Amplify-and-forward Relay Research Articles

Unscented-Kalman-Filter-Based Remote State Estimation for Complex Networks With Quantized Measurements and Amplify-and-Forward Relays.

In this article, the remote estimation problem is addressed for a class of discrete-time complex networks under the influence of probabilistic quantization and amplify-and-forward (AF) relays. The underlying complex network model, which is inherently nonlinear and stochastic, is affected by additive process and measurement noises. Owing to the limited bandwidth of the transmission channel, the measurement outputs are quantized by a probabilistic quantizer prior to transmission. To enhance the signal quality over long-distance transmissions, the quantized measurements are sent to AF relays and subsequently forwarded to the estimator. Utilizing the unscented Kalman filter approach, a novel state estimator is designed to minimize an upper bound on the estimation error covariance. Moreover, sufficient conditions are derived to ensure that the estimation error is exponentially bounded in the mean-square sense. Lastly, the efficacy of the proposed scheme is illustrated through numerical simulations.

Secure performance comparison for NOMA: Reconfigurable intelligent surface or amplify-and-forward relay?

The amplify-and-forward (AF) relay is widely employed owing to its simplicity, while reconfigurable intelligent surface (RIS) technology is envisioned as the next generation of relay technology due to its high energy efficiency. This paper compares these two technologies at the physical layer security (PLS) level for non-orthogonal multiple access (NOMA) with an internal near-end eavesdropper. Specifically, for a fair comparison, both the number of RIS elements and AF relay antennas are set to N, and similar secure transport strategies are utilized for both models to maximize the secrecy rate. Analytical results demonstrate that the PLS performance of RIS-assisted NOMA is better than that of AF relay-assisted NOMA if N reaches a certain threshold. Simulation results verify the correctness of the theoretical analysis.

Optimizing energy harvesting with diversity in cooperative simultaneous wireless information and power transfer systems

SummaryRadio frequency (RF) energy harvesting (EH) for wireless networks provides a green and sustainable solution and offers an energy‐efficient system. It is most crucial for fulfilling the power requirement of the rising number of low‐powered wireless devices and achieving sustainable development goals (SDG). It ensures the longevity of devices in the network even at inaccessible remote locations. Such RF‐EH‐based mechanisms are utilized in simultaneous wireless information and power transfer (SWIPT) systems. Most of the prevailing studies have analyzed the SWIPT system over conventional fading channels. However, due to the higher rate requirements, the current paradigm shift in frequency usage shifts towards the GHz band, which also offers better EH efficiency. Hence, SWIPT system analysis over the channel that is suitable for mm‐wave signal propagation is dealt with in this study. This study evaluates SWIPT performance over fluctuating two‐ray (FTR) fading channel that is crucial since it provides the best fit for characterizing GHz signal and also provides a generalized framework for most of the conventional fading channels. This study presents new analytical results assuming time switch relaying (TSR) protocol with (i) amplify and forward (AF) and (ii) decode and forward (DF) relaying. The results are also analyzed for H branches maximal ratio combining (MRC) diversity technique and evaluated the diversity gain for both AF and DF relays. The effectiveness of the system is measured in terms of system outage probability (SOP) to envisage the reliability of SWIPT based system. This work presents the simulation and modeling of such system and its obtained results are validated by Monte Carlo simulations for their accuracy.

Joint Hybrid Beamforming Design for Millimeter Wave Amplify-and-Forward Relay Communication Systems

Hybrid beamforming (HBF) has been regarded as one of the most promising technologies in millimeter Wave (mmWave) communication systems. In order to guarantee the communication quality in non-line-of-sight (NLOS) scenarios, joint HBF design for the mmWave amplify-and-forward (AF) relay communication system is studied in this paper. The ideal case is first considered where the mmWave half-duplex (HD) AF relay system operates with channel state information (CSI) accurately known. In order to tackle the non-convex problem, a manifold optimization (MO)-based alternating optimization algorithm is proposed, where an optimization problem containing only constant modulus constraints in Euclidean space can be converted to an unconstrained optimization problem in a Riemann manifold. Furthermore, considering more practical cases with estimation errors of CSI, we investigate the robust joint HBF design with the system operating in full-duplex (FD) mode to obtain higher spectral efficiency (SE). A null-space projection (NP) based self-interference cancellation (SIC) algorithm is developed to attenuate the self-interference (SI). Different from the traditional SI suppression algorithm, there’s no limit on the number of RF chains. Numerical results reveal that our proposed algorithms has a good convergence and can effectively deal with the influence of different CSI estimation errors. A significant performance improvement can be achieved in contrast with other approaches.

Optimized Distributed Filtering for Saturated Systems With Amplify-and-Forward Relays Over Sensor Networks: A Dynamic Event-Triggered Approach.

In this article, the optimized distributed filtering problem is studied for a class of saturated systems with amplify-and-forward (AF) relays via a dynamic event-triggered mechanism (DETM). The AF relays are located in the channels between sensors and filters to prolong the transmission distance of signals, where the transmission powers of sensors and relays can be described by a sequence of random variables with a known probability distribution. With the purpose of alleviating the communication burden and preventing data collision, the DETM is used to schedule the transmission cases of nodes by dynamically adjusting the triggered threshold according to the practical requirements. An upper bound matrix (UBM) of the filtering error (FE) covariance is first provided under the sense of variance constraint and the proper filter gain is further constructed via minimizing the proposed UBM. In addition, the boundedness evaluation regarding the trace of the UBM is provided. Finally, simulation experiments are used to illustrate the usefulness of the developed distributed recursive filtering scheme.

Token-Bucket-Protocol-Based Recursive Remote State Estimation for Complex Networks Under Amplify-and-Forward Relays.

This article is concerned with a recursive remote estimation problem for a class of nonlinear complex networks subject to the token bucket protocol (TBP) and amplify-and-forward (AF) relays. The influence of the TBP is considered, for the first time, in the context of networked state estimation, where the token consumptions are modeled in a stochastic manner, so as to describe the potential size variability of transmitted measurement signals. Once processed by the TBP, the signals, with stochastic channel coefficients, are transmitted to the remote estimator via AF relays, where a failure in transmission under the TBP may occur due to insufficient tokens in the bucket. An extended-Kalman-filter-based novel recursive estimator is proposed, and by solving Riccati-like difference equations, an upper bound of prediction/estimation error covariance is determined and further minimized through the design of an appropriate estimator gain. The impact of the TBP on estimation performance is also investigated. Some numerical simulations are presented to demonstrate the effectiveness of the proposed estimator and the effects of the TBP.

Performance Comparison of Relay-Based Covert Communications: DF, CF and AF.

In this paper, we investigate the performance of covert communications in different types of a relay system: decode-and-forward (DF), compress-and-forward (CF) and amplify-and-forward (AF). We consider a source node that attempts to send both public and covert messages to a destination node through a relay on which a covert message detector is embedded. By taking the minimum detection error probability (DEP) at the relay into account, we optimize the power distribution between the public and covert messages to achieve the maximum covert rate. We further make a delay-aware comparison among DF, CF and AF relay systems with the obtained closed-form covert rates and conduct an extensive examination on the asymptotic behaviors in different limits. Our analyses reveal that CF or AF tend to outperform DF for high source transmit power or low relay transmit power, while various system parameters such as the processing delay, minimum required quality of service for public messages and DEP threshold lead to different performance relationships among DF, CF and AF for high relay transmit power. Numerical results verify our investigation into the performance comparison in various channel models.

Dynamic output-feedback model predictive control for polytopic uncertain systems with amplify-and-forward relays

In this paper, the dynamic output-feedback model predictive control (MPC) problem is investigated for systems with polytopic uncertainties and amplify-and-forward (AF) relays, where the signal transmission with random power is adopted to facilitate the remote transmission with the limited transmission capacity of sensors. With respect to the parameter uncertainties of the system and the randomness of AF relays, a new objective function is constructed, which is defined by the mathematical expectation of the conventional quadratic function over the infinite time horizon. Then, the singular value decomposition technique is applied to handle the inherent couplings of variables to formulate a solvable optimization problem. Furthermore, sufficient conditions are provided to guarantee the recursive feasibility of the proposed MPC algorithm, meanwhile the underlying system can be stabilized in the mean-square sense by the designed controllers. Finally, two simulation examples are used to show the effectiveness of the proposed MPC strategy.

Recursive state estimation for a class of quantized coupled complex networks subject to missing measurements and amplify-and-forward relay

This paper investigates the algorithm design problem of recursive state estimation (RSE) for a class of complex networks (CNs) subject to quantized coupled parameter, missing measurements (MMs) and amplify-and-forward (AF) relay. In the node-to-node network channels, the signals before entering into the communication networks are quantized. In addition, a series of Bernoulli random variables is employed to model the phenomenon of MMs and an AF relay is deployed in the sensor-to-estimator network channels with the purpose of achieving the task of remote data transmission. A recursive state estimator is constructed such that, for all quantized coupled signal, MMs and AF relay, a state estimation error covariance (SEEC) upper bound (SEECUB) is presented and then the estimator gain (EG) is parameterized by optimizing the trace of SEECUB. Subsequently, a rigorous theoretical analysis is given to establish the monotonicity relationship between the trace of the minimized SEECUB and the probabilities of MMs. Finally, a simulation study is carried out for the proposed RSE approach to demonstrate the feasibility and validity of such state estimation strategy.

Joint Transceiver Design for Dual-Functional Full-Duplex Relay Aided Radar-Communication Systems

Driven by the demand for massive and accurate sensing data to achieve wireless network intelligence under a limited available spectrum, the coexistence between radar and communication systems has attracted public attention. In this paper, we investigate a novel dual-functional full-duplex relay aided radar-communication system where the phased-array radar is employed at the amplify-and-forward (AF) relay. A joint transceiver design is proposed to maximize the minimum signal-to-interference-plus-noise ratio (SINR) among all detection directions at the radar receiver under communication quality-of-service and total energy constraints. The formulated optimization problem is particularly challenging due to the highly nonconvex objective function and constraints. Based on the problem structure, we equivalently decompose it into the radar-energy and relay-energy minimization problems under SINR requirements. To solve the radar-energy minimization problem, we propose a low-complexity algorithm based on the alternating direction method of multipliers to optimize the radar transmit power and receiver. The relay-energy minimization problem can be simplified into an equivalent quadratic programming problem by introducing an insightful unitary matrix. Then, the closed-form expression for the AF relay beamforming matrix can be derived, which is jointly determined by the channel condition of relay communication and the detection direction of the radar. After that, we introduce the overall transceiver design algorithm to the original problem and discuss its optimality and computational complexity. Simulation results verify that the proposed algorithm significantly outperforms other benchmark algorithms.

Energy efficient air-to-ground communication networks with reconfigurable intelligent surface

Reconfigurable intelligent surface (RIS) assisted air-to-ground wireless powered communication networks (WPCNs) are constructed to promote the energy efficiency of the system, in which unmanned aerial vehicles (UAV) reflects energy towards the energy-constrained hybrid access points (HAP) through RIS. Subsequently, HAP uses the collected energy to communicate with users in blind areas through the RIS-UAV. By optimizing parameters such as charging time ratio, transmit power and phase shifts matrix, the energy efficiency for single and multiuser scenarios are maximized, respectively. The energy efficiency is modeled as a non-convex quadratic programming problem with inequality constraints in the single-user scenario. Then the problem is converted into an equivalent convex problem by using the Taylor expansion and convex approximation method. A joint optimization algorithm of power and phase shifts is proposed to obtain a feasible solution. The energy efficiency is modeled as a fractional programming problem with non-convex inequality constraints in the multi-user scenario, and the feasible solution is obtained by proposing an alternating algorithm. Finally, both two scenarios are compared with the system of traditional amplify-and-forward (AF) relay, respectively. Finally, the simulation results show that the proposed algorithms can provide up with 150% and 160% improvement of the energy efficiency in the single and multi-user scenarios, respectively, compared to the traditional AF relay.

Capacity and outage performance of multiple AF relays based cooperative OFDM-QIM system

In this paper, we propose a multiple amplify-and-forward (AF) relays based cooperative orthogonal frequency division multiplexing (OFDM) with quadrature index modulation (C-OFDM-QIM) system to enhance the spectral efficiency and the transmission reliability, where two independent subcarrier subsets are activated to convey the real and imaginary symbol vectors, respectively, and the per-subcarrier relay selection (RS) scheme is adopted to select the relay with the maximum end-to-end signal-to-noise ratio (SNR) for each active subcarrier. Both fixed-gain AF and variable-gain AF protocols are investigated at the selected relays. Based on the order statistics and the max-flow min-cut theory, the closed-form average outage probability (AOP) and the average capacity are derived, respectively. Numerical results demonstrate that the theoretical AOP is correct and accurate and the proposed C-OFDM-QIM system outperforms the traditional cooperative OFDM with index modulation (C-OFDM-IM) system in the spectral efficiency, the outage performance, and the average capacity.

Energy Efficiency for Proactive Eavesdropping in Cooperative Cognitive Radio Networks

This article investigates a distant proactive eavesdropping system in cooperative cognitive radio (CR) networks. Specifically, an amplify-and-forward (AF) full-duplex (FD) secondary transmitter assists to relay the received signal from suspicious users to legitimate monitor for wireless information surveillance. In return, the secondary transmitter is granted to share the spectrum belonging to the suspicious users for its own information transmission. To improve the eavesdropping, the transmitted secondary user’s (SU) signal can also be used as a jamming signal to moderate the data rate of the suspicious link. We consider two cases, i.e., nonnegligible processing delay (NNPD) and negligible processing delay (NPD) at the secondary transmitter. Our target is to maximize network energy efficiency (NEE) via jointly optimizing the AF relay matrix and precoding vector at the secondary transmitter, as well as the receiver combining vector at the monitor, subject to the maximum power constraint at the secondary transmitter and minimum data rate requirement of the SU. We also guarantee that the achievable data rate of the eavesdropping link should be no less than that of the suspicious link for efficient surveillance. Due to the nonconvexity of the formulated NEE maximization problem, we develop an efficient path-following algorithm and a robust alternating optimization (AO) method as solutions under perfect and imperfect channel state information (CSI) conditions, respectively. We also analyze the convergence and computational complexity of the proposed schemes. Numerical results are provided to validate the effectiveness of our proposed schemes.

Performance Analysis of Mixed Rayleigh and F Distribution RF-FSO Cooperative Systems with AF Relaying

This paper proposes a dual-hop mixed radio frequency-free-space optical (RF-FSO) cooperative system with amplify-and-forward (AF) relaying. The RF link is subject to Rayleigh fading and the FSO link is assumed to follow F-distributed fading with pointing error. The different types of detection, including intensity modulation with direct detection (IM/DD) and coherent heterodyne detection (HD), are considered. The closed-form expressions for the cumulative distribution function (CDF), the moment generating function (MGF), and the moments of end-to-end signal-to-noise ratio (SNR) are derived. Furthermore, closed-form expressions for the outage probability, average bit error rate (BER), and ergodic capacity are presented. Asymptotic outage probability expressions are derived to obtain additional insights into the system performance. It is shown that the HD technique exhibits better performance than an IM/DD technique. The system performance is deteriorated by atmospheric turbulence and pointing error. Finally, analytical results are confirmed by Monte Carlo simulations.

Age of information and energy efficiency of amplify‐and‐forward relay‐assisted Internet of Things with nonlinear energy harvesting and imperfect channel state information over Nakagami‐ fading channels

AbstractThe emergence of the fifth generation of communication networks (5G) has paved the way for the fast development of Internet of Things (IoT) as well as many real‐time and mission‐critical applications. Because the status update required to be as timely as possible, a new metric termed as age of information (AoI) was born with the ability of capturing the timeliness. However, in practical implementation the sensor is energy constrained and transmits very low‐power signals, which yield high AoI so that the received status update can be stale or even outdated. To overcome this problem, this work proposes an IoT system model by integrating energy harvesting (EH), amplify‐and‐forward (AF) relay cooperation, and short packet communication (SPC) techniques. In the proposed scheme, the relay that is connected to fixed power grid, transfers energy radio frequency signals to charge the sensor and assists forwarding status update by using time switching scheme. The employment of SPC overcomes the freshness loss caused by relay cooperation and EH. Then, this work investigates the AoI and energy efficiency of the proposed scheme under finite block length communications over Nakagami‐ fading channels by specially considering channel state information (CSI) and nonlinear EH model. Under these practical constraints, the tractable AF relay transmission model and the end‐to‐end approximated signal‐to‐noise ratio are found. The end‐to‐end block error probability of finite block length transmission is derived, too. Third, under the simultaneous consideration of nonlinear EH and outdated CSI, the statistical descriptions of the time duration for the sensor fully charging its battery are derived as well as the ones of the time intervals of update packet delivery. As a result, the average AoI is achieved with closed‐form expression and the tradeoff model of AoI to energy efficiency is established by simultaneously exploiting outdated CSIs and nonlinearity of EH circuit. The presented numerical analysis exploits the impact of the outdated CSIs and nonlinear EH model and gives the insights of such model.

A Novel Average Autoencoder-Based Amplify-and-Forward Relay Networks With Hardware Impairments

In this paper, we propose a novel Average autoencoder (AE)-based amplify-and-forward (AF) relay networks impacted by the I/Q imbalance (IQI) and additional hardware impairments (AHI), where the source and destination nodes are equipped with neural network (NN)-based encoder and decoder, while a conventional AF relay node assists the transmission. The average AE employs multiple small NN-based decoders at the destination node, each decoding a soft probabilistic output that is averaged to obtain the final soft probabilistic output at the destination node. By considering multiple small NN decoders, we reduce the implementation complexity significantly while improving the performance compared to the AE with a single large but NN-based decoder. Within this Average AE framework, we propose a coded modulation design (CMD) with zero-forcing-based IQI compensation that considers the availability of the channel state information (CSI) and IQI knowledge. However, the IQI and CSI need to be estimated separately. Thus, we also propose a CMD with no IQI compensation that requires only the CSI knowledge. Finally, we propose a differential CMD that removes the necessity of both the CSI and IQI knowledge. Under low signal-to-interference-and-noise-ratio regimes, we show that the proposed Average AE outperforms the optimal maximum likelihood detector by considerable margin.

Joint Optimization for Multi-Antenna AF-Relay Aided Over-the-Air Computation

Benefiting from exploiting the waveform superposition property in the multi-access channels, over-the-air computation (AirComp) has emerged as a promising technique to swiftly compute functions of data from a large number of sensors. To enlarge the wireless coverage area, a two-phase multi-antenna amplify-and-forward (AF)-relay aided AirComp system is considered, where all the sensors transmit sensing data during both two phases in a half-duplex AF relay system with direct links. We present efficient designs for optimizing the transmit scalar vectors at the sensors, the AF matrix at the relay, and the aggregation vector at the access point, which aims to minimize the mean-square-error (MSE) subject to the transmit power budgets at the relay and the sensors, respectively. To solve the resultant multiple variables coupled non-convex optimization problem efficiently, we develop an alternating optimization-based algorithm to obtain locally optimal solutions. Specifically, in each iteration, closed-form expressions are derived for each optimizing variable. Finally, the computation distortion improvement of our proposed design over baseline schemes is demonstrated via simulations.

Characterization of mmWave X‐duplex multi‐relay system in 5G mobile network

SummaryIn this paper, we propose a millimeter wave (mmWave) X‐duplex (XD) amplify‐and‐forward (AF) multirelay system for 5G and beyond. Each XD AF relay is equipped with a shared antenna for both transmission and reception radio frequency (RF) chains. Also, the performance of mmWave XD AF multirelay system is analyzed, and a relay selection method in this scenario is suggested, where the best relay and the best operation mode are selected based on maximum end‐to‐end signal‐to‐interference‐plus‐noise ratio (SINR). XD relays can switch adaptively between half‐duplex (HD) and full‐duplex (FD) operation modes. As a practical channel model, Rician fading, path loss with line‐of‐sight (LOS) and non‐line‐of‐sight (NLOS) propagation, and blockage effects are considered for mmWave channel model in both source–relay and relay–destination links. We derive closed‐form expressions for end‐to‐end SINR and its distribution, outage probability, energy efficiency (EE), rate, and average symbol error rate (SER) based on the relay selection method. Monte Carlo simulations are performed to validate our analytical derivations, and also, the simulation results depict that XD relays outperform both HD and FD operation modes in terms of outage probability, EE, SER, and rate. Furthermore, the effects of self‐interference (SI) cancellation, blockage, and number of XD AF relays over the performance and also the comparison of XD relay selection to different existing relay selection policies are presented. In addition, it is shown that the XD relay selection method in our proposed system eliminates the performance floor of the FD caused by the residual SI that it is considered as a significant advantage of our proposed system.

Energy Efficiency Analysis in Modified GoF Spectrum Sensing-Based AF Relay Cooperative Cognitive Sensor Network with Energy Harvesting

In this paper, we propose a joint sensing duration and transmission power allocation scheme to maximize the energy efficiency (EE) of the secondary user (SU) in a cooperative cognitive sensor network (CSN). At the initial time slot of the frame, the secondary transmitter (ST) performs energy harvesting (EH) and spectrum sensing simultaneously using power splitting (PS) protocol. The modified goodness of fit (GoF) spectrum sensing algorithm is employed to detect the licensed spectrum, which is not sensitive to an inaccurate noise power estimate. Based on the imperfect sensing results, the ST will act as an amplify-and-forward (AF) relay and assist in transmission of the primary user (PU) or transmit its own data. The SU’s EE maximization problem is constructed under the constraints of meeting energy causality, sensing reliability, and PU’s quality of service (QoS) requirement. Since the SU’s EE function is a nonconvex problem and difficult to solve, we transform the original problem into a tractable convex one with the aid of Dinkelbach’s method and convex optimization technique by applying a nonlinear fractional programming. The closed-form expression of the ST’s transmission power is also derived through Karush-Kuhn-Tucker (KKT) and gradient method. Simulation results show that our scheme is superior to the existing schemes.

High speed integrated RF–VLC data communication system: Performance constraints and capacity considerations

In this research paper, we propose a two-hop integrated radio frequency–visible light communication (RF–VLC) system which may provide a better option to transceive between the hospitals and some laboratory to transfer patient’s information. In the proposed system model, the data (such as patient’s lab test reports) is transmitted towards the amplify and forward (AF) relay mounted on the top of the hospital building via the RF channel. Further, the AF relay amplifies and converts the received information into corresponding optical signal using light emitting diodes (LED) and supporting circuitry. This optical signal is then forwarded towards the destination device (equipped with VLC transceiver), via the VLC channel. To analyse the performance of the system, we first derive the closed form analytical expressions for the cumulative distribution function (CDF) of the end-to-end (e2e) signal to noise ratio (SNR) of the system by using the moment generating function (MGF) of the SNR of the individual RF and VLC channels. Further, we use these statistical expressions to obtain the outage probability, average bit error rate (BER) and the average capacity of the system. Moreover, the asymptotic performance of the proposed system is also analysed to study the system’s behaviour at high SNR regimes. Finally, we studied the impact of the variations in channel parameters on the proposed system model performance through numerically simulated plots.