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Federated learning (FL) has recently emerged as an important and promising learning scheme in IoT, enabling devices to jointly learn a model without sharing their raw data sets. As FL does not collect and store the data centrally, it requires frequent model exchange through the wireless network. However, since the aggregation in FL can be partially participated with synchronized frequency, its communication pattern is different from the conventional network. Therein, limited bandwidth and package loss restrict interactions in training. Thus, the network scheduling could largely affect the FL convergence. To figure out the specific effects, we analyze the convergence rate of FL regarding the joint impact of communication and training. Combining it with the network model, we formulate the optimal scheduling problem for FL implementation. The theoretical results could guide the hyper-parameter design in the network and explain the principle of how the wireless communication could influence the FL training process. [ABSTRACT FROM AUTHOR]

A UAV-aided wireless power transfer and data collection network is studied, where it is assumed that when the harvested energy at the sensor node (SN) cannot surpass its circuit activation threshold or the received data rate at UAV falls below a minimal required rate threshold, the information outage occurs. The closed-form expressions of energy outage probability and rate outage probability are derived at first, and then the overall outage probability and coverage performance of the system are analyzed. Based on which, an optimization problem is formulated to minimize the overall outage probability by optimizing UAV’s elevation angle and the time splitting (TS) factor. Since the problem is non-convex and has no known solution, an alternating optimization (AO)-based algorithm with Golden-section (GS) based linear search method is designed to find the global optimal solution. In order to explore the maximum coverage area of the UAV for a given tolerable outage probability, another optimization problem is also formulated to maximize the coverage range by optimizing UAV’s elevation angle. By using Karush-Kuhn-Tucker (KKT) conditions, the closed-form solution of the optimal elevation angle for maximizing the coverage area is derived. Monte Carlo simulations verify the accuracy of the derived closed-form expression of the overall outage probability and the semi-closed-form expressions of the optimum UAV’s elevation angle and TS factor. It shows that there exist a unique optimum elevation angle and the TS factor to achieve the minimum overall outage probability, and significant performance gain can be obtained by using our proposed optimization scheme. The developed theoretical results can be useful to the design of UAV-aided wireless communication systems with wireless power transfer. [ABSTRACT FROM AUTHOR]

This paper investigates a multi-node wireless powered communication network (WPCN), where a hybrid access point (HAP) first charges an Internet of Thing (IoT) device wirelessly with the assistance of multiple selfish wireless nodes (WNs), and then the IoT device uses the harvested energy to transmit real-time status updates to the HAP. Two incentive schemes, i.e., the energy-incentive scheme and the price-incentive scheme, are designed to overcome the selfishness of the WNs and enhance the per-packet AoI performance. For the energy-incentive scheme, an AoI-energy utility function is defined and an optimization problem is formulated to maximize the AoI-energy utility value of the HAP-IoT device pair. By using equality constraint elimination and Lagrangian method, the problem is solved and some closed-form solutions are derived to obtain the optimal solution. For the price-incentive scheme, an AoI-price utility function is defined and a Stackelberg game is established to maximize the utility of the HAP-IoT device pair. By using function transformation and Lagrange method, some semi-closed-form solutions are derived to maximize their own profits of the HAP and WNs in a distributed way. Numerical results show that our proposed two incentive mechanisms are able to achieve higher network utility values than the benchmark scheme. The more the number of WNs, the lower the AoI of each status update packet and the higher utility value of the HAP. It also shows that by positioning WNs closer to the IoT device, the better per-packet AoI performance can be achieved by both incentive mechanisms. Additionally, for the energy-incentive mechanism, its achieved AoI gain and energy gain decrease with the increment of the distance between the HAP and the IoT device. But for the price-incentive mechanism, the opposite phenomenon is observed. [ABSTRACT FROM AUTHOR]

This paper studies the information-energy ($\mathrm{I}$ - $\mathrm{E}$) region for simultaneous wireless information and power transfer (SWIPT) networks in mobility scenarios, where a moving transmitter simultaneously transmits information and power to a fixed receiver, and the receiver adopts power splitting (PS) receiving architecture. In order to characterize the tradeoff between the received information and harvested energy, the $\mathrm{I}$ - $\mathrm{E}$ region is defined, and corresponding optimization problems are formulated to explore the system $\mathrm{I}$ - $\mathrm{E}$ regions by jointly optimizing the transmit power at the transmitter and the PS ratio at the receiver with three popular energy harvesting (EH) models, i.e., traditional linear EH model, the logistic nonlinear EH model and the piecewise nonlinear EH model. Particularly, to efficiently solve the nonconvex optimization problem with the logistic nonlinear EH model, a successive convex approximate (SCA)-based algorithm is proposed, which is able to characterize the lower bound of the $\mathrm{I}$ - $\mathrm{E}$ with low complexity. To solve the optimization problems with the linear and piecewise EH models, as they are convex, some closed and semi-closed solutions are derived by using Lagrange dual method and KKT conditions. Numerical results show that compared with the $\mathrm{I}$ - $\mathrm{E}$ regions under the linear and piecewise EH models, that under the logistic nonlinear EH model is smaller due to the limitations of practical EH circuit features. Moreover, with a fixed moving speed, when the transmit power is relatively large, the logistic nonlinear EH model can be replaced with the piecewise one due to the relatively small gap between their achieved $\mathrm{I}$ - $\mathrm{E}$ regions. Additionally, for a fixed moving track length, the higher moving speed yields the smaller $\mathrm{I}$ - $\mathrm{E}$ region with all three EH models. [ABSTRACT FROM AUTHOR]

In the long-term evolution for railway, orthogonal frequency-division multiplexing (OFDM) is adopted to provide seamless connection to existing ground cellular network and support high mobility communication in future 5G. However, due to the high velocity of high-speed railway (HSR), the channel is fast time-varying and serious intercarrier interference (ICI) is introduced, meaning that low-complexity and real-time ICI reduction methods are needed, which has not been well discussed in previous works. In this paper, we focus on the HSR downlinks with distributed transmit antennas and develop two corresponding ICI reduction methods for additive white Gaussian noise (AWGN) and Rician channels, respectively. With the information of relative locations and velocities between corresponding antenna pairs, we show that the ICI matrices in AWGN and Rician channels can be mathematically calculated, and they are approximately unitary. With these results, we propose two corresponding low-complexity ICI reduction methods to avoid matrix inversion and suit fast time-varying nature. Simulation results show our proposed ICI mitigation method can achieve similar service quantity with that obtained on the case without ICI when velocity is about 300 km/h. [ABSTRACT FROM PUBLISHER]

We consider channel estimation for high-speed railway communication systems, where both the transmitter and the receiver are equipped with large-scale antenna arrays. It is known that the throughput of conventional training schemes monotonically decreases with the mobility. Assuming that the moving terminal employs a large linear antenna array, this paper proposes a position-aided channel estimation scheme whereby only a portion of the transmit antennas send pilot symbols and the full channel matrix can be well estimated by using these pilots together with the antenna position information based on the joint spatial-temporal correlation. The relationship between mobility and throughput/DoF is established. Furthermore, the optimal selections of transmit power and time interval partition between the training and data phases as well as the antenna size are presented accordingly. Both analytical and simulation results show that the system throughput with the position-aided channel estimator does not deteriorate appreciably as the mobility increases, which is sharply in contrast with the conventional one. [ABSTRACT FROM PUBLISHER]

This paper investigates the simultaneous wireless information and power transfer (SWIPT) in cooperative relay networks, where a relay harvests energy from the radio frequency (RF) signals transmitted by a source and then uses the harvested energy to assist the information transmission from the source to its destination. Both source and relay transmissions use rateless codes (RCs), which allow the destination to employ any of the two information receiving strategies, i.e., the mutual information accumulation (IA) and the energy accumulation (EA). The SWIPT-enabled relay employs three different SWIPT receiver architectures, the ideal receiver, and two practical receivers (i.e., the power splitting (PS) receiver and the time switch (TS) receiver). Accordingly, three relaying protocols, namely, the ideal protocol, PS protocol, and TS protocol, are presented. To explore the system performance limits with these three protocols, optimization problems are formulated to maximize their achievable information rates. For the ideal protocol, explicit expressions of the optimal solutions are derived. For the PS protocol, a linear-search algorithm is designed to solve the nonconvex problems. For the TS protocol, two solving methods are presented. Numerical experiments are carried out to validate our analysis and algorithms, which show that, with the same SWIPT receiver, the IA-based system outperforms the EA-based system, whereas with the same information receiving strategy, the PS protocol outperforms the TS protocol. Moreover, compared with nonrateless-coded systems, the proposed protocols exhibit considerable performance gains. Moreover, the effects of the relay position on system performance are also discussed, which provides insights on SWIPT-enabled relay systems. [ABSTRACT FROM AUTHOR]

Multiple-Input, Multiple-Output (MIMO)-orthogonal frequency division multiplexing (OFDM) is a promising technique in 5G wireless communications. In high-mobility scenarios, the transmission environments are time-varying and/or the relative moving velocity between the transmitter and receiver is also time-varying. In the literature, most of previous works mainly focused on fixed subcarrier group size and precoded the MIMO signals with unitary channel state information. In this way, the subcarrier grouping may naturally lead to big loss of channel capacity in high-mobility scenarios because of the channel state information difference on the subcarriers in each group. To employ the MIMO-OFDM technique, adaptive subcarrier grouping scheme may be an efficient way. In this paper, we first consider MIMO-OFDM systems over double-selective i.i.d. Rayleigh channels and investigate the quantitative relation between subcarrier group size and capacity loss theoretically. With developed theoretical results, we also propose an adaptive subcarrier grouping scheme to satisfy the preset capacity loss threshold by adjusting grouping size with the sensed environmental information and mobile velocity. Theoretical analysis and simulation results show that to achieve a better system capacity, a sparse scattering, lower signal-to-noise ratio, and lower velocity as well as properly large antenna number are matched with larger subcarrier group size. One important observation is that if the antenna number is too large and higher than a threshold, which will not bring any additional gain to the subcarrier grouping. That is, the system capacity loss will converge to a lower bound expeditiously with respect to antenna number, which is given in theory also. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In 5G heterogeneous networking, it is promising to integrate different wireless networks to provide higher data rate. This paper models the integrated system as a receiver frequency division relay channel (RFDRC) and studies how to improve the transmission rate by combining decode-forward (DF), compress-forward (CF), and amplify-forward (AF) schemes. First, we establish clear criterions on how to select a relay scheme among DF, CF, and AF schemes and prove that the CF outperforms AF for all possible configurations. Based on the scheme selection criterions, we propose a hybrid DF–CF scheme which takes advantage of both DF and CF schemes in RFDRC. A near-optimal resource allocation is presented for the DF–CF-based system, leading to a new achievable rate for RFDRC. For ease of implementation, we further put forward a hybrid DF–AF scheme and reconsider the joint bandwidth and power allocation. Two suboptimal resource allocation solutions are established. In particular, when source frequency band and relay frequency band have equivalent bandwidth, we show that the proposed hybrid DF–AF scheme can achieve the concave envelope of the maximum between DF rate and AF rate. Numerical results show that the proposed schemes bring significant gains for RFDRC. [ABSTRACT FROM AUTHOR]

Widespread deployment of high-speed railways in recent years has created huge demand for high-mobility broadband wireless communications. To provide broadband wireless access for passengers on the train, a well-acknowledged approach is to apply a two-hop architecture, under which passengers communicate with base stations (BSs) via an access point (AP) installed in the train. We consider the uplink transmission from the AP to the BSs on the ground along the railway. The key problem we discuss is how to match user-data arrival process and time-varying channel service process with a delay constraint at the AP. We first assume the constant-rate data arrival and the wireless channel affected only by large-scale fading in high-speed railway scenarios. We present the optimal power-allocation policy given the delay constraint. Based on the policy, we show that there exists a power–delay tradeoff in our system model, with the delay within a limited range. Besides, we find that the average transmit power and the train velocity have a tradeoff, which is similar to the power–delay tradeoff. Besides, given average transmit power constraint, the delay constraint is inversely proportional to the train velocity. Finally, when small-scale fading is considered, we modify the optimal power-allocation policy and provide a convenient approach to counteract Nakagami- $m$ fading in high signal-to-noise ratio (SNR) regimes. The modified power-allocation policy can be well adapted to different fading statistics in different terrestrial environments experienced by the high-speed train. [ABSTRACT FROM PUBLISHER]

To provide stable and high data rate wireless access for passengers in the train, it is necessary to properly deploy base stations along the railway. We consider this issue from the perspective of service, which is defined as the integral of the time-varying instantaneous channel capacity. With large-scale fading assumption, it will be shown that the total service of each base station is inversely proportional to the velocity of the train. Besides, we find that if the ratio of the service provided by a base station in its service region to its total service is given, the base station interval (i.e., the distance between two adjacent base stations) is a constant regardless of the velocity of the train. On the other hand, if a certain amount of service is required, the interval will increase with the velocity of the train. The aforementioned results apply not only to simple curve rails, like line rail and arc rail, but also to any irregular curve rail, provided that the train is traveling at a constant velocity. Furthermore, the new developed results are applied to analyze the on-off transmission strategy of base stations. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, we study the channel service process of a multiple-input multiple-output (MIMO) system over an independent and identically distributed ( i.i.d.) fading channel. One key problem of communication over fading MIMO channels is what kind of service the MIMO channel can provide. In this paper, this problem is investigated in terms of channel service process. Assuming that the channel state information is available at the receiver, the channel service process S( t) is defined as the integral of the instantaneous channel capacity over a time interval of length t, which specifies the service provided by the channel during the period. Using the characteristic function approach and the infinitely divisible law, it is proved that the channel service process S( t) is a deterministic linear function of time t, other than any curve form or a stochastic process. Specifically [ABSTRACT FROM AUTHOR]

Modeling of wireless channels, especially non-stationary fading channels, is important for design and performance analysis of wireless communication systems. Recently, we proposed a new approach to modeling non-stationary fading channels, based on the theory of evolutionary spectrum (ES). In this paper, we develop a time-varying autoregressive (AR) model for a non-stationary flat fading channel; specifically, we develop a method to determine the time-varying coefficients of the AR channel model, given the ES of a non-stationary process. Furthermore, with the ES theory, we develop a trace-driven time-varying AR channel simulator to generate a non-stationary flat fading process. Simulation results show that the ES of the channel gain process produced by our joint ES-and-AR-based channel model agrees well with the user-specified ES, indicating the accuracy of our joint ES-and-AR-based channel model. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

High-speed railways (HSRs) have been widely deployed all over the world in recent years. Different from traditional cellular communications, the high mobility of HSR communication makes it essential to implement power allocation (PA) along time. In the HSR case, the transmission rate greatly depends on the distance between the base station (BS) and the train. As a result, the train receives a time-varying data rate service when passing by a BS. It is clear that the most efficient PA will spend all the power when the train is nearest the BS, which will cause great unfairness along time. On the other hand, channel inversion allocation achieves the best fairness in terms of constant rate transmission. However, its power efficiency is much lower. Therefore, power efficiency and fairness along time are two incompatible objects. For the HSR cellular system considered in this paper, a tradeoff between the two is achieved by proposing a temporal proportional-fair PA scheme. In addition, a near-optimal closed-form solution and one algorithm finding \epsilon-optimal allocation are presented. [ABSTRACT FROM PUBLISHER]

The grail of next-generation wireless networks is providing real-time services for delay-sensitive applications, which require that the wireless networks provide QoS guarantees. The effective capacity (EC) proposed by Wu and Negi provides a powerful tool for design of QoS provisioning mechanisms. In this paper, we intend to generalize their formula for the effective capacity of a correlated Rayleigh fading channel; specifically, we derive a closed form approximate EC formula for a special correlated Nakagami-m fading channel, for which the inverse of the correlation coefficient matrix is tridiagonal. To verify its accuracy via simulation, we develop a Green-matrix based approach, which allows us to analytically obtain the effective capacity (given the joint probability density function of a correlated Nakagami-m fading channel) while being able to simulate the corresponding channel gain process. Simulation results show that our EC formula is accurate. Furthermore, to facilitate the application of the EC theory to the design of practical QoS provisioning mechanisms, we propose a simple algorithm for estimating the EC of an arbitrary correlated Nakagami-m fading channel, given channel measurements; simulation results demonstrate the accuracy of our proposed EC estimation algorithm showing its suitability in practice. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

ABSTRACT Secure transmission of information over wireless channels in the presence of an eavesdropper has attracted much attention recently. Previous work assumes that a transmitter has perfect knowledge of the channel side information (CSI) of the legitimate channel and the eavesdropper's channel. To loosen this strong requirement, this paper considers the case where a transmitter has perfect knowledge of the CSI of the legitimate channel and only the average channel gain of the eavesdropper's channel. In this case, some information may be leaked to the eavesdropper because the eavesdropper's channel may have a higher gain than the legitimate channel. Hence, we propose, for the first time, to study leakage-probability-constrained secrecy capacity of a fading channel, that is, secrecy capacity under the constraint on leakage probability. We also propose an optimal power allocation strategy that maximizes leakage-probability-constrained secrecy capacity under average power constraint. Moreover, we study the impact of the bias of the average gain estimate of the eavesdropper's channel on leakage-probability-constrained secrecy capacity. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The next generation wireless networks call for quality of service (QoS) support. The effective capacity (EC) proposed by Wu and Negi provides a powerful tool for the design of QoS provisioning mechanisms. In their previous work, Wu and Negi derived a formula for effective capacity of a Rayleigh fading channel with arbitrary Doppler spectrum. However, their paper did not provide simulation results to verify the accuracy of the EC formula derived in their paper. This is due to difficulty in simulating a Rayleigh fading channel with a Doppler spectrum of continuous frequency, required by the EC formula. To address this difficulty, we develop a verification methodology based on a new discrete-frequency EC formula; different from the EC formula developed by Wu and Negi, our new discrete-frequency EC formula can be used in practice. Through simulation, we verify that the EC formula developed by Wu and Negi is accurate. Furthermore, to facilitate the application of the EC theory to the design of practical QoS provisioning mechanisms in wireless networks, we propose a spectral-estimation-based algorithm to estimate the EC function, given channel measurements; we also analyze the effect of spectral estimation error on the accuracy of EC estimation. Simulation results show that our proposed spectral-estimation-based EC estimation algorithm is accurate, indicating the excellent practicality of our algorithm. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This article investigates a relay-assisted wireless powered communication network (WPCN), where the access point (AP) inspires the auxiliary nodes to participate together in charging the sensor, and then the sensor uses its harvested energy to send status update packets to the AP. An incentive mechanism is designed to overcome the selfishness of the auxiliary node. In order to further improve the system performance, we establish a Stackelberg game to model the efficient cooperation between the AP–sensor pair and auxiliary node. Specifically, we formulate two utility functions for the AP–sensor pair and the auxiliary node, and then formulate two maximization problems respectively. As the former problem is non-convex, we transform it into a convex problem by introducing an extra slack variable, and then by using the Lagrangian method, we obtain the optimal solution with closed-form expressions. Numerical experiments show that the larger the transmit power of the AP, the smaller the age of information (AoI) of the AP–sensor pair and the less the influence of the location of the auxiliary node on AoI. In addition, when the distance between the AP and the sensor node exceeds a certain threshold, employing the relay can achieve better AoI performance than non-relaying systems. [ABSTRACT FROM AUTHOR]

Wireless powered communication technology has a great potential to power low-power wireless sensor networks and Internet of Things (IoT) for real-time applications in future 5G networks, where age of information (AoI) plays a very important performance metric. This paper studies the system average AoI of a wireless powered network, where a wireless-powered user harvests energy from a wireless power source (WPS) and then transmits data packets to its access point (AP) by using the harvested energy. The user generates data packets with some probability and adopts the first-come-first-served (FCFS) service policy. For such a system, by using the queuing theory and the probability models, we derive a closed-form expression of the system average AoI. We also formulate an optimization problem to minimize the AoI by optimizing the data packet generating probability, and find its solution by simple calculation and search. Simulation results demonstrate the correctness of our obtained analytical results. It also shows that, when the total distance of the two hops is fixed, the system average AoI increases linearly with the increment of the distance of the first hop, and a smaller data packet generating probability should be selected to match a bigger first-hop distance for achieving a smaller system average AoI. Moreover, a smaller data packet size also contributes to a smaller system average AoI. [ABSTRACT FROM AUTHOR]

This paper investigates the multi-cell coordinated beamforming (MCBF) design for secure simultaneous wireless information and power transfer (SWIPT) in both centralized and distributed manners. In each cell, one transmitter serves multiple information receivers (IRs) and energy receivers (ERs) with the non-linear energy harvesting (EH) model. Meanwhile, several eavesdroppers (Eves) intend to intercept the confidential information transmitted for IRs. To achieve a secure transmission, the artificial noise (AN) is embedded in the transmit signals of each transmitter. The proposed design is formulated into a power-minimization problem to guarantee the IRs’ information and ERs’ energy requirements while avoiding the information being intercepted by Eves. Since the problem is non-convex and not easy to solve, a solution method based on semi-definition relaxation (SDR) is proposed and the global optimum is proved to be guaranteed with full channel state information (CSI). We further present a distributed AN-aided MCBF for the system by using alternating direction method of multipliers (ADMM), with which each transmitter is able to calculate its own beamforming vectors and AN covariance matrix based on its local CSI. Simulation results show that our proposed distributed design converges to the global optimum obtained by the centralized one. It is also shown that by employing AN, the total required power of the system is reduced and the effect of AN on the system performance decreases with increment of transmit antennas. Compared with traditional linear EH model, optimizing the system under the non-linear EH one avoids false output power at the ERs and saves power at the transmitter. [ABSTRACT FROM AUTHOR]