In this letter, we study the impact of the low-pass resistor-capacitor (RC) filter on radio frequency (RF) wireless power transfer (WPT). The RC filter influences both the RF bandwidth by removing the harmonics as well as the ripple voltage at the output of the rectifier. In particular, a large (small) RC time constant, reduces (increases) the ripple but decreases (enhances) the direct-current (DC) component. By following a Fourier series approach, we obtain closed-form expressions for the rectifier's output voltage, the RC filter's output as well as the DC voltage. Our analytical framework provides a complete characterization of the RC filter's impact on the WPT performance. We show that this complete and tractable analytical framework is suitable for the proper design of the RC filter in WPT systems.
This study considers the Joint Transmit/Reflect Beamforming and Power Splitting (JTRBPS) optimization problem in a spectrum underlay setting, such that the transmit sum-energy of the intelligent reflecting surface (IRS)-aided secondary transmitter (ST) is minimized subject to the quality-of-service requirements of the PS-simultaneous wireless information and power transfer (SWIPT) secondary receivers and the interference constraints of the primary receivers (PR). The interference at the PRs caused by the reception of IRS-reflected signals sent by the primary transmitter is taken into account. A coordinated channel state information (CSI) acquisition protocol is proposed. Next, assuming availability at the ST of perfect CSI for all direct and IRS-cascaded transmitter--receiver channels, two penalty-based iterative algorithms are developed: an alternating minimization algorithm that involves semi-definite relaxation in JTBPS design and successive convex approximation in RB optimization, and a block coordinate descent algorithm that employs the Riemannian conjugate gradient algorithm in RB updates. Finally, an outage-constrained robust design under imperfect CSI is devised. Numerical simulations highlight the performance gains of the proposed strategies over benchmarks, corroborate the benefits of using an IRS, and provide valuable insights.
The efficiency of wireless information and power transfer (WIPT) systems requires an essential reevaluation and rethinking of the entire transceiver chain, which is characterized by a bottom-up cross-layer design approach. In this paper, we introduce and describe the key design layers: i) "Mathematical modeling", associated with the investigation of mathematical models for the wireless power transfer process, ii) "Information-theoretic limits", which refers to the fundamental limits of the WIPT channel, iii) "Link design", corresponding to signal processing techniques that make WIPT feasible, iv) "System-level perspective", which studies the developed WIPT techniques from a macroscopic system-level point-of-view, and v) "Experimental studies", that refers to real-world implementation of WIPT systems. These layers are well-connected and their interplay is imperative for the effective design of WIPT systems. Specific case studies are discussed, which demonstrates the interdisciplinary nature of the aforementioned cross-layer design framework.
By utilizing the combination of two powerful tools i.e., stochastic geometry (SG) and evolutionary game theory (EGT), in this paper, we study the problem of mobile user (MU) mode selection in heterogeneous sub-$6$ GHz/millimeter wave (mmWave) cellular networks. Particularly, by using SG tools, we first propose an analytical framework to assess the performance of the considered networks in terms of average signal-to-interference-plus-noise (SINR) ratio, average rate, and mobility-induced time overhead, for scenarios with user mobility{.} According to the SG-based framework, an EGT-based approach is presented to solve the problem of access mode selection. Specifically, two EGT-based models are considered, where for each MU its utility function depends on the average SINR and the average rate, respectively, while the time overhead is considered as a penalty term. A distributed algorithm is proposed to reach the evolutionary equilibrium, where the existence and stability of the equilibrium is theoretically analyzed and proved. Moreover, we extend the formulation by considering information delay exchange and evaluate its impact on the convergence of the proposed algorithm. Our results reveal that the proposed technique can offer better spectral efficiency and connectivity in heterogeneous sub-$6$ GHz/mmWave cellular networks with mobility, compared with the conventional access mode selection techniques.
Wireless power transfer (WPT) is a promising technology for powering up distributed devices in machine type networks. Over the last decade magnetic resonant coupling (MRC) received significant interest from the research community, since it is suitable for realizing mid-range WPT. In this paper, we investigate the performance of a single cell MRC-WPT network with multiple receivers, each equipped with an electromagnetic coil and a load. We first consider pre-adjusted loads for the receivers and by taking into account spatial randomness, we derive the harvesting outage probability of a receiver; for both the strong and loosely coupling regions. Then, we develop a non-cooperative game for a fixed receiver topology, in order to acquire the optimal load which maximizes each receiver's harvested power. Throughout our work, we obtain insights for key design parameters and present numerical results which validate our analysis.
Simultaneous wireless information and power transfer (SWIPT) has long been proposed as a key solution for charging and communicating with low-cost and low-power devices. However, the employment of radio frequency (RF) signals for information/power transfer needs to comply with international health and safety regulations. In this paper, we provide a complete framework for the design and analysis of far-field SWIPT under safety constraints. In particular, we deal with two RF exposure regulations, namely, the specific absorption rate (SAR) and the maximum permissible exposure (MPE). The state-of-the-art regarding SAR and MPE is outlined together with a description as to how these can be modeled in the context of communication networks. We propose a deep learning approach for the design of robust beamforming subject to specific information, energy harvesting and SAR constraints. Furthermore, we present a thorough analytical study for the performance of large-scale SWIPT systems, in terms of information and energy coverage under MPE constraints. This work provides insights with regards to the optimal SWIPT design as well as the potentials from the proper development of SWIPT systems under health and safety restrictions.
In this paper, a cooperative protocol is investigated for a multi-hop network consisting of relays with buffers of finite size, which may operate in different communication modes. The protocol is based on the myopic decode-and-forward strategy, where each node of the network cooperates with a limited number of neighboring nodes for the transmission of the signals. Each relay stores in its buffer the messages that were successfully decoded, in order to forward them through the appropriate channel links, based on its supported communication modes. A complete theoretical framework is investigated that models the evolution of the buffers and the transitions at the operations of each relay as a state Markov chain (MC). We analyze the performance of the proposed protocol in terms of outage probability and derive an expression for the achieved diversity-multiplexing tradeoff, by using the state transition matrix and the related steady state of the MC. Our results show that the proposed protocol outperforms the conventional multi-hop relaying scheme and the system's outage probability as well as the achieved diversity order depend on the degree of cooperation among neighboring nodes and the communication model that is considered for every relay of the network.
Rate splitting (RS) and wireless edge caching are essential means for meeting the quality of service requirements of future wireless networks. In this work, we focus on the cross-layer co-design of wireless edge caching schemes with sophisticated physical layer techniques, which facilitate non-orthogonal multiple access and interference mitigation. A flexible caching-aided RS (CRS) technique is proposed that operates in various modes that specify the cache placement at the receivers. We consider two caching policies: the intelligent coded caching (CC), as well as the well-known most popular content (MPC) policy. Both caching policies are integrated within the design parameters of RS in order to serve multiple cache-enabled receivers. The proposed technique is investigated from a system level perspective by taking into account spatial randomness. We consider a single cell network consisting of center and edge receivers and provide a comprehensive analytical framework for the evaluation of the proposed technique in terms of achieved rates. Specifically, we derive the rate achieved at each receiver under minimum rate constraints while incorporating the cache placement characteristics. Numerical results are presented which highlight the flexibility of the proposed technique and show how caching can be exploited in order to further boost the performance of RS.
In this paper, we investigate multi-dimensional chaotic signals with respect to wireless power transfer (WPT). Specifically, we analyze a multi-dimensional Lorenz-based chaotic signal under a WPT framework. By taking into account the nonlinearities of the energy harvesting process, closed-form analytical expressions for the average harvested energy are derived. Moreover, the practical limitations of the high power amplifier (HPA) at the transmitter are also taken into consideration. We interestingly observe that for these types of signals, high peak-to-average-power-ratio (PAPR) is not the only criterion for obtaining enhanced WPT. We demonstrate that while the HPA imperfections do not significantly affect the signal PAPR, it notably degrades the energy transfer performance. As the proposed framework is general, we also demonstrate its application with respect to a Henon signal based WPT. Finally we compare Lorenz and Henon signals with the conventional multisine waveforms in terms of WPT performance.
This paper studies the fast adaptive beamforming for the multiuser multiple-input single-output downlink. Existing deep learning-based approaches assume that training and testing channels follow the same distribution which causes task mismatch, when the testing environment changes. Although meta learning can deal with the task mismatch, it relies on labelled data and incurs high complexity in the pre-training and fine tuning stages. We propose a simple yet effective adaptive framework to solve the mismatch issue, which trains an embedding model as a transferable feature extractor, followed by fitting the support vector regression. Compared to the existing meta learning algorithm, our method does not necessarily need labelled data in the pre-training and does not need fine-tuning of the pre-trained model in the adaptation. The effectiveness of the proposed method is verified through two well-known applications, i.e., the signal to interference plus noise ratio balancing problem and the sum rate maximization problem. Furthermore, we extend our proposed method to online scenarios in non-stationary environments. Simulation results demonstrate the advantages of the proposed algorithm in terms of both performance and complexity. The proposed framework can also be applied to general radio resource management problems.