Chin Keong Ho

Optimal Energy Allocation for Wireless Communications With Energy Harvesting Constraints

We consider the use of energy harvesters, in place of conventional batteries with fixed energy storage, for point-to-point wireless communications. In addition to the challenge of transmitting in a channel with time selective fading, energy harvesters provide a perpetual but unreliable energy source. In this paper, we consider the problem of energy allocation over a finite horizon, taking into account channel conditions and energy sources that are time varying, so as to maximize the throughput. Two types of side information (SI) on the channel conditions and harvested energy are assumed to be available: causal SI (of the past and present slots) or full SI (of the past, present and future slots). We obtain structural results for the optimal energy allocation, via the use of dynamic programming and convex optimization techniques. In particular, if unlimited energy can be stored in the battery with harvested energy and the full SI is available, we prove the optimality of a water-filling energy allocation solution where the so-called water levels follow a staircase function.

Wireless powered communication: opportunities and challenges

The performance of wireless communication is fundamentally constrained by the limited battery life of wireless devices, the operations of which are frequently disrupted due to the need of manual battery replacement/recharging. The recent advance in RF-enabled wireless energy transfer (WET) technology provides an attractive solution named wireless powered communication (WPC), where the wireless devices are powered by dedicated wireless power transmitters to provide continuous and stable microwave energy over the air. As a key enabling technology for truly perpetual communications, WPC opens up the potential to build a network with larger throughput, higher robustness, and increased flexibility compared to its battery-powered counterpart. However, the combination of wireless energy and information transmissions also raises many new research problems and implementation issues that need to be addressed. In this article, we provide an overview of state-of- the-art RF-enabled WET technologies and their applications to wireless communications, highlighting the key design challenges, solutions, and opportunities ahead.

Performance bounds for two-way amplify-and-forward relaying

In this paper, the average sum rate of two-way amplify-and-forward (AF) half-duplex relaying system is analyzed. To this end, we first derive the harmonic mean of two independent gamma distributed random variables which have the same shape parameter but different scale parameters. By deriving tight upper and lower bounds for the average sum rate of two-way relaying, we verify that two-way relaying can significantly recover the spectrum efficiency loss of one-way relaying. We also extend the two-way AF half-duplex relaying to the case where source and destination terminals both transmit Alamoutis orthogonal space time block code (OSTBC) utilizing two antennas and the relay has only one antenna. By deriving both upper and lower bounds for the average sum rate as well as an upper bound for the pairwise error probability (PEP) for the proposed two-way OSTBC scheme, we show that the average sum rate is further improved compared to the single antenna case and a diversity order of two is also achieved. Furthermore, optimal power allocations under a global power constraint for two-way relaying with single antenna and the proposed two-way OSTBC scheme are derived analytically.

Wireless Information and Power Transfer in Multiuser OFDM Systems

In this paper, we study the optimal design for simultaneous wireless information and power transfer (SWIPT) in downlink multiuser orthogonal frequency division multiplexing (OFDM) systems, where the users harvest energy and decode information using the same signals received from a fixed access point (AP). For information transmission, we consider two types of multiple access schemes, namely, time division multiple access (TDMA) and orthogonal frequency division multiple access (OFDMA). At the receiver side, due to the practical limitation that circuits for harvesting energy from radio signals are not yet able to decode the carried information directly, each user applies either time switching (TS) or power splitting (PS) to coordinate the energy harvesting (EH) and information decoding (ID) processes. For the TDMA-based information transmission, we employ TS at the receivers; for the OFDMA-based information transmission, we employ PS at the receivers. Under the above two scenarios, we address the problem of maximizing the weighted sum-rate over all users by varying the time/frequency power allocation and either TS or PS ratio, subject to a minimum harvested energy constraint on each user as well as a peak and/or total transmission power constraint. For the TS scheme, by an appropriate variable transformation the problem is reformulated as a convex problem, for which the optimal power allocation and TS ratio are obtained by the Lagrange duality method. For the PS scheme, we propose an iterative algorithm to optimize the power allocation, subcarrier (SC) allocation and the PS ratio for each user. The performances of the two schemes are compared numerically as well as analytically for the special case of single-user setup. It is revealed that the peak power constraint imposed on each OFDM SC as well as the number of users in the system play key roles in the rate-energy performance comparison by the two proposed schemes.

Throughput Optimization for Massive MIMO Systems Powered by Wireless Energy Transfer

This paper studies a wireless-energy-transfer (WET) enabled massive multiple-input-multiple-output (MIMO) system (MM) consisting of a hybrid data-and-energy access point (H-AP) and multiple single-antenna users. In the WET-MM system, the H-AP is equipped with a large number M of antennas and functions like a conventional AP in receiving data from users, but additionally supplies wireless power to the users. We consider frame-based transmissions. Each frame is divided into three phases: the uplink channel estimation (CE) phase, the downlink WET phase, as well as the uplink wireless information transmission (WIT) phase. Firstly, users use a fraction of the previously harvested energy to send pilots, while the H-AP estimates the uplink channels and obtains the downlink channels by exploiting channel reciprocity. Next, the H-AP utilizes the channel estimates just obtained to transfer wireless energy to all users in the downlink via energy beamforming. Finally, the users use a portion of the harvested energy to send data to the H-AP simultaneously in the uplink (reserving some harvested energy for sending pilots in the next frame) . To optimize the throughput and ensure rate fairness, we consider the problem of maximizing the minimum rate among all users. In the large-M regime, we obtain the asymptotically optimal solutions and some interesting insights for the optimal design of WET-MM system.

Wireless information and power transfer: Architecture design and rate-energy tradeoff

Simultaneous information and power transfer over the wireless channels potentially offers great convenience to mobile users. Yet practical receiver designs impose technical constraints on its hardware realization, as practical circuits for harvesting energy from radio signals are not yet able to decode the carried information directly. To make theoretical progress, we propose a general receiver operation, namely, dynamic power splitting (DPS), which splits the received signal with adjustable power ratio for energy harvesting and information decoding, separately. Three special cases of DPS, namely, time switching (TS), static power splitting (SPS) and on-off power splitting (OPS) are investigated. The TS and SPS schemes can be treated as special cases of OPS. Moreover, we propose two types of practical receiver architectures, namely, separated versus integrated information and energy receivers. The integrated receiver integrates the front-end components of the separated receiver, thus achieving a smaller form factor. The rate-energy tradeoff for the two architectures are characterized by a so-called rate-energy (R-E) region. The optimal transmission strategy is derived to achieve different rate-energy tradeoffs. With receiver circuit power consumption taken into account, it is shown that the OPS scheme is optimal for both receivers. For the ideal case when the receiver circuit does not consume power, the SPS scheme is optimal for both receivers. In addition, we study the performance for the two types of receivers under a realistic system setup that employs practical modulation. Our results provide useful insights to the optimal practical receiver design for simultaneous wireless information and power transfer (SWIPT).

MIMO Broadcasting for Simultaneous Wireless Information and Power Transfer

This paper studies the performance limits of multi-antenna wireless broadcasting systems for simultaneous information and power (energy) transfer. For the purpose of exposition, a three-node network is investigated, in which one receiver harvests energy and another receiver decodes information separately from the signals broadcast by a common transmitter. Two scenarios are examined, where the information receiver and energy receiver are separated and see different channels from the transmitter, or co-located and see the same channel from the transmitter. For the case of separated receivers, we derive the optimal transmission strategies to achieve different tradeoffs for maximal information rate versus energy transfer, which are characterized by the boundary of a so-called rate-energy (R-E) region. For the case of co-located receivers, we show an outer bound for the achievable R-E region, due to the potential limitation that practical circuits for harvesting energy from radio signals are not yet able to decode the carried information at the same time. Under this constraint, we propose two practical receiver designs for the co-located receivers, namely, time switching and power splitting, and characterize their achievable R-E regions in comparison with the outer bound.

Two-Way Relaying over OFDM: Optimized Tone Permutation and Power Allocation

We consider an amplify-and-forward scheme for two-way relaying over OFDM, in which two nodes wish to exchange information via a relay. Assuming full channel knowledge, we perform power allocation for the relay and both information-exchanging nodes, as well as tone permutation at the relay, so as to maximize the sum capacity. A dual decomposition technique is employed for power allocation, while a greedy approach is proposed for tone permutation. In particular, we explore an interesting water-filling behavior displayed by this power allocation solution. Numerical results demonstrate that substantial capacity gains are achieved by implementing the two proposed solutions, either individually or successively.

Full-Duplex Wireless-Powered Communication Network With Energy Causality

In this paper, we consider a wireless communication network with a full-duplex hybrid energy and information access point and a set of wireless users with energy harvesting capabilities. The hybrid access point (HAP) implements full-duplex through two antennas: one for broadcasting wireless energy to users in the downlink and the other for simultaneously receiving information from the users via time division multiple access (TDMA) in the uplink. Each user can continuously harvest wireless power from the HAP until it transmits, i.e., the energy causality constraint is modeled by assuming that energy harvested in the future cannot be used for the current transmission. This leads to the causal dependence of each users harvesting time on the transmission time of earlier users, e.g., the second user scheduled to transmit can harvest more energy if the first user has longer transmission time. Under this setup, we investigate the sum-throughput maximization (STM) problem and the total-time minimization (TTM) problem for the proposed full-duplex wireless-powered communication network. For the STM problem, the optimal solution is obtained as a closed-form expression, which can be computed with linear complexity. For the TTM problem, by exploiting the properties of the coupled constraints, we propose a two-step algorithm to obtain an optimal solution. Then, low-complexity suboptimal solutions are proposed for each problem by exploiting the characteristics of the optimal solutions. Finally, simulation studies on the effect of user scheduling show that different scheduling strategies should be adopted for STM and TTM.

Block-iterative generalized decision feedback equalizers for large MIMO systems: algorithm design and asymptotic performance analysis

This paper studies the problem of signal detection for multiple-input multiple-output (MIMO) channels with large signal dimensions. We propose a block-iterative generalized decision feedback equalization (BI-GDFE) receiver to recover the transmitted symbols in a block-iterative manner. By exploiting the input-decision correlation, a measure for the reliability of the earlier-made decisions, we design the feed-forward equalizers (FFEs) and feedback equalizers (FBEs) in such a way that maximized signal-to-interference-plus-noise ratio (SINR) is achieved for each of the iterations. Novel implementations are also introduced to simplify the complexity of the receiver, which requires only one-tap filters for FFE and FBE. The proposed receiver also works when the signal dimension is greater than the observation dimension. The asymptotic performance of the proposed receiver is analyzed and its convergence has been confirmed through numerical evaluations for various parameters. Computer simulations are presented to illustrate the capability of the proposed receiver to achieve single user matched-filter bound (MFB) for large random MIMO channels when the received SNR is high enough.