM partitions broadband channels into decoupled sub-channels, enabling multiple-device recharging and power-control algorithms that exploit frequency diversity.The paper presents a practical OFDM-based SWIPT framework and contrasts it with prior single-antenna designs whose isotropic radiation limits MPT efficiency.
  • System Model: The system combines single-user or multiuser operation, downlink or uplink information transfer, and variable or fixed coding rates across OFDM sub-channels.A multiantenna base station powers mobiles while transmitting or receiving one data stream per sub-channel; uplink operation uses full-duplex MPT/IT with separate antenna sub-arrays.
  • System Architecture: The proposed mobile architecture uses dual antennas, an information transceiver, and an energy harvester that supplies circuit and uplink transmission power.It can be reconfigured according to the information-transfer direction.

C. Broadband Signals

The broadband SWIPT design uses OFDM/OFDMA sub-channels and a reconfigurable dual-antenna mobile architecture to support downlink or uplink information transfer alongside MPT.

  • Downlink IT uses OFDM-modulated data over sub-channels, with no uplink transmission.
  • Uplink IT uses OFDMA data signals from mobiles while the base station transmits downlink power tones.
  • The mobile architecture combines a transceiver and energy harvester, and can be reconfigured for either IT direction.The harvester supplies DC power for circuitry and, in uplink mode, transmission.
  • For downlink IT, antenna outputs are coherently combined, then split between the receiver and energy harvester with relative powers β and (1 −β).
  • For uplink IT, separate antennas support full-duplex information and power transfer, with uplink receive SNR determined by allocated transmission power and channel gain.
  • Adding mobile antennas increases received power and uplink array gain, but spatial multiplexing is difficult because line-of-sight channels are practically rank-one.

A. Single-User Downlink IT with Variable Coding Rates

For single-user downlink IT with variable coding rates, throughput maximization includes a circuit-power feasibility constraint and is solved using an approximation with frequency-domain water-filling structure.

  • The throughput objective includes an indicator representing whether harvested power satisfies the circuit-power constraint.
  • The non-convex power-control problem is approximated by convex formulations whose policies are nearly optimal according to simulation.
  • SWIPT is feasible if the maximum harvested power, pmax = pt maxn hn, satisfies the receiver-power requirement.
  • Fixing β yields a convex subproblem solvable through duality, with an active index set selected to maintain nonnegative allocated powers.
  • The resulting allocation is frequency water-filling with a water level that decreases as sub-channel gain increases.Unlike classic water-filling, the water level is not constant because receiver turn-on power depends on channel gain.

B. Single-User Downlink IT with Fixed Coding Rates

For single-user downlink IT with fixed coding rates, maximizing throughput means maximizing the number of correctly decoded streams under circuit-power and minimum-SNR constraints.

  • Throughput is proportional to the number of successfully transmitted streams, while an indicator enforces the circuit-power constraint.
  • For k streams, the minimum-power solution uses the k sub-channels with the largest channel gains.
  • The splitting ratio for a given k is obtained from a quadratic equation, with the positive root providing the valid solution.
  • The optimal policy performs greedy channel inversion and determines k∗ by searching for the largest feasible stream count under the total-power constraint.
  • The final power vector assigns the required powers to the selected streams and zero power to the remaining sub-channels.

A. Single-User Uplink IT with Variable Coding Rates

For single-user uplink IT with variable coding rates, harvested power must first operate the circuitry; the remaining power is then allocated across uplink sub-channels by water-filling.

  • Uplink transmission is feasible only when harvested power exceeds the circuit power, PK n ≥pt.
  • After circuit operation, the remaining harvested power is allocated over sub-channels to maximize uplink throughput.
  • The problem decomposes into maximizing transferred downlink power and maximizing uplink throughput.
  • The base station maximizes MPT efficiency by transmitting the maximum power pt on the downlink tone with the maximum effective channel gain.
  • The water level η is selected so that the allocated uplink powers satisfy the available-power constraint.
  • The resulting uplink budget is (pt maxn g′ n −pc), distributed over sub-channels using water-filling.

B. Single-User Uplink IT with Fixed Coding Rates

This section establishes feasibility for single-user uplink information transfer and derives a fixed-rate policy that prioritizes streams with stronger uplink sub-channels.

  • Optimization: The uplink power-control problem allocates power to satisfy minimum-SNR decoding constraints under the available uplink-power budget.The formulation uses the receive-SNR expression and circuit-power constraints.
  • Power-control policy: The optimal policy sorts uplink sub-channel gains in descending order before selecting streams for transmission.A permutation matrix represents the reordered gains.
  • Power-control policy: Under fixed coding rates, the solution is summarized as a sequential policy for the feasible uplink streams.Proposition 3 states that the base-station policy matches the corresponding earlier policy and gives the uplink transmission allocation.
  • Feasibility: Uplink transmission is feasible if and only if the maximum harvested-power condition exceeds the circuit power.The feasibility condition is pt max_n g′_n > p_c.

2) Solution:

The multiuser downlink solution handles circuit-power constraints by optimizing the number of active streams and combining channel-aware allocation with water-filling.

  • Approximation: The non-convex multiuser problem is approximated by a convex formulation using objective-function bounds.The lower- and upper-bound approximations have the same structure and produce practically similar simulated solutions.
  • Power splitting: For mobiles meeting circuit-power constraints, additional harvested power can be redirected away from energy harvesting because it provides no throughput gain.The corresponding splitting choice sets the energy-harvester input to p_c.
  • Active-stream selection: Reducing the number of active streams lowers total circuit-power consumption and leaves more power available for information transfer.The optimal stream count is therefore not necessarily the maximum feasible count.
  • Water-filling: For a fixed number of streams, the solution combines traditional water-filling with constant allocations for inactive channels.The resulting throughput is then evaluated for each candidate stream count.
  • Active-stream selection: The optimal stream count has no closed-form solution and is obtained by a simple search over feasible values.The traditional choice L = ℓ_max may be suboptimal because using fewer streams can increase throughput.
  • Solution quality: The resulting power-control policy is close to optimal according to simulation.The lemma specifies the allocation from the optimized stream count and associated powers.

B. Multi-User Downlink IT with Fixed Coding Rates

This section derives the multiuser downlink fixed-rate solution, including a common splitting ratio and a channel-inversion power policy under circuit constraints.

  • Problem formulation: The multiuser throughput problem differs from the single-user case by including circuit-power constraints for multiple mobiles.These constraints are incorporated into the corresponding power-control formulation.
  • Power splitting: The splitting ratios are determined from two linear equations and have an optimal common value across all mobiles.The common ratio β* follows the same form as the single-user counterpart.
  • Power control: With the splitting ratio fixed, the optimal power-control policy performs greedy channel inversion.The policy is stated in Proposition 4 and is represented using a permutation of the channel ordering.
  • Stream selection: The solution activates the largest feasible number of streams satisfying the power and circuit-power constraints.The maximum stream count m_max is defined by those feasibility conditions.

VII. POWER CONTROL FOR MULTI-USER SWIPT SYSTEMS WITH UPLINK IT

The multiuser uplink design selects active mobiles for power transfer efficiency, then applies channel-aware uplink power control while accounting for circuit-power feasibility.

  • Problem formulation: The uplink problem incorporates combined downlink and uplink channel losses in its throughput and power-control formulation.The product g_n g′_n represents propagation loss in both directions, unlike downlink-only loss.
  • Mobile selection: For a fixed active-mobile count, selecting mobiles with the strongest downlink gains maximizes MPT efficiency.All other mobiles receive zero power in this subproblem.
  • Mobile selection: This downlink-based selection is not always globally optimal because a mobile with weaker downlink but stronger uplink gain may improve throughput.The trade-off arises when maximizing uplink sum throughput after satisfying circuit-power constraints.
  • Uplink allocation: Given the selected mobiles, the uplink sum-throughput problem is solved by water-filling.The reduction follows after subtracting the circuit-power requirement from allocated power.
  • Feasibility: The algorithm first determines the maximum number of active mobiles satisfying circuit-power and total-power constraints.This quantity is denoted z_max.
  • Algorithm: The final algorithm searches candidate active-mobile counts rather than assuming the maximum feasible count is optimal.It sequentially schedules mobiles with high MPT efficiency and maximizes the scheduled users’ uplink sum rate.
  • Algorithm: The sequential algorithm provides a close-to-optimal solution according to simulation results.Its priority is meeting circuit-power constraints because they are prerequisites for information transfer.

B. Multi-User Uplink IT with Fixed Coding Rates

For multi-user uplink information transfer with fixed coding rates, optimal power control prioritizes streams according to their required effective power and serves as many as the power budget permits.

  • Power allocation order: Streams are prioritized by the descending order of the sequence v_n, which combines channel inversion and circuit-power consumption.The sequence is sorted in ascending order as an intermediate step, then the allocation follows the corresponding descending priority.
  • Power allocation order: The algorithm allocates each selected stream the power needed to meet its minimum-SNR requirement, subject to the total power constraint.The maximum number of active streams is the largest integer q_max satisfying the available-power constraint.
  • Interpretation: The resulting policy is a variant of greedy channel inversion that incorporates both closed-loop channel inversion and circuit-power consumption.The final powers are rearranged into the original sub-channel order using the inverse permutation.
  • Solution: The base station optimally allocates power according to policy (43).The policy is specified by the reordered optimal powers and their inverse permutation.
  • Mobile operation: Each active mobile harvests nonzero power and uses all remaining available power for uplink transmission after circuit operation is supported.This property characterizes the optimal policy for the multi-user fixed-rate uplink system.

VIII. SIMULATION RESULTS

Simulations evaluate spectral efficiency under circuit-power constraints across downlink and uplink information-transfer configurations. Power control improves SWIPT efficiency, while the preferred architecture depends on propagation loss and circuit power.

  • Simulation setup: The simulations use line-of-sight, near-free-space propagation with five frequency-nonselective sub-channels and distances of 100 m for single-user and 50–200 m for multi-user systems.The base-station powers are 10 W and 20 W, respectively, with a 5.8 GHz carrier and fading Z following CN(1, 0.2).
  • Downlink IT: TD-IPT achieves about half the spectral efficiency of SWIPT at low to moderate circuit power but can outperform SWIPT at high circuit power for single-user fixed coding rates.The comparison includes equal-power SWIPT and time-division IPT, where each slot alternates between MPT and IT.
  • Downlink IT: Downlink spectral efficiencies decrease as circuit power increases, with a threshold effect for single-user systems and greater sensitivity in multi-user systems.At low circuit power, efficiencies converge to the reliable-power-supply case, reported as extremely high at 10 −13 bit/s/Hz.
  • Uplink IT: Uplink information transfer incurs more than 10 bit/s/Hz of spectral-efficiency reduction from round-trip propagation loss, and TD-IPT outperforms SWIPT in that setting.The sub-optimal multi-user uplink algorithm performs close to the exhaustive-search optimum.
  • Reduced-distance uplink IT: When uplink transmission distances are reduced fivefold, SWIPT and TD-IPT curves intersect, indicating that the preferred method depends on propagation loss and circuit power.SWIPT is preferred when propagation loss is not extremely severe or circuit power is low; otherwise, TD-IPT provides higher spectral efficiency.
  • Overall findings: The simulations show that power control is important for enhancing SWIPT efficiency across the considered configurations.The evaluated comparisons include controlled SWIPT, equal-power SWIPT, and TD-IPT.
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