Average Achievable Rate Research Articles

Secure short-packet communications in power beacon-assisted IoT networks over Nakagami-m fading channels

In this work, we investigate short-packet communications in power beacon (PB)-assisted Internet-of-Things (IoT) networks, where an energy-constrained actuator first harvests energy from a dedicated PB, and then transmits confidential signals to a desired controller in the presence of an eavesdropper. We derive a closed-form lower bound approximation expression for the average achievable effective secrecy rate (AESR) over Nakagami-m fading channels. To gain more insights, we also present the asymptotic average AESR in the high signal-to-noise ratio (SNR) regime. Specifically, analytical results indicate that an average AESR floor appears with the increase of SNR. Moreover, a low complexity one-dimensional search method is employed to maximize the average AESR by optimizing the energy harvesting length. Monte-Carlo simulations are provided to corroborate our analysis.

Unmanned aerial vehicle-assisted wideband cognitive radio network based on DDQN-SAC

Cognitive radio (CR) systems have emerged as effective tools for improving spectrum efficiency and meeting the growing demands of communication. This study focuses on a flexible CR system based on opportunistic spectrum access technology, which enables secondary networks to efficiently utilize unoccupied spectrum resources for information transmission by actively sensing the spectrum utilization of primary networks. Specifically, we introduce unmanned aerial vehicles (UAV) technology into the CR system to further enhance its flexibility and adaptability, which enables the transmission efficiency of low-altitude UAV networks. In this CR system, UAVs are employed for more flexible spectrum management. The objective of this research is to maximize the average achievable rate of SUs by jointly optimizing the trajectories of secondary UAV, the trajectories of primary UAV, the beamforming of secondary UAV, subchannel allocation and sensing time. To achieve this goal, we employ deep reinforcement learning (DRL) algorithms to optimize these variables. Compared to traditional optimization algorithms, DRL algorithms not only have lower computational complexity but also achieve faster convergence. To address the mixed-action space problem, we propose a Dueling DQN-Soft Actor Critic algorithm. Simulation results demonstrate that the proposed approach in this paper significantly enhances the performance of the CR system compared to traditional baseline schemes. This is manifested in higher spectrum efficiency and data transmission rates, while minimizing interference with the primary network. This innovative research combines drone technology and DRL algorithms, bringing new opportunities and challenges to the future development of cognitive communication systems.

Federated learning-based trajectory prediction for dynamic resource allocation in moving small cell networks

With the evolution of fifth generation (5G) of mobile communication, vehicular edge computing (VEC) and moving small cell (MSC) network are gaining attention because of their capability to provide improved quality-of-service (QoS) to vehicular users. The ultimate goal of VEC-enabled MSC network is to diminish the vehicular penetration effect and path loss resulting in improved network performance for vehicular users. In this paper, we explore distributed resource block (RB) allocation for fronthaul links of MSCs with probabilistic mobility in VEC-enabled MSC network. The proposed work exploits the computational power of road side units (RSUs) deployed with VEC servers present along the road sides to allocate the resources to MSCs in a distributed manner by exchanging limited information, with the objective of maximizing the data rate achieved by MSC network. Moreover, we propose federated learning (FL)-based position prediction of MSCs to predict the trajectory of MSCs in advance for efficient prediction of resource allocation in MSC network. Simulations results are presented to compare the position prediction dependent distributed and centralized time interval dependent interference graph-based resource allocation to MSCs in terms of RB utilization and average achievable data rate of MSC network. For comparison, we further investigated centralized as well as distributed threshold time dependent interference graph-based allocation of resources to MSC network.

Performance evaluation for multi-antenna UWOC-RF NOMA systems with imperfect CSI and SIC

Information transmission is easily affected by obstacles or other factors, which makes it challenging to achieve perfect channel state information (CSI) and successive interference cancellation (SIC) in practical applications. Therefore, in this paper, a dual-hop underwater wireless optical communication-radio frequency (UWOC-RF) system with non-orthogonal multiple access (NOMA) in the presence of both imprecise CSI and imperfect SIC is investigated. In particular, the underwater source sends a superimposed optical NOMA signal to a pair of land-based users via a decode-and-forward relay on the surface, which decodes the received signal and encodes it into the RF one before broadcasting it to the terrestrial users. Considering a scenario that both the land-based users are equipped with multiple antennas and adopt a maximal-ratio combining technique to deal with those multiple copies of received signals, we first format the expressions of probability density function, cumulative distribution function, and the p-th moment of the imperfect channel gain in the UWOC link. And then the analytical and asymptotic expressions for outage probability as well as the closed-form expression for average achievable rate of each user are obtained by utilizing the Meijer's-G and the Fox's-H functions. Finally, Monte-Carlo simulations are performed to validate the accuracy of those analytical expressions.

A Framework for Transmission Design for Active RIS-Aided Communication With Partial CSI

Active reconfigurable intelligent surfaces (RISs) have recently been proposed to compensate for the severe multiplicative fading effect of conventional passive RIS-aided systems. Each reflecting element of active RISs is assisted by an amplifier such that the incident signal can be reflected and amplified instead of only being reflected as in passive RIS-aided systems. This work addresses the practical challenge that, on the one hand, in active RIS-aided systems the perfect individual channel state information (CSI) of the RIS-aided channels cannot be acquired due to the lack of signal processing power at the active RISs, but, on the other hand, this CSI is required to calculate the expected system data rate and RIS transmit power needed for transceiver design. To address this issue, we first derive closed-form expressions for the average achievable rate and the average RIS transmit power based on partial CSI of the RIS-aided channels. Then, we formulate an average achievable rate maximization problem for jointly optimizing the active beamforming at both the base station (BS) and the RIS. This problem is then tackled using the majorization–minimization (MM) algorithm framework, and, in each iteration low-complexity solutions for the BS and RIS beamforming are found based on the Karush-Kuhn-Tucker (KKT) conditions. To ensure the quality of service (QoS) of each user, we further formulate a rate outage constrained beamforming problem, which is solved using the Bernstein-Type inequality (BTI) and semidefinite relaxation (SDR) techniques. Numerical results show that the proposed algorithms can efficiently overcome the challenges imposed by imperfect CSI in active RIS-aided wireless systems.

Performance Analysis of a WPCN-Based Underwater Acoustic Communication System

Underwater acoustic communication (UWAC) has a wide range of applications, including marine environment monitoring, disaster warning, seabed terrain exploration, and oil extraction. It plays an indispensable and increasingly important role in marine resource exploration and marine economic development. In current UWAC systems, the terminal nodes are usually powered by energy-limited batteries. Due to the harshness of the underwater environment, especially in the ocean environment, it is very costly and difficult, even impossible, to replace the batteries for the terminal nodes in UWACs, which results in the short lifetime and unreliability of the terminal nodes and the systems. In this paper, we present the application of a wireless powered communication network (WPCN) to the UWAC systems to provide an auxiliary and convenient energy supplement for solving the energy-limited problem of the terminal nodes, where the hybrid access point (H-AP) transfers energy to the terminal nodes in the downlink. In contrast, the terminal nodes use the harvested energy to transmit the information to the H-AP in the uplink. To evaluate the proposed WPCN-based UWAC systems, we investigate the performance of the average bit error rate (BER), outage probability, and achievable information rate for the systems in a frequency-selective sparse channel and non-white noise environment. We derive the closed-form expression for the probability density function (PDF) of the received signal-to-noise ratio (SNR). Based on this, we further derive novel closed-form expressions for the average BER and the outage probability of the systems. Numerical results confirm the validity of the proposed analytical results. It is shown that there exists an optimal signal frequency and time allocation factor for the systems to achieve optimal performance, and a larger optimal time allocation factor is preferred for a smaller hybrid access point (H-AP) transmit power or a larger transmission distance, while a smaller optimal signal frequency is required for a larger transmission distance.

Coverage and Rate Analysis of LEO Satellite-to-Airplane Communication Networks in Terahertz Band

The low Earth orbit (LEO) satellite constellation in the terahertz (THz) band is one of the promising technologies to provide global coverage and high-rate transmission to the airplane, whose key performance evaluation is required before realistic deployment. In this paper, we consider a downlink THz LEO satellite-airplane network with directional antennas, where the satellites follow a binomial point process on a spherical surface. Incorporating the distinctive THz propagation properties and directional beams in the two scenarios with/without molecular absorption noise, we propose an analytical framework to evaluate the coverage probability and average achievable rate of an arbitrary airplane. The analytical results are expressed in terms of the Laplace transforms of the interference-plus-molecular absorption noise and interference. Specifically, considering a frequency reuse strategy, we first provide the probability distributions of the distances from an arbitrary satellite, the serving satellite and any non-serving satellite to the target airplane, and calculate the probabilities of whether an interfering satellite is blocked by the Earth. Numerical results verify the accuracy of the analytical expressions and show that fewer orthogonal channels and lower LEO satellite altitude lead to better coverage and rate performance. As a key parameter in network design, the number of satellites has two competing effects on coverage and rate, and an optimum satellite number exists. Overall, this study provides theoretical guidance for deploying and planning THz satellite constellations.

Performance Analysis of RIS-Assisted Large-Scale Wireless Networks Using Stochastic Geometry

In this paper, we investigate the performance of a reconfigurable intelligent surface (RIS) assisted large-scale network by characterizing the coverage probability and the average achievable rate using stochastic geometry. Considering the spatial correlation between transmitters (TXs) and RISs, their locations are jointly modelled by a Gauss-Poisson process (GPP). Two association strategies, i.e., nearest association and fixed association, are both discussed. For the RIS-aided transmission, the signal power distribution with a direct link is approximated by a gamma random variable using a moment matching method, and the Laplace transform of the aggregate interference power is derived in closed form. Based on these expressions, we analyze the channel hardening effect in the RIS-assisted transmission, the coverage probability, and the average achievable rate of the typical user. We derive the coverage probability expressions for the fixed association strategy and the nearest association strategy in an interference-limited scenario in closed form. Numerical results are provided to validate the analysis and illustrate the effectiveness of RIS-assisted transmission with passive beamforming in improving the system performance. Furthermore, it is also unveiled that the system performance is independent of the density of TXs with the nearest association strategy in the interference-limited scenario.

Coverage Performance Analysis of a Cache-Enabled UAV Base Station Assisted Cellular Network

Unmanned Aerial Vehicle base stations (UBSs) can be used to assist a ground cellular network to enhance its network services for cellular users. This paper studies the coverage performance analysis of a cache-enabled UBS-assisted cellular network. Analytical models are derived for investigating the overall coverage probability of the network and the average achievable rate of a cellular user. In deriving the analytical models, an air-to-ground (A2G) channel model with both a line-of-sight (LoS) link and a non-line-of-sight (NLoS) link, a BS association strategy based on the strongest average received power, and a cache model with a probabilistic caching strategy are considered. The cache hit probability of UBSs based on the cache model is also taken into consideration. Moreover, the association probabilities with the association strategy are derived for different types of base stations. The derived analytical models are validated through simulation results and the impacts of system parameters on the coverage performance of the network are investigated through numerical results. Compared with existing relevant work, the novelty of this work is that the effects of both an access link and a backhaul link are taken into account in the coverage performance analysis. The obtained results can provide theoretical guidance for the deployment of UBSs in a cache-enabled UBS-assisted cellular network.

Toward Optimal Deployment of UAV Relays in UAV-Assisted Internet of Vehicles

The past decade has witnessed an explosive growth of unmanned aerial vehicles (UAVs), which have attracted great attention in assisting Internet of Vehicles (IoV) communication systems thanks to the advantages of cost-effectiveness, high maneuverability, and flexible deployment. Yet several issues, such as UAVs' transmit power and energy resources as well as the high-speed mobility of IoV user equipment (VUE), pose challenges to the development of UAVs in UAV-assisted IoV networks. To provide reliable and high-throughput wireless links for VUEs in a given ground area, this paper considers a scenario in which a ground VUE is facing difficulties in receiving service from a ground roadside unit (RSU) owing to possible sudden RSU malfunction or poor signal coverage. In this case, UAVs are generally deployed in the air, serving as relays to establish communication links between uncovered VUE and the neighboring RSU. To maximize the system capacity, we investigate the deployment problem of UAV relays under single-UAV relaying and multi-UAV relaying cases upon considering VUE mobility, and exploit the optimal deployment strategy of UAV relays under fixed total power consumption. Comprehensive simulation results verify that the proposed algorithm can outperform benchmark methods on significant critical indicators such as the average achievable user rate, and the outage probability. Also, evaluations and analyses have highlighted the effects of key system parameters (e.g., altitude, number, and transmit power of UAV relays) on optimal UAV relay deployment position and system performance.

STAR-RIS-Enabled Short-Packet NOMA Systems

This paper analyzes the performance of simultaneous transmitting and reflecting (STAR) reconfigurable intelligent surface (RIS)-enabled short-packet non-orthogonal multiple access (NOMA) systems. A mode-switching protocol combined with partition strategies (MSPS) for the STAR-RIS design is proposed to simultaneously serve multiple actuators along with the discrete phase-shift alignment in order to reduce the STAR-RIS implementation costs. Approximate and asymptotic closed-form expressions for the average block error rate (BLER) and achievable rate have been derived to reveal some useful insights, such as the actuators' diversity order, coding gain, the power allocation factor, packet length, and the number of information bits. Numerical results confirm that: i) the considered system achieves better BLER balance among the actuators than classical RIS-based short-packet NOMA systems and higher achievable sum rate than RIS-based short-packet orthogonal multiple access ones; ii) the STAR-RIS with discrete phase shift design using 3-bit quantization achieves near-optimal performance with the continuous phase shift; iii) there is a trade-off between using bit quantizer and the total number of STAR-RIS elements; and iv) the power allocation strategy provides better average sum rate improvement than block-length increasing strategy.

Joint Optimization of Phase Shift Matrices and Trajectory for AF Relay-Based Cooperation Communication With RIS-Enabled UAV System

In the complicated or hard-to-reach communication areas, sometimes much higher average achievable rate (AAR) or wider coverage is in urgent and temporary need. To address this challenge, this article proposes a novel amplify-and-forward (AF) relay-based cooperation communication scheme with reconfigurable intelligent surface (RIS)-enabled unmanned aerial vehicle (UAV) enhancing. The UAV acts as a moving RIS in the sky, which provides additional links to enhance the performance of the AF relay-based cooperation on the ground. Aiming to maximize the AAR of the proposed scheme, we jointly optimize the trajectory of UAV and the phase shift matrices of RIS over total time frames. At first, we decompose the original intractable problem into two subproblems of the phase shift matrices optimization and trajectory optimization. Subsequently, the optimal phase shift matrices are achieved by aligning the phases of received signals. Since the trajectory optimization subproblem is still complicated and nonconvex, we apply the successive convex approximation (SCA) method to reformulate it into a convex problem and further solve it by iterative method. Simulation results demonstrate the superiorities of the proposed scheme as compared with the benchmark schemes and also reveal the effects of various factors on its performance.

Performance Analysis for Dual-Hop UWOC-RF Systems With NOMA

In this study, we investigate a non-orthogonal multiple access (NOMA)-assisted dual-hop underwater wireless optical communication-radio frequency (UWOC-RF) network. Specifically, an optical source forwards a NOMA signal to a marine relay, which first deploys either the heterodyne detection or intensity modulation direct detection to process the received signal, and then encodes and re-transmits a superimposed signal to two terrestrial destinations. Assuming the UWOC channel is subject to a unified mixture Exponential-Generalized Gamma distribution and the RF channels experience Nakagami-m fading, the analytical as well as asymptotic expression for outage probability is obtained in the form of the Meijer’s G-function. Moreover, the average achievable rate is also investigated by utilizing the bivariate Fox’s H-function. In addition, the accuracy of those expressions is verified with Monte-Carlo simulations.

Impact of Channel Aging on Dual-Function Radar-Communication Systems: Performance Analysis and Resource Allocation

In conventional dual-function radar-communication (DFRC) systems, the radar and communication channels are routinely estimated at fixed time intervals based on their worst-case operation scenarios. Such situation-agnostic repeated estimations cause significant training overhead and dramatically degrade the system performance, especially for applications with dynamic sensing/communication demands and limited radio resources. In this paper, we leverage the channel aging characteristics to reduce training overhead and to design a situation-dependent channel re-estimation interval optimization-based resource allocation in a multi-target tracking DFRC system. Specifically, we exploit the channel temporal correlation to predict radar and communication channels for reducing the need for training preamble retransmission. Then, we characterize the channel aging effects on the Cramer-Rao lower bounds (CRLBs) for radar tracking performance analysis and achievable rates with maximum ratio transmission (MRT) and zero-forcing (ZF) transmit beamforming for communication performance analysis. In particular, the aged CRLBs and achievable rates are derived as closed-form expressions with respect to the channel aging time, bandwidth, and power. Based on the analyzed results, we optimize these factors to maximize the average total aged achievable rate subject to individual target tracking precision demand, communication rate requirement, and other practical constraints. Since the formulated problem belongs to a non-convex problem, we develop an efficient one-dimensional search based optimization algorithm to obtain its suboptimal solutions. Finally, simulation results are presented to validate the correctness of the derived theoretical results and the effectiveness of the proposed allocation scheme.

Coexisting Terahertz and RF Finite Wireless Networks: Coverage and Rate Analysis

Wireless communications over Terahertz (THz)-band frequencies are vital enablers of ultra-high rate applications and services in sixth-generation (6G) networks. However, THz communications suffer from poor coverage because of inherent THz features such as high penetration losses, significant molecular absorption, and severe path loss. To surmount these critical challenges and fully exploit the THz band, we explore a coexisting radio frequency (RF) and THz finite indoor network in which THz small cells are deployed to provide high data rates, and RF macrocells are deployed to satisfy coverage requirements. Using stochastic geometry tools, we assess the performance of coexisting RF and THz networks and derive tractable analytical expressions for the coverage probability and average achievable rate. The analytical results are validated with Monte-Carlo simulations. Several insights are devised for accurate tuning and optimization of THz system parameters, including the THz bias, and the fraction of THz access points (APs) to deploy. The obtained results recognize a clear coverage/rate trade-off where a high fraction of THz AP improves the rate significantly but may degrade the coverage performance. Furthermore, the location of a user in the finite area highly affects the fraction of THz APs that optimizes its quality of service.

Analysis and Optimization of a Double-IRS Cooperatively Assisted System With a Quasi-Static Phase Shift Design

The analysis and optimization of single intelligent reflecting surface (IRS)-assisted systems have been extensively studied, whereas little is known regarding multiple-IRS-assisted systems. This paper investigates the analysis and optimization of a double-IRS cooperatively assisted downlink system (D-IRS-C), where a multi-antenna base station (BS) serves a single-antenna user with the help of two multi-element IRSs, connected by an inter-IRS channel. The channel between any two nodes is modeled with Rician fading. The BS adopts the instantaneous CSI-adaptive maximum-ratio transmission (MRT) beamformer, and the two IRSs adopt a cooperative quasi-static phase shift design. The goal is to maximize the average achievable rate, which can be reflected by the average channel power of the equivalent channel between the BS and user at low channel estimation and phase adjustment costs and computational complexity. First, we obtain tractable expressions of the average channel power of the equivalent channel in the general (Rician factor), pure line of sight (LoS), and pure non-line of sight (NLoS) regimes, respectively. Then, we jointly optimize the phase shifts of the two IRSs to maximize the average channel power of the equivalent channel in these regimes. The optimization problems are challenging non-convex problems. We obtain globally optimal closed-form solutions for some cases and propose computationally efficient iterative algorithms to obtain stationary points for the other cases. Next, we compare the computational complexity for optimizing the phase shifts and the optimal average channel power of D-IRS-C with those of a counterpart double-IRS non-cooperatively assisted system (D-IRS-NC) and a counterpart single-IRS-assisted system (S-IRS) at a large number of reflecting elements in the three regimes. Finally, we numerically demonstrate notable gains of the proposed solutions over the existing solutions at different system parameters. To our knowledge, this is the first work that optimizes the quasi-static phase shift design of D-IRS-C and characterizes its advantages over the optimal quasi-static phase shift design of the counterpart D-IRS-NC and S-IRS.

Stochastic geometry modelling and analysis for cooperative NOMA with large transmit antennas for 5G applications and beyond

AbstractAmong the technologies that have made 5G wireless communication successful are non‐orthogonal multiple access (NOMA) and cooperative NOMA. The distinction is that cooperative NOMA adds coding schemes to improve performance. Nevertheless, research on cooperative NOMA has primarily used theoretical correlation‐based stochastic models (CBSM) instead of geometric‐based stochastic models (GBSM) that represent suitable channel conditions by including characteristics like path loss, delay profile, and angle of arrival in the model. This paper connects the low adoption of GBSM is due to computational challenges. Given this, it is essential to assess cooperative NOMA that employs GBSM with large antenna transmitters to meet future 5G expectations. The cooperative NOMA system's transmitter is modelled as a uniform rectangular array and a novel channel realisation is proposed for analysis. The location vector of the antenna using the physical dimension of the array is defined to reduce computational problems. Results shows that the average bit‐error performance of GBSM matches that of CBSM at the same antenna element separation, but the spatial correlation between antenna elements significantly impacts the outage probability and average achievable rates of GBSM performance. Enhanced GBSM performance by increasing antenna separation at the transmitter above one‐eighth wavelength.

Integrated Sensing and Communications for V2I Networks: Dynamic Predictive Beamforming for Extended Vehicle Targets

We investigate sensing-assisted beamforming for vehicle-to-infrastructure (V2I) communication by exploiting integrated sensing and communications (ISAC) functionalities at the roadside unit (RSU). The RSU deploys a massive multi-input-multi-output (mMIMO) array at mmWave. The pencil-sharp mMIMO beams and fine range-resolution implicate that the point-target assumption is impractical, as the vehicle’s geometry becomes essential. Therefore, the communication receiver (CR) may never lie in the beam, even when the vehicle is accurately tracked. To tackle this problem, we consider the extended target with two novel schemes. For the first scheme, the beamwidth is adjusted in real-time to cover the entire vehicle, followed by an extended Kalman filter to predict and track the position of CR according to resolved scatterers. An upgraded scheme is proposed by splitting each transmission block into two stages. The first stage is exploited for ISAC with a wide beam. Based on the sensed results at the first stage, the second stage is dedicated to communication with a pencil-sharp beam, yielding significant communication improvements. We reveal the inherent tradeoff between the two stages in terms of their durations, and develop an optimal allocation strategy that maximizes the average achievable rate. Finally, simulations verify the superiorities of proposed schemes over state-of-the-art methods.

Uplink SINR and rate analysis in massive MIMO systems with two-layer linear receiver

In a previous work, a two-layer linear receiver was proposed as a low-complexity scheme that can achieve a good trade-off between performance and complexity in a massive multiple-input multiple-output (MIMO) context. For this scheme, the antenna array is split up into a number of subsets and multi-cell minimum mean-square-error (M-MMSE) combining is applied in each subset at the first layer. Then, the resulting outputs are combined using maximal-ratio combining (MRC) at the second layer. This paper presents a more complete performance analysis. First, we provide an entirely analytical derivation of the distribution of the output signal-to-noise-and-interference ratio (SINR) of first-layer processing based on multivariate statistical theory. The analysis includes both cases where the subset size is smaller or greater than the total number of signals. Furthermore, upper bounds and approximations on the average uplink SINR and achievable rate are derived. Numerical simulations confirm our analysis results.

Covert Millimeter Wave Communications Based on Beam Sweeping

The combination of millimeter wave (mmWave) and covert communications can ensure high security for some specific circumstances. Instead of considering the covertness only in the data transmission (DT) phase for mmWave massive MIMO systems, the covertness in both the beam alignment (BA) phase and the DT phase is investigated. As a common beam training method for mmWave massive multiple-input multiple-output (MIMO), beam sweeping is adopted to obtain the optimal beam pair in the BA phase. Aiming at maximizing the average effective achievable covert rate in the DT phase, a two-stage power optimization scheme is proposed subject to the covertness and power constraints in both the BA and the DT phases. Specifically, by introducing a covertness allocation factor, closed-form expressions of the transmit power in both phases are derived according to the likelihood function of the received signal. Simulation results demonstrate that the average covert rate of MIMO is larger than that of multiple-input single-output (MISO) although the BA success rate of the former is lower than that of the latter.