ISAC-Enabled SWIPT Through Massive MIMO

This chapter examines simultaneous wireless information and power transfer (SWIPT) scenarios. It discusses the main SWIPT receivers, namely, separate and co-located receivers. The chapter provides numerical examples on the performance of the designed SWIPT precoding strategy. It focuses on a co-located SWIPT system, where a HAP serves a set S of devices performing both energy harvesting and information decoding in a given frequency band. The chapter illustrates some numerical results on the performance of the time switching and power splitting protocols. It also discusses some specific promising approaches to boost the performance of SWIPT systems for general wireless energy transfer (WET)-powered internet of things networks. WET and SWIPT systems are subject to non-linear responses that are often model-intractable unless too strong assumptions are adopted. The chapter concludes with an overview of some potential techniques to enable efficient SWIPT in future networks.

This paper considers a relay-assisted massive multiple-input multiple-output (MIMO) downlink system in which a base station (BS) communicates with all terminals via a relay node enabled simultaneous wireless information and power transfer (SWIPT). Both time-switching (TS) and energy-splitting (PS) protocols are respectively considered at the relay node for coordinating energy harvesting and information decoding. The quality-of-service (QoS) fairness problem among terminals is investigated in the considered systems. In detail, the power allocation coefficients and energy harvesting time duration for TS based SWIPT, and the power allocation coefficients and PS ratio for PS based SWIPT are jointly optimised, aiming at seeking to maximise the minimum achievable rate over all terminals. As the formulated problems are non-convex and non-linear, and hard to solve directly, suboptimal heuristic algorithms are proposed for solving them. Additionally, the convergence and complexity of the proposed algorithms are also analysed. Finally, the performance of the proposed algorithms is demonstrated by extensive computer simulations. Results manifest that the proposed algorithms can provide uniformly great QoS for every terminal by resource allocation.

This paper considers simultaneous wireless information and power transfer (SWIPT) mechanisms in a relaying network with finite blocklength (FBL) codes. The reliability of the network is optimized under both a power splitting (PS) protocol and a proposed joint PS and time switching (TS) protocol. Under both protocols, we first determine the overall error probability formulation of the SWIPT-enabled two-hop transmission in the FBL regime. Subsequently, we state and solve optimization problems minimizing the overall error probability. Via numerical analysis, we show the appropriateness of our analytical model and demonstrate the performance advantage of the proposed protocol in comparison to TS and PS protocols. In addition, we provide interesting insights on the system behavior by characterizing the impact of the blocklength, transmit power and packet size on the reliability performance.

This paper analyzes the problem of optimum user association and sum rate maximization for software defined radio access networks (SD-RANs) with access node diversity for fifth generation (5G) wireless networks. We consider four complementary types of access nodes namely, a massive multiple- input multiple-output (MIMO) base station (BS), MIMO BSs, small cells (SCs), and indoor and outdoor distributed antenna systems (DAS). The SDRAN user association problem is solved through a novel three-stage optimization scheme called the place coverage (TPC). TPC divides the user equipment (UEs) into two sets of indoor and outdoor UEs. Initially, TPC associates indoor UEs with the indoor DAS access nodes. Next, outdoor UEs are associated with the outdoor DAS access nodes, SCs, MIMO BSs, and the massive MIMO BS. Finally, the remaining resources of indoor and outdoor access nodes are used to serve the UEs that have not been served. The scope of TPC is multifold. First, TPC reflects the closest model to a real-world diverse 5G network. Secondly, servicing the indoor UEs with iDAS antennas results in lower power load per user for the access network resulting in better coverage, quality, and data speed. Thirdly, TPC provides reduced radiation levels for indoor UEs. Numerical results show that TPC provides significant sum rate and fairness gains over the received signals strength (RSS) based association schemes [1]. Moreover, TPC provides comparable performance levels as the optimum association scheme based on exhaustive search while bringing significant complexity reduction.

This work studies a simultaneous wireless information and power transfer (SWIPT)-enabled relaying network, where a power splitting protocol is applied at the relay before energy harvesting (EH). Due to low-latency requirements, the transmissions are operated with short blocklength codes. We aim at providing a reliability-oriented network design, while for the first time, the finite blocklength (FBL) impact and a realistic nonlinear EH process are jointly considered. In particular, we characterize the overall error probability of the considered network, and formulate the problem minimizing the overall error probability by optimally choosing the power splitting ratio. However, the formulated problem is non-convex due to the nonlinear EH process (which is also non-convex), thus making it challenging to be solved optimally. To tackle this difficulty, we propose a three-step approach to obtain an efficient solution. We first introduce two auxiliary variables, with the assistance of which we reformulate the problem. Then, we apply a convex approximation technique to tightly approximate the problem (at each local point/solution), based on which an efficient iterative algorithm (updating the local point) is finally proposed approaching a high-quality sub-optimal solution. Simulation results are provided to validate the convergence of the proposed algorithm and evaluate the performance in comparison to benchmarks with linear EH.

Simultaneous wireless information and power transfer (SWIPT) has emerged as a viable technique to energize and connect low-power autonomous devices and enable future Internet of Things (IoT). A major challenge of SWIPT is the energy consumption of the receiver of such low-power devices. An attractive low-power solution consists of an integrated information decoder (ID) and energy harvester (EH) architecture for SWIPT receiver (IntRx) where the received radiofrequency (RF) signal is first rectified before being used for information decoding. Such architecture eliminates the need for energy-consuming RF components, such as local oscillators and mixers. This article proposes a novel modulation and demodulation method for the IntRx SWIPT architecture based on pulse position modulation (PPM) where information is encoded in the position of the pulse. The new method transmits high amplitude pulses to increase the peak-to-average power ratio (PAPR) of the transmit signal and exploits the EH's nonlinearity so as to boost the harvested dc power. Simultaneously, the information can be decoded from the rectifier signal by simply finding the position of the pulse in a certain symbol duration. We have analyzed both the information and the power transfer performance of the newly proposed PPM for IntRx SWIPT theoretically, numerically, and experimentally. To that end, we have established a SWIPT system testbed in an indoor environment by prototyping a base station to transfer information-power signal and the IntRx SWIPT receiver, including ID and EH blocks. The performance evaluation of the PPM was carried out in various conditions, and the results have been compared and contrasted to conventional signals. Theoretical, numerical, and experimental results highlight the significant benefits of the proposed PPM scheme to enhance the power transfer performance and operate information decoding with low-power consumption.

This book chapter investigates the advances of energy harvesting (EH) and multiple accesses protocols for smart city applications. In particular, a novel communication scheme that combines EH and a cooperative non-orthogonal multiple access (NOMA) system is introduced. In the proposed scheme, the relay harvests energy from the base station to serve some user groups including the near and far users. Later, simultaneous wireless information and power transfer (SWIPT) technique is exploited to determine performance improvement at least amount of harvested energy. The other parameters need to investigate the impact of imperfect power allocation factors on system performance. It is proved that introducing SWIPT does not harm system performance. Furthermore, the outage probability of both near and far users is derived and indicated in closed-form expressions. Numerical simulations are conducted to examine the outage probability of the proposed scheme and to verify the derived formulas. The proposed scheme has the potential to solve the problem of EH in the context of smart city.KeywordsSimultaneous wireless information and power transfer (SWIPT)Non-orthogonal multiple access (NOMA)Outage probabilitySmart cities

This paper investigates a relay assisted simultaneous wireless information and power transfer (SWIPT) for downlink in cellular systems. Cooperative non-orthogonal multiple access (C-NOMA) is employed along with power splitting protocol to enable both energy harvesting (EH) and information processing (IP). A downlink model consists of a base station (BS) and two users is considered, in which the near user (NU) is selected as a relay to forward the received signal from the BS to the far user (FU). Maximum ratio combining is then employed at the FU to combine both the signals received from the BS and NU. Closed form expressions of outage propability, throughput, ergodic rate and energy efficiency (EE) are firstly derived for the SWIPT based C-NOMA considering both scenarios of with and without direct link between the BS and FU. The impacts of EH time, EH efficiency, power-splitting ratio, source data rate and distance between different nodes on the performance are then investigated. The simulation results show that the C-NOMA with direct link achieves an outperformed performance over C-NOMA without direct link. Moreover, the performance of C-NOMA with direct link is also higher than that for OMA. Specifically, (1) the outage probability for C-NOMA in both direct and relaying link cases is always lower than that for OMA. (2) the outage probability, throughput and ergodic rate vary according to beta, (3) the EE of both users can obtain in SNR range of from -10 to 5 dB and it decreases linearly as SNR increases. Numerical results are provided to verify the findings.

In this paper, we consider the problem of Angle of Departure (AoD) based channel feedback in Frequency Division Duplex (FDD) massive Multiple-Input Multiple-Output (MIMO) systems with multiple antennas at the users. We consider the use of Zero-Forcing Block Diagonalization (BD) as the downlink precoding scheme. We consider two different cases; one in which the number of streams intended for a user equals the number of antennas at that user and the other case in which the number of streams is less than the number of user antennas. BD requires the feedback of the subspace spanned by the channel matrix at the user or a subspace of it in the case of having less number of streams than the number of antennas at a specific user. Based on our channel model, we propose a channel feedback scheme that requires less feedback overhead compared to feeding back the whole channel matrix. Then, we quantify the rate gap between the rate of the system with perfect Channel State Information (CSI) at the massive MIMO Basestation (BS) and our proposed channel feedback scheme for a given number of feedback bits. Finally, we design feedback codebooks based on optimal subspace packing in the Grassmannian manifold. We show that our proposed codes achieve performance that is very close to the performance of the system with perfect CSI at the BS.

This paper presents a ASK modulation based modeling of Simultaneous Wireless Information and Power Transfer (SWIPT) system in LabVIEW. It supports in designing of SWIPT based system which able to harvest RF energy along with transfer of information simultaneously. At the receiver end, both RF energy harvesting (EH) and information decoding (ID) paths are modeled. RF energy harvesting path consists of RF rectifier and low pass filter. While ID path contains RF envelope detector and ASK demodulator. For the simulation verification of SWIPT system, a 2-ASK modulated RF signal is used at 900MHz. This modeling provides flexible parameters selection for the simulation of SWIPT system which helps in understanding and development of SWIPT system.

This paper investigates the physical layer security issue in an amplify-and-forward (AF) multi-input multi-output (MIMO) two-way relay assisted cognitive radio (CR) nonorthogonal multiple access (NOMA) network, where the simultaneous wireless information and power transfer (SWIPT) technology is employed to improve network energy efficiency. We consider the scenario that a pair of primary users and two pairs of secondary users (SUs) exchange information via a MIMO two-way relay, where the edge SU of each SU pair is untrusted and tries to wiretap the central SU’s information. For ensuring security, we aim to maximize the sum achievable secrecy rate (SASR) by jointly optimizing the power allocation at all users, power splitting factor and relay beamforming subject to the quality of service (QoS), energy harvesting and transmit power constraints. The formulated optimization problem is highly nonconvex due to coupling variables, thus it is challenging to solve. An effective path-following (PF)-based algorithm is proposed, which is proven to converge to a stationary point. Theoretical and simulation results show that the proposed PF-based algorithm has lower complexity than the state-of-art algorithm. To further reduce complexity, we proposed a zero-forcing (ZF)-based scheme. Numerical simulations show that the proposed PF-based algorithm achieves the same SASR as the state-of-art algorithm with moderate complexity, while the proposed ZF-based scheme strikes a good balance between performance and complexity.

In this paper, we investigate the performance of cache-assisted simultaneous wireless information and power transfer (SWIPT) cooperative systems, in which one source communicates with one destination via the aid of multiple relays. In order to prolong the relays’ serving time, the relays are assumed to be equipped with a cache memory and energy harvesting (EH) capability. Based on the time-splitting mechanism, we analyze the effect of caching on the system performance in terms of the serving throughput and the stored energy at the relay. In particular, two optimization problems are formulated to maximize the relay-destination throughput and the energy stored at the relay subject to some quality-of-service (QoS) constraints, respectively. By using the KKT conditions and with the help of the Lambert function, closed-form solutions are obtained for the two formulated problems. In order to further improve the performance, a relay selection policy is introduced to select the best relay based on either the maximum throughput between the relays’ and destination link or maximum stored energy at the relay, for conveying information to the destination. Numerical results reveal significant benefits of incorporating caching capabilities to SWIPT systems, in terms of improved serving time, throughput, and EH performance at the relays.

Future wireless networks promise immense increases on data rate and energy efficiency while overcoming the difficulties of charging the wireless stations or devices in the Internet of Things (IoT) with the capability of simultaneous wireless information and power transfer (SWIPT). For such networks, jointly optimizing beamforming, power control, and energy harvesting to enhance the communication performance from the base stations (BSs) (or access points (APs)) to the mobile nodes (MNs) served would be a real challenge. In this work, we formulate the joint optimization as a mixed integer nonlinear programming (MINLP) problem, which can be also realized as a complex multiple resource allocation (MRA) optimization problem subject to different allocation constraints. By means of deep reinforcement learning to estimate future rewards of actions based on the reported information from the users served by the networks, we introduce single-layer MRA algorithms based on deep Q-learning (DQN) and deep deterministic policy gradient (DDPG), respectively, as the basis for the downlink wireless transmissions. Moreover, by incorporating the capability of data-driven DQN technique and the strength of noncooperative game theory model, we propose a two-layer iterative approach to resolve the NP-hard MRA problem, which can further improve the communication performance in terms of data rate, energy harvesting, and power consumption. For the two-layer approach, we also introduce a pricing strategy for BSs or APs to determine their power costs on the basis of social utility maximization to control the transmit power. Finally, with the simulated environment based on realistic wireless networks, our numerical results show that the two-layer MRA algorithm proposed can achieve up to 2.3 times higher value than the single-layer counterparts which represent the data-driven deep reinforcement learning-based algorithms extended to resolve the problem, in terms of the utilities designed to reflect the trade-off among the performance metrics considered.

In this paper, we focus on optimization of simultaneous wireless information and power transfer (SWIPT) in uplink cloud radio access network (C-RAN). The key idea is to design transceiver architecture and implement the SWIPT strategy at remote radio heads (RRHs). The minimum mean-square-error (MMSE) is considered as the performance metrics with transmit power constraint and energy constraint. Toward the goal of MMSE, the precoders and the detectors are iteratively updated in proposed scheme. However, because of the energy constraint, the precoding optimization problem with a specified detection matrix become non-convex. To solve this problem, a new precoding design based on the Lagrangian dual relaxation (LDR) is developed. Meanwhile, conditions to make sure the optimization problem has its physical interpretation and LDR become convex are determined. Finally, simulation results demonstrate that the proposed transceiver design can significantly improve the system performance.

The main challenges of sensing in harsh industrial and biological environments are the limited energy of sensor nodes and the difficulty of charging sensor nodes. Simultaneous wireless information and power transfer (SWIPT) is a non-invasive option to replenish energy. SWIPT harvests energy and decodes information from the same RF signal, which is influencing the design of a wireless sensor network. In multi-hop multi-flow wireless sensor networks, interference generally exists, and the interference has a different influence on SWIPT. Route, interference and SWIPT are dependent. However, existing works consider SWIPT link resource allocation with a given route or only select path for one flow without interference. Therefore, this paper firstly analyzes the influence of interference on SWIPT, and select the SWIPT routing with interference. We design an interference-based information and energy allocation model to maximize the link capacity with SWIPT. Then, we design an interference-aware route metric, formulate SWIPT routing problem, and design an interference-aware SWIPT routing algorithm. The simulation results show that as the number of flows increases, there is more likely to obtain performance gains from interference and SWIPT.