In this paper, we propose a lightwave power transfer-enabled underwater optical integrated sensing and communication (O-ISAC) system, where an access point (AP) mounted on a seasurface ship transmits lightwave signals to two nodes, namely ($i$) a seabed sensor that harvests energy and transmits uplink information to the AP, and ($ii$) a sensing target whose position is estimated by the AP using an array of pinhole cameras. To capture practical deployment conditions, the ship attitude variation is modeled through its roll, pitch, and yaw angles, each following a Gaussian distribution under low-to-moderate sea states. Closed-form approximations are derived for the mean squared error (MSE) of target localization and the achievable uplink data rate. Analytical and simulation results demonstrate excellent agreement, validating the proposed models and derived expressions, while revealing the fundamental communication-sensing tradeoff in the O-ISAC system. The results further provide valuable design insights, including the optimal camera placement on the ship to minimize localization error, achieving a minimum MSE of $10^{-2}$ $\text{m}^2$ with multiple cameras under roll, pitch, and yaw angle variation of $10^{\circ}$, and the optimal harvest-use ratio of $0.55$ for the considered setup.

The majority in existing energy harvesting (EH) models utilize complex analysis and often overlook the memory effects of the system’s low-pass filter (LPF). In this work, we aim to fill this gap and propose a simple yet effective approach to model the receiver’s output and capture the LPF’s memory. Specifically, we analyze two fundamental circuits: the half-wave rectifier (HWR) and the diplexer-based receiver (DBR). By using circuit analysis, we derive mathematical models for each receiver’s output, validated through circuit simulations. We then investigate these models in the context of integrated simultaneous wireless information and power transfer (SWIPT) receivers. For the HWR, we consider amplitude modulation and, using communication theory tools, we evaluate the performance in terms of bit error rate (BER) for both maximum likelihood (ML) and ML sequence detection (MLSD) schemes. Our results reveal the impact of memory-induced intersymbol interference on the BER and indicate that MLSD is necessary towards achieving higher data rates. For the DBR, we show that its LPF exhibits similar characteristics to the HWR yet is able to achieve better EH performance due to the lack of signal splitting. Finally, we explore the DBR’s band-pass filter output for information decoding, highlighting its capability to also use phase modulation. Clearly the DBR stands out as a more flexible receiver, while the HWR’s simple design makes it ideal for devices with limited resources.

The concept of fluid antennas (FAs) has emerged as a promising solution to enhance the spectral efficiency of wireless networks, achieved by introducing additional degrees of freedom, including reconfigurability and flexibility. In this paper, we investigate the use of index-modulated (IM) transmissions within the framework of FA systems, where an FA position is activated during each transmission interval. This approach is motivated by the common characteristics exhibited by FAs and IM transmissions, which entails the use of a single radio-frequency chain. From this perspective, we derive a closed-form expression for the bit error rate of IM-FAs considering spatial correlation, demonstrating superior performance compared to conventional IM systems. To enhance the performance of IM-FAs in correlated conditions, channel coding techniques are applied. We first analyze a set partition coding (SPC) scheme for IM-FAs to spatially separate the FA ports, and provide a tight performance bound over correlated channels. Furthermore, the spatial SPC scheme is extended to turbo-coded modulation where the performance is analyzed for low and high signal-to-noise ratios. Our results reveal that through the implementation of channel coding techniques designed for FAs and IM transmission, the performance of coded IM-FAs exhibits notable enhancements, particularly in high correlation scenarios.

In this paper, we study the fundamental limits of simultaneous semantic information and power transfer in wireless networks, where we consider both the point-to-point case as well as the Gaussian multiple access channel (MAC). Specifically, for the point-to-point case, we consider a three-party communication system, where a transmitter aims to simultaneously convey semantic information to an information receiver and energy to an energy harvesting receiver (ER). An achievable and a converse region in terms of information and energy rates are presented for both the discrete memoryless (DM) and Gaussian channel. For the DM channel, the achievable region is obtained by utilizing the asymptotic equipartition property and a converse region is obtained by using outer bounds on the semantic information rates. For the Gaussian channel, we characterize an achievable region by applying a power splitting technique between the information and the semantic context parts. A converse region is obtained that provides an estimate on the information-energy capacity while taking into account semantics. On the other hand, for the Gaussian MAC case, we consider an hybrid setup where a semantic transmitter and a conventional transmitter are employed subject to an energy harvesting constraint at the ER. Specifically, we characterize the semantic-bit information energy region, by providing an achievable and a converse region. Numerical results show that in both cases a higher performance can be achieved in terms of information and energy rates when considering a low semantic ambiguity code in comparison to the classical coding scheme (without semantic). Moreover, in the context of Gaussian MAC, it is shown that it is preferable to use semantic communications in scenarios with low signal-to-noise ratio (SNR), while conventional communications is more suitable at high SNRs.

This paper investigates the problem of transmit waveform design in the context of a chaotic signal-based self-sustainable reconfigurable intelligent surface (RIS)-aided system for simultaneous wireless information and power transfer (SWIPT). Specifically, we propose a differential chaos shift keying (DCSK)-based RIS-aided point-to-point set-up, where the RIS is partitioned into two non-overlapping surfaces. The elements of the first sub-surface perform energy harvesting (EH), which in turn, provide the required power to the other sub-surface operating in the information transfer (IT) mode. In this framework, by considering a generalized frequency-selective Nakagami-mfading scenario as well as the nonlinearities of the EH process, we derive closed-form analytical expressions for both the bit error rate (BER) at the receiver and the harvested power at the RIS. Our analysis demonstrates, that both these performance metrics depend on the parameters of the wireless channel, the transmit waveform design, and the number of reflecting elements at the RIS, which switch between the IT and EH modes, depending on the application requirements. Moreover, we show that, having more reflecting elements in the IT mode is not always beneficial and also, for a given acceptable BER, we derive a lower bound on the number of RIS elements that need to be operated in the EH mode. Furthermore, for a fixed RIS configuration, we investigate a trade-off between the achievable BER and the harvested power at the RIS and accordingly, we propose appropriate transmit waveform designs. Finally, our numerical results illustrate the importance of our intelligent DCSK-based waveform design on the considered framework.

In this paper, we propose a novel simultaneous wireless information and power transfer (SWIPT) technique that employs orthogonal frequency-division multiplexing (OFDM)-based waveforms. By using deterministic symbols at the subcarriers with appropriate phase rotation, the proposed scheme embeds information into the position of the power peak of the OFDM-based waveform and is suitable for low-complexity SWIPT integrated receivers. Low-complexity decision rules are also investigated to extract information at the output of the rectification circuit. We study the performance of the proposed scheme in terms of average harvested power and symbol error probability for various modulation orders. The proposed technique transforms conventional OFDM transmitters to SWIPT devices without costly architectural modifications and is promising for practical applications.

Sixth generation networks will establish the terahertz (THz) era, introducing numerous potential applications for wireless power transfer (WPT). In this work, we focus on a fluid-antenna (FA)-aided WPT system which operates over the THz bands, featuring a non-monotonic diode-based rectifier. By taking into account the circuit's unconventional behavior, we first exploit a linear piece-wise function to approximate rectifier's input-output power relationship. Based on this, we provide an analytical framework in terms of the energy outage probability for three FA port selection (PS) schemes, namely (i) the input-based selection, (ii) the harvesting-based selection, and (iii) the random selection, each corresponding to different complexity and performance. Numerical results which validate our analysis, reveal a novel utilization of FAs, stemming from the alignment of the PS process with the non-monotonic harvesting characteristics.

Fluid antennas (FAs) enable the reconfigurability of systems by moving between predefined locations, known as "ports". This is a promising concept for sixth generation (6G) mobile communications. To make full advantage of FAs, each port needs to estimate the channel, which requires enormous estimation overhead. We study how machine learning techniques can recover the complete channel from measurements at a few predefined ports. The stability of correlation between ports is crucial to the robustness of the network. However, the correlation varies in practice as the propagation environment changes. To address this challenge, we design dedicated sub-networks for different correlation conditions instead of training a single network for all correlation conditions. We also propose a hard selection approach for these sub-networks, which dynamically adjusting the number of ports that need to be estimated for different correlation conditions. Simulation results show that compared with a single neural network, the proposed hard selection approach achieves comparable performance while saving 17% of the estimation overhead.

Wireless power transfer has been proposed as a key technology for the foreseen machine type networks. A main challenge in the research community lies in acquiring a simple yet accurate model to capture the energy harvesting performance. In this work, we focus on a half-wave rectifier and based on circuit analysis we provide the actual output of the circuit which accounts for the memory introduced by the capacitor. The provided expressions are also validated through circuit simulations on ADS. Then, the half-wave rectifier is used as an integrated simultaneous wireless information and power transfer receiver where the circuit's output is used for decoding information based on amplitude modulation. We investigate the bit error rate performance based on two detection schemes: (i) symbol-by-symbol maximum likelihood (ML); and (ii) ML sequence detection (MLSD). We show that the symbol period is critical due to the intersymbol interference induced by circuit. Our results reveal that MLSD is necessary towards improving the error probability and achieving higher data rates.

In this paper, we study the fundamental limits of simultaneous lightwave information and power transfer (SLIPT) systems over channels with path loss and lognormal fading conditions. We consider a system with a single transmitter transferring information to a photodiode-based receiver as well as transferring energy to a photovoltaic cell receiver. In particular, we study the information-energy capacity region and the optimal input distribution under (a) peak-power and average-power constraints at the transmitter, and (b) the minimum harvest energy at the energy harvesting receiver. To this end, an expression for the transition probability distribution function of the lognormal channel is derived. By extending Smith's framework and using Hermite polynomial bases, we prove that the optimal input distribution is discrete with a finite number of mass points. Information-energy capacity region for SLIPT over lognormal channel conditions is illustrated and compared with the case of additive white Gaussian noise channel.

Wireless information and energy transfer (WIET) represents an emerging paradigm that employs controllable transmission of radio frequency signals for the dual purpose of data communication and wireless charging. As such, WIET is widely regarded as an enabler of envisioned sixth-generation (6G) use cases that rely on energy-sustainable Internet-of-Things (IoT) networks, such as smart cities and smart grids. Meeting the quality-of-service demands of WIET, in terms of both data transfer and power delivery, requires effective codesign of the information and energy signals. In this article, we present the main principles and design aspects of WIET, focusing on its integration in 6G networks. First, we discuss how conventional communication notions, such as resource allocation and waveform design, need to be revisited in the context of WIET. Next, we consider various candidate 6G technologies that can boost WIET efficiency, namely, holographic multiple-input multiple-output, near-field beamforming, terahertz communication, intelligent reflecting surfaces (IRSs), and reconfigurable (fluid) antenna arrays. We introduce respective WIET design methods, analyze the promising performance gains of these WIET systems, and discuss challenges, open issues, and future research directions. Finally, a near-field energy beamforming scheme and a power-based IRS beamforming algorithm are experimentally validated using a wireless energy transfer testbed. The vision of WIET in communication systems has been gaining momentum in recent years, with constant progress with respect to theoretical and also practical aspects. The comprehensive overview of the state of the art of WIET presented in this article highlights the potential of WIET systems and their overall benefits in 6G networks.

Reconfigurable antenna multiple-input multiple-output (MIMO) is a foundational technology for the continuing evolution of cellular systems, including upcoming 6G communication systems. In this paper, we address the problem of flexible/reconfigurable antenna configuration selection for point-to-point MIMO antenna systems by using physics-inspired heuristics. Firstly, we optimize the antenna configuration to maximize the signal-to-noise ratio (SNR) at the receiver by leveraging two basic heuristic solvers,i.e.,coherent Ising machines (CIMs), that mimic quantum mechanical dynamics, and quantum annealing (QA), where a real-world QA architecture is considered (D-Wave). A mathematical framework that converts the configuration selection problem into CIM- and QA- compatible unconstrained quadratic formulations is investigated. Numerical and experimental results show that the proposed designs outperform classical counterparts and achieve near-optimal performance (similar to exhaustive search with exponential complexity) while ensuring polynomial complexity. Moreover, we study the optimal antenna configuration that maximizes the end-to-end Shannon capacity. A simulated annealing (SA) heuristic which achieves near-optimal performance through appropriate parameterization is adopted. A modified version of the basic SA that exploits parallel tempering to avoid local maxima is also studied, which provides additional performance gains. Extended numerical studies show that the SA solutions outperform conventional heuristics (which are also developed for comparison purposes), while the employment of the SNR-based solutions is highly sub-optimal.

This paper proposes a chaotic waveform-based multi-antenna receiver design for simultaneous wireless information and power transfer (SWIPT). Particularly, we present a differential chaos shift keying (DCSK)-based SWIPT multiantenna receiver architecture, where each antenna switches between information transfer (IT) and energy harvesting (EH) modes depending on the receiver’s requirements. We take into account a generalized frequency-selective Nakagami-m fading model as well as the nonlinearities of the EH process to derive closed-form analytical expressions for the associated bit error rate (BER) and the harvested direct current (DC), respectively. We show that, both depend on the parameters of the transmitted waveform and the number of receiver antennas being utilized in the IT and EH mode. We investigate a trade-off in terms of the BER and energy transfer by introducing a novel achievable ‘success rate - harvested energy’ region. Moreover, we demonstrate that energy and information transfer are two conflicting tasks and hence, a single waveform cannot be simultaneously optimal for both IT and EH. Accordingly, we propose appropriate transmit waveform designs based on the application specific requirements of acceptable BER or harvested DC or both. Numerical results demonstrate the importance of chaotic waveform-based signal design and its impact on the proposed receiver architecture.

Reconfigurability is a desired characteristic of future communication networks. From a transceiver’s standpoint, this can be materialized through the implementation of fluid antennas (FAs). An FA consists of a dielectric holder, in which a radiating liquid moves between pre-defined locations (called ports) that serve as the transceiver’s antennas. Due to the nature of liquids, FAs can practically take any size and shape, making them both flexible and reconfigurable. In this paper, we deal with the outage probability of FAs under general fading channels, where a port is scheduled based on selection combining. An analytical framework is provided for the performance with and without errors due to post-scheduling delays. We show that although FAs achieve maximum diversity, this cannot be realized in the presence of delays. Hence, a linear prediction scheme is proposed that overcomes delays and restores the lost diversity by predicting the next scheduled port. Moreover, we design space-time coded modulations that exploit the FA’s sequential operation with space-time rotations and code diversity. The derived expressions for the pairwise error probability and average word error rate give an accurate estimate of the performance. We illustrate that the proposed design attains maximum diversity, while keeping a low-complexity receiver, thereby confirming the feasibility of FAs.

In this paper, we present the superposition of chirp waveforms for simultaneous wireless information and power transfer (SWIPT) applications. Exploiting the chirp waveform characteristics enables us to superimpose multiple chirps, thereby allowing transmission of the same number of waveforms over less bandwidth. This enables us to perform subband selection when operating over set of orthogonal subbands. Furthermore, we consider a user equipped with a diplexer-based integrated receiver (DIR), which enables to extract radio frequency power and decode information from the same signal without splitting. Thereby, incorporating chirp superposition and subband selection, a transmission scheme is proposed to exploit both the diode’s nonlinearity and frequency diversity. We derive novel closed-form analytical expressions of the average harvested energy (HE) via transmission of superimposed chirp over selected subbands based on tools from order statistics. We also analyze the downlink information rate achieved at the user. Through our analytical and numerical results, for the considered system setup, we show that superimposed chirp-based SWIPT provides an improvement of 30% in average HE performance as compared to multisine waveforms consisting of a set of fixed-frequency cosine signals, improves the minimum level of HE in a multiuser network, and extends the operating range of energy transfer as compared to fixed-frequency waveforms. Furthermore, we illustrate that the inclusion of DIR at the receiver for SWIPT enlarges the energy-information transfer region when compared to the widely considered power splitting receiver.

In this paper, we investigate the use of index-modulated (IM) transmissions within the framework of fluid antenna (FA) systems, where an FA port is activated during each transmission interval. The adoption of this approach is motivated by the common physical characteristic exhibited by both FAs and IM transmissions, which entails the use of a single radio-frequency (RF) chain. From this perspective, we derive a closed-form expression for the bit error rate (BER) of IM-FA systems in the presence of spatial correlation. Our results demonstrate that IM-FAs outperform conventional IM systems. Since the FA ports are relatively close to each other, we focus on correlation mitigation techniques to improve performance. Specifically, we first investigate two port selection strategies, namely the maximum norm-based and the Euclidean distance-based selection schemes, assuming full channel knowledge. Then, we introduce the concept of spatial set partition coding for IM-FAs to spatially separate the FA ports. Numerical results demonstrate that the performance of IM-FAs is further improved in the case of high correlation whenever we apply the proposed correlation mitigation strategies.

In this paper, we study the fundamental limits of simultaneous semantic information and power transfer. In particular, a three-party communication system is considered, where an information transmitter aims to simultaneously convey semantic information to an information receiver (IR) and deliver energy to an energy harvesting receiver. An achievable and a converse region in terms of information and energy rates (in bits per channel use and energy-units per channel use, respectively) are presented for the discrete memoryless (DM) channel. The achievable region is obtained by using the asymptotic equipartition property (AEP) and a converse region is obtained by using outer bounds on the semantic information rates. In addition, we characterize an achievable region for the Gaussian case by using a power splitting technique between the information and the semantic context parts. A converse region is also obtained that provides an estimate of the information-energy capacity while taking into account semantics. Numerical results show a higher performance in terms of information and energy rates by considering a low semantic ambiguity code in comparison to the classical coding scheme (without semantic).

In this work, a low-complexity hybrid scheme is presented for a wireless network assisted by a reconfigurable intelligent surface (RIS), where channel estimation is required for only a subset of the elements. Specifically, in order to reduce the channel training overhead and boost the performance of the RIS-aided network, the RIS is partitioned in two sub-surfaces, which are sequentially activated to assist the communication. The elements of the first sub-surface align their phase shifts, based on the acquired channel state information (CSI) from a channel training period, whereas the elements of the second sub-surface randomly rotate the phase of the incident signals. The performance of the proposed scheme is investigated under the effect of imperfect CSI acquisition at the RIS. Analytical expressions for the outage probability are derived and useful insights on the optimal configuration of the RIS are provided. We show that, by optimizing the number of elements that need to be estimated, the proposed scheme provides significant performance gains and overcomes the limitations caused by the imperfect CSI acquisition.

In this work, we investigate a superimposed chirp waveform for wireless power transfer (WPT) applications. By taking into account the properties of chirp signals, a transmission scheme is proposed that incorporates chirp superposition and subband selection to exploit both diode’s nonlinearity and frequency diversity. Novel closed-form expressions of the average harvested energy (HE) at the receiver are derived by considering tools from order statistics. Through analytical and numerical results, we prove that superimposed chirp-based WPT improves the HE level of about 30%, and extends the operating range of energy transfer compared to conventional fixed-frequency waveforms.

A desired characteristic of future communication networks is the notion of reconfigurability. For a wireless device, this can be realized through the employment of the so-called fluid antennas (FAs). An FA consists of a dielectric holder, in which a radiating liquid moves between pre-defined locations (called ports) that serve as the device's antennas. Therefore, due to the nature of liquids, an FA can essentially take any size and shape, making them both flexible and reconfigurable. In this paper, we study the outage probability of FAs where the scheduled port, based on selection combining, is subject to scheduling delays. An analytical framework is provided for the performance with and without estimation errors, as a result of post-scheduling delays. We show that even though FAs achieve maximum channel (spatial) diversity, this cannot be attained in the presence of delays.

This paper studies the performance of a wireless powered backscatter communication network consisting of an exciter, several randomly distributed backscattering devices (BDs) and a receiver. We consider selection/scheduling schemes, where a BD is selected for information transmission. The proposed schemes are based on random, end-to-end (e2e) signal-to-noise ratio (SNR) and Euclidean distance. By using stochastic geometry tools, we derive analytical expressions for the outage probability of each selection scheme. Our results show that the scheme based on the e2e SNR achieves the best performance. We also present a cluster-based selection scheme and provide some simulation results. The derived analytical framework provides useful insights on the design of such networks.

In this paper, we investigate the performance of multiple-input multiple-output (MIMO) fading channels assisted by a reconfigurable intelligent surface (RIS), through the employment of partition-based RIS schemes. The proposed schemes are implemented without requiring any channel state information knowledge at the transmitter side; this characteristic makes them attractive for practical applications. In particular, the RIS elements are partitioned into sub-surfaces, which are periodically modified in an efficient way to assist the communication. Under this framework, we propose two low-complexity partition-based schemes, where each sub-surface is adjusted by following an amplitude-based or a phase-based approach. Specifically, the activate-reflect (AR) scheme activates each sub-surface consecutively, by changing the reflection amplitude of the corresponding elements. On the other hand, the flip-reflect (FR) scheme adjusts periodically the phase shift of the elements at each sub-surface. Through the sequential reconfiguration of each sub-surface, an equivalent parallel channel in the time domain is produced. We analyze the performance of each scheme in terms of outage probability and provide expressions for the achieved diversity-multiplexing tradeoff. Our results show that the asymptotic performance of the considered network under the partition-based schemes can be significantly enhanced in terms of diversity gain compared to the conventional case, where a single partition is considered. Moreover, the FR scheme always achieves the maximum multiplexing gain, while for the AR scheme this maximum gain can be achieved only under certain conditions with respect to the number of elements in each sub-surface.

The future sixth generation (6G) wireless communications are envisioned to bring forth the era of the Internet of Everything (IoE). This work investigates wireless power transfer (WPT) in the radiating near-field region, as a medium for charging the low-powered IoE devices. Specifically, we exploit the near- field channel model in order to create power beamfocusing at a predefined focal point. We consider a uniform planar array employing beamfocusing, and provide analytical expressions for the harvested power at the receiver located at (i) a fixed and (ii) a random location in the network. We present numerical results which validate our analysis and draw an insight overview for the near-field WPT under various design parameters while demonstrating the gains brought against far-field WPT.

In this work, we propose an opportunistic beamforming strategy, which enables beam selection through random- rotations of an intelligent reflecting surface (IRS). To boost performance over a time slot, the proposed scheme splits the training period into multiple mini-slots. In each mini-slot, the access point generates different sets of orthonormal beamforming vectors and the IRS employs random-rotations. We provide an analytical framework for the sum-rate capacity and it is shown that a trade-off between the sum-rate capacity and the length of the training period exists due to the time constraint on the communication process. Based on this, we also derive the optimal number of the training mini-slots. The proposed low- complexity scheme outperforms conventional counterparts (single training slot) and approximates the performance of conventional beamforming (with channel state information) even for small number of users. Finally, by utilizing extreme value theory tools, we analyze the system’s performance under an asymptotic scenario, where the number of the users significantly increases.

In this paper, a partition-based scheme is investigated for multiple-input multiple-output (MIMO) fading channels assisted by an intelligent reflecting surface (IRS). In this scheme, the IRS elements are partitioned into sub-surfaces, which are periodically selected to assist the communication. Through the sequential activation of each sub-surface, an equivalent parallel channel in the time domain is produced. The proposed scheme has low implementation complexity and does not require knowledge of the channel state information. We analyze the performance of the proposed scheme in terms of outage probability and provide an expression for the diversity-multiplexing tradeoff. We show, through theoretical and numerical results, that the asymptotic performance of the considered network under the partition-based scheme can be significantly enhanced in terms of diversity gain compared to the conventional case, where a single partition is considered. Moreover, both maximum diversity and multiplexing gain can be achieved under certain conditions with respect to the number of elements in each sub-surface.

In this paper, we study the fundamental limits of a simultaneous wireless information and power transfer communication system, which is facilitated by an intelligent reflecting surface (IRS). Specifically, we propose a low-complexity optimization scheme that optimizes iteratively the input probability distribution at the transmitter side and the phase shift coefficient at the IRS to enhance the information-energy capacity region. By using alternating optimization and Lagrangian decomposition, analytical expressions for the optimal input distribution and the phase shifts are derived which decrease the computational complexity of the proposed scheme. A novel joint optimization scheme is also proposed inspired by the one in [1] for SWIPT systems. Numerical results show that the iterative optimization scheme almost achieves the same performance in comparison with the proposed joint optimization scheme while ensuring a reduced computation for high energy-harvesting thresholds.

Simultaneous wireless information and power transfer (SWIPT) is an emerging technology to connect and energize devices wirelessly, in the future Internet of Things (IoT) and wireless sensor networks (WSN). In this paper, we investigate two coherent detection schemes for integrated SWIPT receivers. At first, we examine a single input multiple output (SIMO) topology, with multiple rectennas at the receiver’s side, i.e. MRCA scheme. Targeting to reduce the decoding complexity, we further investigate a single input single output (SISO) topology, with one receive antenna connected to multiple rectifiers, i.e. MRCE scheme. A non-linear energy harvesting (EH) model, is considered for both schemes, by taking into account the sensitivity and saturation effects of rectifiers. With the use of maximum likelihood (ML) and soft decoding, energy detection is succeeded. An asymptotic analysis is conducted for both schemes, providing upper and lower bounds for EH and information decoding, respectively. Simulation and experimental results along with theoretical analysis, validate the enhanced performance of the proposed schemes.

This paper studies the performance of a differential chaos shift keying (DCSK)-based wireless power transfer (WPT) setup in a frequency selective scenario. Particularly, by taking into account the nonlinearities of the energy harvesting (EH) process and a generalized frequency selective Nakagami-m fading channel, we derive closed-form analytical expressions for the harvested energy in terms of the transmitted waveform and channel parameters. A simplified closed-form expression for the harvested energy is also obtained for a scenario, where the delay spread is negligible in comparison to the transmit symbol duration. Nontrivial design insights are provided, where it is shown how the power delay profile of the channel as well as the parameters of the transmitted waveform affect the EH performance. Our results show that a frequency selective channel is comparatively more beneficial for WPT compared to a flat fading scenario. However, a significant delay spread negatively impacts the energy transfer.

Amplitude detection (AD) is a low-complexity nonlinear scheme for information retrieval, as it only considers the envelope of the received signal. This makes it ideal in applications with low-cost low-power devices such as the Internet of Things (IoT). We consider a basic Point-to-Point (P2P) setup and develop a unified analytical framework for the asymptotic symbol error rate (SER) performance of the maximum-likelihood (ML) decoder with$M$-ary amplitude-shift keying (ASK). The developed framework is general and can be applied for a large class of fading channels. The SER can be characterized by two parameters: the diversity order and the coding gain at a sufficiently high signal-to-noise regime. We derive closed-form expressions for the exact diversity order along with a lower and upper bound on the coding gain. We show that the diversity order is equal to$m$for Nakagami-$m$fading, whereas for the other considered models, it is equal to one. We also prove that among all possible binary modulations with equal power, the modulation with one symbol equal to zero [i.e., on–off keying (OOK)] achieves the minimum asymptotic SER. The mathematical framework developed for the P2P setup is extended for cooperative relay networks. Specifically, we consider a basic amplify-and-forward (AF) three-node relay topology that employs AD at both the relay and the destination. We analytically derive the ML decoder and study asymptotic bounds on the SER by showing that the proposed AF-AD relay setup can be transformed into an equivalent P2P-AD with respect to the ML decoder.

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 article, 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 and the potentials from the proper development of SWIPT systems under health and safety restrictions.

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.

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 study the co-design of full-duplex (FD) radio with joint communication and radar sensing (JCAS) techniques in millimeter-wave (mmWave) heterogeneous networks (HetNets). Spectral co-existence of radar and communication systems causes mutual interference between the two systems, compromising both the data exchange and sensing capabilities. Focusing on the detection performance, we propose a cooperative detection technique, which exploits the sensing information from multiple base stations (BSs), aiming at enhancing the probability of successfully detecting an object. Three combining rules are considered, namely theOR, theMajorityand theANDrule. In real-world network scenarios, the locations of the BSs are spatially correlated, exhibiting a repulsive behavior. Therefore, we model the spatial distribution of the BSs as a$\beta$-Ginibre point process ($\beta$-GPP), which can characterize the repulsion among the BSs. By using stochastic geometry tools, analytical expressions for the detection performance of$\beta$-GPP-based FD-JCAS systems are expressed for each of the considered combining rule. Furthermore, by considering temporal interference correlation, we evaluate the probability of successfully detecting an object over two different time slots. Our results demonstrate that our proposed technique can significantly improve the detection performance when compared to the conventional non-cooperative technique.

In this paper, we carry out a performance analysis of a full-duplex (FD) relaying system consisting of parallel hybrid radio frequency (RF)/free-space optical (FSO) communication links. The RF links are hampered by the residual self-interference (RSI), due to the FD relaying operation, along with the in-phase and quadrature-phase imbalance (IQI) effect, due to imperfections at the RF nodes' front-ends. The parallel FSO links, of the dual-hop configuration, are influenced by the joint effects of atmospheric turbulence and pointing errors. The performance of the dual-hop FD system with parallel hybrid RF/FSO links, operating under a hard-switching scheme, is evaluated in terms of the outage probability. Analytical closed-form expressions are derived for both RF and FSO subsystems as well as for the overall dual-hop hybrid system. The presented numerical results show the significant performance gains obtained by the exploitation of parallel RF/FSO links in an FD relaying channel under various operating conditions. Finally, the derived analytical results are verified by Monte Carlo simulations.

In this work, we investigate differential chaos shift keying (DCSK), a communication-based waveform, in the context of wireless power transfer (WPT). Particularly, we present a DCSK-based WPT architecture, that employs an analog correlator at the receiver in order to boost the energy harvesting (EH) performance. By taking into ac-count the nonlinearities of the EH process, we derive closed-form analytical expressions for the peak-to-average-power-ratio of the received signal as well as the harvested power. Nontrivial design in-sights are provided, where it is shown how the parameters of the transmitted waveform affects the EH performance. Furthermore, it is demonstrated that the employment of a correlator at the receiver achieves significant EH gains in DCSK-based WPT systems.

LoRa networks have been deployed all over the world and are a major enabling wireless technology for the Internet of Things (IoT). Massive connectivity applications such as smart metering, agriculture, and supply chain & logistics are most suitable for LoRa deployments due to their long range, low cost, and low power features. Meanwhile, energy harvesting technologies that extract energy from ambient sources have enabled the battery-less operation of many small wireless sensors. This paper studies the merger of these two technologies and mathematically models device and network performance using tools from stochastic geometry and Markov analysis. To that end, we derive the steady-state distribution of the capacitor voltage, the outage probability due to co-spreading factor interference at the LoRa gateway, and propose adaptive charging time schemes in order to mitigate energy outage events.

Intelligent reflecting surfaces (IRSs) have the potential of increasing the coverage and energy efficiency of future wireless networks. In this paper, we study the performance of an IRS-aided network in the presence of blockages from a large-scale point-of-view, where multiple IRSs are randomly distributed. We model the blockages and IRSs with a line segment process and take into account the fading channels from both the direct and indirect links. The performance of a receiver is studied based on specific association policies, i.e. which IRS(s) should be activated to reflect the signal to the receiver. Specifically, we consider the association with a random IRS, the closest IRS or with all available IRSs in the cell. A complete analytical framework in terms of the outage probability is developed using tools from stochastic geometry. We show that each association policy has its advantages, which heavily depend on the network’s parameters such as the cell-radius, the number of IRS elements and the blockage density.

The rapid growth of the so-called Internet of Things is expected to significantly expand and support the deployment of resource-limited devices. Therefore, intelligent scheduling protocols and technologies such as wireless power transfer, are important for the efficient implementation of these massive low-powered networks. This paper studies the performance of a wireless powered communication network, where multiple batteryless devices harvest radio-frequency from a dedicated transmitter in order to communicate with a common information receiver (IR). We investigate several novel selection schemes, corresponding to different channel state information requirements and implementation complexities. In particular, each scheme schedules the$k$-th best device based on: a) the end-to-end (e2e) signal-to-noise ratio (SNR), b) the energy harvested at the devices, c) the uplink transmission to the IR, and d) the conventional/legacy max-min selection policy. We consider a non-linear energy harvesting (EH) model and derive analytical expressions for the outage probability of each selection scheme by using tools from high order statistics. Moreover, an asymptotic scenario in terms of the number of devices is considered and, by applying extreme value theory, the system’s performance is evaluated. We derive a complete analytical framework that provides useful insights for the design and realization of such networks.

The employment of intelligent reflecting surfaces (IRSs) is a potential and promising solution to increase the spectral and energy efficiency of wireless communication networks. Despite their many advantages, IRS-aided communications have limitations as they are subject to high propagation losses. To overcome this, the phase rotation (shift) at each element needs to be designed in such a way as to increase the channel gain at the destination. However, this increases the system's complexity as well as its power consumption. In this article, we present an analytical framework for the performance of random rotation-based IRS-aided communications. Under this framework, we propose four low-complexity and energy efficient schemes, based on a coding or a selection approach. Both of these approaches employ random phase rotations and require limited knowledge of channel state information. Specifically, the coding-based schemes use time-varying random phase rotations to produce an equivalent time-varying channel. On the other hand, the selection-based schemes select a partition of the IRS elements based on the received signal power at the destination. Analytical expressions for the achieved outage probability and energy efficiency of each scheme are derived. It is demonstrated that all schemes can provide significant performance gains as well as full diversity order.

In this paper, a cooperative protocol is investigated for a multi-hop network with buffers of finite size at the relay nodes. The protocol is based on the myopic decode-and-forward coding 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. A complete theoretical framework is investigated that models the evolution of the buffers as a state Markov chain (MC). We analyze the performance of the proposed protocol in terms of outage probability and diversity gain 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.

This paper studies the performance of a wireless powered communication network consisting of a finite number of batteryless devices that harvest radio frequency energy. We consider novel selection/scheduling schemes, where the k-th best device is selected for information transmission. The proposed schemes correspond to different complexity and are based on: a) the end-to-end (e2e) signal-to-noise ratio (SNR), b) the energy harvested at the devices, and c) the conventional channel-based max-min selection policy. By considering a non-linear energy harvesting (EH) model, we derive analytical expressions for the outage probability of each selection scheme by using high order statistics. We also consider an asymptotic scenario, where the number of devices increases and analyze the behavior of the system by applying extreme value theory. Due to the saturation effects of the non-linear EH model, the performance of all the proposed schemes converges to an error floor. Our results show that the scheme based on the e2e SNR achieves the best performance and the one based on the EH the worst. The derived analytical framework provides useful insights on the design of such networks.

On the brink of the internet of things (IoT) revolution, different low power wide area network (LPWAN) technologies are competing for market share and scalability. In this paper we leverage stochastic geometry tools to better understand how one should model the uplink wireless coverage in a multi-cell LoRa network while taking under consideration both the effects of co-spreading factor interference and the spatial diversity afforded by the LoRa network server. To that end, we propose a tractable model that captures these two system peculiarities and mathematically show that gateway densification has an overall positive effect on network coverage thus supporting the scalability of LoRa networks.

The employment of intelligent reflecting surfaces (IRSs) is a potential solution to increase the spectral and energy efficiency of wireless networks. The passive operation of their elements and the fact they can be deployed on any flat surface, makes them ideal for future wireless networks. However, the passive operation of their elements, incurs limitation on their capabilities. In this paper, we propose two low-complexity and energy efficient techniques for IRS-aided communications, namely, a coding-based and a selection-based scheme, both based on random phase rotations. In particular, the coding-based scheme uses time-varying random phase rotations to produce a time-varying channel. The selection-based scheme, selects and activates a partition of the IRS elements at each time slot based on the received signal power at the destination. Analytical expressions for both schemes are derived and the achieved performance gains are demonstrated. Furthermore, it is shown that both schemes provide full diversity order.

A vision of a digital and connected world is now a global strategy for 5G Internet of Things (IoT), targeting for high-speed communication services with more capacity, lower latency, increased reliability, and availability. In this article, we assess the added value of backscatter communication in 5G IoT technology, by studying spatial modulation (SM)-based techniques, applied over a traditional multiple antenna backscatter communication system. Particularly, with backscatter, we fulfill the need for wireless self-powered devices, as one of the main characteristics of 5G IoT. Furthermore, with the use of multiple antennas, we apply sophisticated techniques that enhance the overall efficiency of the backscatter communication system. Initially, we study generalized SM (GSM) and its special case of SM, exploiting the antenna index as an additional source of information. With this technique, enhanced performance in terms of symbol error rate (SER) and spectral efficiency, is provided. In addition, we expand GSM in the time domain, by applying the Alamouti coding scheme (GSMA) in two out of the multiple available antennas. In this way, we further enhance the performance and succeed transmit diversity. Finally, analytical expressions regarding the pairwise error probability are derived and presented, while a diversity analysis is carried out for the proposed techniques. The simulation results along with theoretical bounds are provided, validating the enhanced performance of our study.

Motivated by the demand of reliable and finite blocklength communications, we employ tools from information theory, stochastic processes and queueing theory, in order to provide a comprehensive framework regarding the analysis of a Time Division Multiple Access (TDMA) network with bursty traffic, in the finite blocklength regime. Specifically, we reexamine the stability conditions of a non-cooperative TDMA multiple access channel, evaluate the optimal throughput, and identify the optimal data packet size, k, for fixed codeword of blocklength, n. The evaluation is performed both numerically and via the proposed approximations, which result in closed form expressions and provide insight on how the optimal data size, k*, relates to the information metrics of channel capacity and channel dispersion in the finite blocklength regime. Then, we examine the stability conditions and the performance of the Multiple Access Relay Channel with TDMA scheduling, subject to finite blocklength constraints, by applying a cognitive cooperation protocol that assumes relaying is enabled when sources are idle. Finally, we propose the novel Batch-And-Forward (BAF) strategy, a mechanism that allows terminals to send batches of data packets instead on individual data packets, and evaluate the stability conditions and the optimal throughput. Numerical evaluation of the proposed strategy indicates that the performance of the cooperative network in the finite blocklength regime, in terms of throughput, can be significantly enhanced. Moreover, it reduces the requirement in control signals (metadata) [3], since, it avoids the unnecessary repetition of metadata (e.g. address of the source terminal and the destination). The BAF strategy is quite versatile, thus, it can be embedded in existing cooperative protocols, without imposing additional complexity on the overall scheme.

In this paper, we investigate the user association problem for mobile edge computation (MEC) offloading in non-orthogonal multiple access (NOMA) networks. According to NOMA, multiple users can access the MEC server to offload data simultaneously. However, resources are shared among the users which can potentially impact the required transmit power for offloading, thus increasing the total energy consumption. Aiming to minimize the overall energy consumption for all the users of the network, we formulate a problem where user association, optimal power allocation, data rate and offloaded data are jointly considered. More specifically, two coalition game algorithms are proposed and compared in an effort to efficiently reduce the total energy consumption. Simulation results show that both proposed algorithms can successfully reach a final state with low complexity, where the overall energy consumption is significantly reduced.

Ambient radio-frequency (RF) energy harvesting is a potential solution for charging low-powered devices, as a result of its cost effectiveness and pervasiveness. In this paper, we deal with devices which are underlaid in a wireless communication network and harvest energy from the ambient RF transmitted signals. The devices are equipped with an array of multiple rectifying antennas, combined either at the RF or the DC domain, to increase the harvesting efficiency. A large-scale analysis is undertaken, with the use of stochastic geometry. We take into account the non-linearities of the RF energy harvesting process and derive closed-form analytical expressions for the average harvested energy for both array architectures. Our results show the importance of considering non-linearities, mainly in terms of the network's density and the size of the rectifying antenna array but also for other network parameters.

Recent advances in information theory have provided a novel framework regarding finite blocklength analysis, which can be employed to address the current and future demands of communication networks. In this paper, we investigate the performance of the Time-Division Multiple-Access (TDMA) scheme with bursty traffic, subject to finite blocklength constraints. In contrast to previously reported work, where the analysis of such communication networks was performed under the infinite blocklength assumption, we develop a comprehensive framework that takes finite blocklength constraints into account. In particular, we employ the recent results in finite blocklength analysis, to prove necessary stability conditions for the overall system at the finite blocklength regime, and to identify the optimal trade-off between data length and channel blocklength. The later one is evaluated both numerically and via the proposed linear and quadratic approximations that result to closed form expressions.

This work provides a comprehensive framework regarding the analysis of the Multiple Access Relay Channel (MARC) with Time Division Multiple Access (TDMA) scheduling, subject to finite blocklength constraints. In particular, we examine the stability conditions and evaluate the maximum throughput, by applying a cognitive cooperation protocol that assumes relaying is enabled when sources are idle. Moreover, we propose the novel Batch-And-Forward (BAF) strategy, that can significantly enhance the performance of cooperative networks in the finite blocklength regime, as well as reduce the requirement in metadata. The BAF strategy is quite versatile, thus, it can be embedded in existing cooperative protocols, without imposing additional complexity on the overall scheme.

This paper studies the beneficial combination of wireless power transfer and millimeter-wave (mmWave) communications in wireless sensor networks. In particular, an mmWave wireless powered sensor network is considered, where the access point (AP) employs beamforming techniques to transfer energy to the sensors of a selected sector of the cell. The served sensors harvest and store energy from the received signal, and use it to power their uplink transmissions. We consider a random energy beamforming scheme but also propose several intelligent schemes that steer the beam to specific areas of the cell by considering the sensors' locations. This setup is investigated from a large-scale point-of-view where spatial randomness is considered with the aid of Poisson point processes. The performance of the network is described in terms of the energy outage probability and the beam outage probability. We show that, depending on the scenario, each of the considered energy beamforming schemes can provide significant gains to the network's performance. Finally, we study an event monitoring application of our theoretical framework, where the active sensors observe a random event in the network and the AP attempts to estimate it based on the received information; this scenario is evaluated in terms of the estimation's mean squared error.

We propose a new simultaneous wireless information and power transfer technique that embeds information bits in the tone index of multisine waveforms. By varying the number of subcarriers of the transmitted bandwidth-constrained multisine signal, the proposed scheme enables efficient radio-frequency energy harvesting and low-complexity information transmission. The receiver does not require channel estimation and employs a non-coherent maximum-likelihood detection at the envelope of the received signal. The performance of the proposed tone-index modulation is evaluated in terms of average error probability for a flat-fading channel, and we show that it outperforms its peak-to-average-power-ratio counterpart.

In this paper, we assess the effect of full-duplex (FD) radio in the context of millimeter-wave (mm-Wave) communications. Particularly, we propose an analytical framework, based on stochastic geometry, to evaluate the performance of heterogeneous FD-mm-Wave cellular networks for two user location-based classifications, namely cell-center users (CCUs) and cell-edge users (CEUs). Moreover, we evaluate the performance of the considered networks with successive interference cancellation (SIC) capabilities. Based on the proposed framework, analytical expressions for the coverage and sum-rate performance are derived. We investigate the impact of FD-mm-Wave communications on the network performance of CCUs/CEUs and quantify the associated performance gains under different network parameter settings. Our results demonstrate the beneficial combination of FD radio with heterogeneous mm-Wave cellular networks, since it increases the spectral efficiency but also alleviates the effects of the multi-user interference. Furthermore, we present the tradeoff between the coverage and sum-rate performance of heterogeneous FD-mm-Wave cellular networks for the considered user classifications. The results show that half-duplex mode is beneficial for the CEUs to achieve better network performance, as opposed to the CCUs for which FD mode is more efficient. Finally, we show the effectiveness of SIC on the network performance, with significant performance gains for the CEUs.

In this paper, we investigate non-coherent detection schemes, for the integrated simultaneous wireless information and power transfer (SWIPT) receiver. Firstly, we study a symbol by symbol (SBS) detection, while optimization of the transmitted energy pulses, enhances the performance of the receiver, in terms of symbol error rate (SER). In addition, by exploiting the channel coherence time, over N transmitted energy pulses, we study sequential detection and introduce an integrated SEQ-MLSD decoder. With the use of sophisticated techniques such as Viterbi-type trellis-search algorithm and strategic-store strategy, we simplify the complexity of the sequential detection and overcome the error floor problem. Simulation results along with theoretical bounds are provided, validating the enhanced performance of our solution. The proposed sequential decoding scheme outperforms in terms of SER, the integrated SBS decoder and the conventional power-splitting SWIPT receiver, without degrading the energy harvested.

In this paper, we assess the effect of full-duplex (FD) communications in the context of millimeter-wave (mmWave) cellular networks. The FD radio can potentially double the spectral efficiency but its performance is compromised by the existence of loop- and multi-user interference compared to half-duplex radio. Using stochastic geometry tools, we propose an analytical framework to evaluate the performance of FD-mmWave cellular networks for two location-based user classifications, namely cell-center users (CCUs) and cell-edge users (CEUs). Based on the proposed framework, analytical expressions for the downlink and the uplink coverage performance are derived for each user classification. We evaluate the impact of the FD radio on the performance of CCUs/CEUs and quantify the associated performance gains under different network parameter settings. Our results demonstrate the significant impact of the user's location on the network performance and the beneficial combination of FD radio with mmWaves, which provides significant gains, as it alleviates the effects of multi-user interference.

Handover and mobility management are important and critical aspects of future ultra-dense cellular networks. This paper proposes an intelligent handover technique, which reduces the handover rate without significant performance losses. Specifically, we investigate a user-centric handover scheme that exploits base station (BS) cooperation to enable a dynamic handover skipping. By considering mobility awareness, the users skip some handover executions and remain connected with at least a single BS. In this way, we achieve a balance between BS cooperative transmissions and single BS transmission to reduce handover rate and consequently the associated signal overhead. Our results show that the proposed scheme outperforms conventional solutions in terms of the average user throughput, particularly for high velocities and ultra-dense networks.

Relay selection is a simple yet effective means to improve the reliability and coverage of wireless cooperative networks. However, it suffers from inefficient use of the available bandwidth resources. This paper introduces the use of content caching at relays in order to tackle this problem and improve the performance of relay selection. Three cache placement schemes are considered: one based on the most popular files, a uniform based caching and a hybrid scheme of the two. We analytically derive their outage performance as well as their diversity order and coding gain. Numerical results demonstrate the substantial performance gains of these schemes over the traditional optimal relay selection approach without caching capabilities.

In this paper, we study the performance of next-generation cellular networks in the context of a low-complexity base station (BS) selection scheme. In contrast to existing BS cooperation approaches, where multiple BSs jointly transmit to the user, by using our proposed low-complexity technique, a user communicates with the BS that provides the maximum signal-to-interference-plus-noise-ratio from a set formed according to a pre-selection policy. We consider three pre-selection policies based on: 1) the Euclidean distance; 2) the averaged received power; and 3) a random selection. Moreover, we consider the case where the users have the ability to employ the successive interference cancellation (SIC) scheme. Despite its high computational complexity, SIC can potentially decode and remove strong interfering signals from the aggregate received signal, which can significantly boost the user's performance. By using stochastic geometry tools, analytical expressions for the coverage performance are derived for each policy, by taking into account spatial randomness and blockage effects. Our proposed technique provides low computational and implementation complexity due to the two-level selection scheme. Furthermore, we show that our proposed scheme does not lose in diversity compared with existing cooperation techniques and that all policies can benefit by the employment of the SIC scheme.

In this paper, we consider two fundamental full-duplex (FD) architectures, two-node and three-node, in the context of cellular networks where the terminals employ directional antennas. The simultaneous transmission and reception of data in non-orthogonal channels makes FD radio a potential solution for the currently limited spectrum. However, its implementation generates high levels of interference either in the form of loopback interference (LI) from the output to the input antenna of a transceiver or in the form of co-channel interference in large-scale multicell networks due to the large number of active links. Using a stochastic geometry model, we investigate how directional antennas can control and mitigate the co-channel interference. Furthermore, we provide a model which characterizes the way directional antennas manage the LI in order to passively suppress it. Our results show that both architectures can benefit significantly by the employment of directional antennas. Finally, we consider the case where both architectures are employed in the network and derive the optimal values for the density fraction of each architecture, which maximize the success probability and the network throughput.

In this paper, we study the problem of base station (BS) cooperation in millimeter wave multi- tier heterogeneous cellular networks. In contrast to conventional approaches, where a number of BSs jointly transmit data to a user, we investigate a low-complexity technique that enables the selection of a single BS for transmission. Specifically, a single BS that provides the highest instantaneous signal-to-interference-plus- noise ratio is selected, among the strongest BSs from each tier. By using stochastic geometry tools, we derive closed-form expressions for the coverage probability and the diversity gain of the system by taking into account spatial randomness and blockage effects. Our results show that the proposed scheme achieves full diversity and is appropriate for networks with strict computation constraints. In addition, we study the case where users employ successive interference cancellation (SIC) to further boost the achieved performance; SIC allows the mitigation of strong interference terms from the received signal. The impact of SIC on the coverage probability of the system is studied and closed-form expressions are provided.

In the opportunistic beamforming (OBF) scheme, the access point (AP) acquires channel related feedback from the network's terminals and allocates the orthonormal beams to the users with the best link. This paper investigates the OBF scheme in a wireless powered communication network, where multi-antenna terminals with wireless power harvesting capabilities are randomly deployed around the AP. In this context, the terminals adapt the length of their feedback based on the power harvested with the use of rectenna arrays. We study two fundamental architectures for the combination of the rectenna elements, the direct-current combiner and the radio-frequency combiner, as well as a hybrid architecture of these two. By using higher order statistics and stochastic geometry, the beam outage probability is derived in closed form for all considered architectures.

Motivated by the effects of buildings/obstacles on the performance of high frequency cellular networks, this paper deals with the base station (BS) cooperation in heterogeneous cellular networks with blockages. Our main focus is a joint transmission scenario, where an ideal backhaul network allows a set of randomly located BSs belonging to different network tiers, to cooperate and jointly transmit data. By using concepts from random shape theory, we model the spatial randomness as well as the main characteristics of the blockages (e.g., size, orientation, etc). The outage probability performance of the system is analyzed for two low complexity transmission techniques with different channel state information requirements by using stochastic geometry tools. Our results show that the spatial diversity associated with the BS cooperation is an efficient technique to overcome the degradation effects of blockages and ensure connectivity.

The implementation of full-duplex (FD) radio in wireless communications is a potential approach for achieving higher spectral efficiency. A possible application is its employment in the next generation of cellular networks. However, the performance of large-scale FD multiuser networks is an area mostly unexplored. Most of the related work focuses on the performance analysis of small-scale networks or on loop interference cancellation schemes. In this paper, we derive the outage probability performance of large-scale FD cellular networks in the context of two architectures: two-node and three-node. We show how the performance is affected with respect to the model's parameters and provide a comparison between the two architectures.

Recent years have shown a promising progress in understanding geometric underpinnings behind the structure, function, and dynamics of many complex networks in nature and society. However, these promises cannot be readily fulfilled and lead to important practical applications, without a simple, reliable, and fast network mapping method to infer the latent geometric coordinates of nodes in a real network. Here, we present HyperMap, a simple method to map a given real network to its hyperbolic space. The method utilizes a recent geometric theory of complex networks modeled as random geometric graphs in hyperbolic spaces. The method replays the network's geometric growth, estimating at each time-step the hyperbolic coordinates of new nodes in a growing network by maximizing the likelihood of the network snapshot in the model. We apply HyperMap to the Autonomous Systems (AS) Internet and find that: 1) the method produces meaningful results, identifying soft communities of ASs belonging to the same geographic region; 2) the method has a remarkable predictive power: Using the resulting map, we can predict missing links in the Internet with high precision, outperforming popular existing methods; and 3) the resulting map is highly navigable, meaning that a vast majority of greedy geometric routing paths are successful and low-stretch. Even though the method is not without limitations, and is open for improvement, it occupies a unique attractive position in the space of tradeoffs between simplicity, accuracy, and computational complexity.

This paper studies the beamforming design of a multiple-input single-output system with eavesdropping, when a quantized channel feedback is available. We consider two basic cases a) the beamforming vector belongs to the quantization codebook and b) the beamforming design is not limited to the quantization codebook. For the first case, we design two beamforming schemes that incorporate a feedback channel from the eavesdropper, which provides the direction of its physical channel or the direction of its null-space. For the case where the codebook constraint is relaxed, we design an optimal beamformer that requires feedback from both receivers as well as a scheme that transmits towards the quantized null-space of the eavesdropper's channel. The ergodic secrecy rate is derived in closed-form and we show that all schemes suffer from a secrecy rate floor for a constant-size feedback. Simplified asymptotic expressions are proposed and the scaling laws of the feedback, which ensure constant secrecy losses, are provided.