Average Achievable Rate Research Articles

Adaptive Transmission for Reconfigurable Intelligent Surface-Assisted OFDM Wireless Communications

Reconfigurable intelligent surfaces (RISs) have recently emerged as an innovative technology for improving the coverage, throughput, and energy/spectrum efficiency of future wireless communications. In this paper, we propose a new transmission protocol for wideband RIS-assisted single-input multiple-output (SIMO) orthogonal frequency division multiplexing (OFDM) communication systems, where each transmission frame is divided into multiple sub-frames to execute channel estimation simultaneously with passive beamforming. As the training symbols are discretely distributed over multiple sub-frames, the channel state information (CSI) associated with RIS cannot be estimated at once. As such, we propose a new channel estimation method to progressively estimate the associated CSI over consecutive sub-frames, based on which the passive beamforming at the RIS is fine-tuned to improve the achievable rate for data transmission. In particular, during the channel training, the RIS plays two roles of embedding training reflection states for progressive channel estimation and performing passive beamforming for data transmission on the data tones. Based on the estimated CSI in each sub-frame, we formulate an optimization problem to maximize the average achievable rate by designing the passive beamforming at the RIS, which needs to balance the received signal power over different sub-carriers and different receive antennas. As the formulated problem is non-convex and thus difficult to solve optimally, we propose two efficient algorithms to find high-quality solutions. Simulation results validate the effectiveness of the proposed channel estimation and beamforming optimization methods. It is shown that the proposed joint channel estimation and passive beamforming scheme is able to drastically improve the average achievable rate and reduce the delay for data transmission as compared to existing schemes.

Joint spectrum sensing, power, and bandwidth allocation for multiband cognitive radio systems

Multiband cognitive radio (CR) signalling allows CR networks to efficiently take advantage of the unused frequency bands. On the other hand, joint spectrum sensing and power allocation in CR systems has been shown to enable higher opportunities for CR transmission. In this work, the authors perform joint spectrum sensing and resource allocation (power and bandwidth) in a multiband CR system. This is achieved by defining an optimisation problem, which is formulated to maximise the average opportunistic CR data rate under constraints on interference, power budget, and total available bandwidth leading to a non-convex optimisation problem. As the original formulated optimisation problem is inherently non-convex, they convert it into a convex problem where the optimal solution is obtained using the Lagrange multipliers method and linear programming. For performance comparison, they consider the classical method based on equal bandwidth allocation for each subchannel. They provide several numerical results to contrast the performance of the proposed method compared to the classical method in terms of the average achievable CR data rate.

Distributed Interference Management: A Broadcast Approach

Effective interference management in the multiuser interference channel strongly hinges on the channel state information’s availability at the transmitters (CSIT). In a broad range of emerging large-scale and distributed networks (e.g., the Internet of Things), acquiring the CSIT is prohibitive due to the extensive information exchange that it imposes. As a result, the interference management approaches that rely on the CSIT lose their effectiveness in such circumstances. This article focuses on the two-user interference channel and proposes a broadcast approach to interference management. Its hallmark is that the transmitters, unlike the receivers, are entirely oblivious to instantaneous channel states. Each transmitter splits its message into multiple superimposed encoded information layers, where each layer is adapted to a given possible state for the combined states of all channels. Depending on the relative gain between the direct and interfering channels, each receiver opportunistically decodes a subset of both transmitters’ received layers. An average achievable rate region is delineated, serving as an inner bound on the Gaussian interference channel’s average capacity region in the absence of CSIT. Finally, an upper bound on the gap between the achievable sum-rate and the sum-rate capacity is established.

Stochastic Geometry Based Performance Characterization of SWIPT in Cell-Free Massive MIMO

This paper investigates the integration of wireless information and power transfer (SWIPT) and cell-free massive multiple-input multiple-output (MIMO) technologies for a cell-free spatially random network, where the access points (APs) are located randomly and modeled using a Poisson point process, and the users' energy and data transfers are separated in time. For the time-division-duplexing mode of operation, the uplink channel state information is acquired locally at the distributed APs via user pilots, and the APs utilize conjugate beamforming for downlink transmissions by exploiting channel reciprocity. In addition, line-of-sight and non-line-of-sight scenarios, which arise from link blockages due to objects are considered along with the corresponding path loss and fading parameters in our performance analysis of the above system set-up. We characterize the harvested energy at a user for both linear and non-linear energy harvesting models, and derive expressions for the average achievable downlink rate for the energy harvesting users. Subsequently, we propose a multi-slot energy storing scheme, and thereby, derive the probability of a user being fully charged at any given time. The throughput and the harvested energy are investigated under different system parameters. We show that a higher mean energy can be harvested by energy users with limited impact on non-energy users through allocating a higher portion of power for the energy users. Furthermore, we reveal that increasing the AP power level has diminishing effect on the probability of being within the fully charged state.

CoMP Transmission in Downlink NOMA-Based Heterogeneous Cloud Radio Access Networks

In this paper, we investigate the integration between the coordinated multipoint (CoMP) transmission and the non-orthogonal multiple access (NOMA) in downlink heterogeneous cloud radio access networks (H-CRANs). In H-CRAN, low-power high-density small remote radio heads (SRRHs) are underlaid by high-power low-density macro RRH (MRRH). However, co-channel deployment of the different RRHs gives rise to the problem of inter-cell interference that significantly affects system performance especially the cell-edge users. Thus, the users are first categorized into Non-CoMP users and CoMP users based on the relation between the useful signal to the dominant interference signal. The Non-CoMP user is the user equipment (UEs) having high signal-to-interference-plus-noise-ratio (INR) and hence associates with only one RRH. On the other hand, the CoMP user, cell-edge user, is the UE that experiences less distinctive received power with the best two RRHs. In the proposed CoMP-NOMA framework, each RRH schedules CoMP-UE and non-CoMP-UE over the same transmission channel using NOMA. We first design an analytical framework based on tools from the stochastic geometry to evaluate the performance of the proposed framework (CoMP-NOMA) which is based on H-CRAN in terms of the average achievable data rate for each NOMA UE. We then examine the spectral efficiency of the proposed CoMP-NOMA based H-CRAN. Simulation results are provided to validate the accuracy of the analytical models and to reveal the superiority of the proposed CoMP-NOMA framework compared with conventional CoMP orthogonal multiple access (CoMP-OMA) techniques. By reaping the benefits of both JT-CoMP and NOMA, we prove that the proposed framework can successfully deal with the inter-cell interference by using CoMP and improve the network's spectral efficiency through NOMA technique. We also show that, with an appropriate power allocation coefficient setting at the Non-CoMP-UEs, a fairness performance can be achieved between the CoMP-UEs and the Non-CoMP-UEs.

Resource Allocations for Symbiotic Radio With Finite Blocklength Backscatter Link

This article exploits a generic downlink symbiotic radio (SR) system, where a base station (BS) establishes a direct (primary) link with a receiver having an integrated backscatter device (BD). In order to accurately measure the backscatter link, the backscattered signal packets are designed to have finite block length. As such, the backscatter link in this SR system employs the finite blocklength channel codes. According to different types of the backscatter symbol period and transmission rate, we investigate the noncooperative and cooperative SR systems, and derive their average achievable rate of the direct and backscatter links, respectively. We formulate two optimization problems, i.e., transmit power minimization and energy-efficiency maximization. Due to the nonconvex property of these formulated optimization problems, the semidefinite programming (SDP) relaxation and the successive convex approximation (SCA) are considered to design the transmit beamforming vector. Moreover, a low-complexity transmit beamforming structure is constructed to reduce the computational complexity of the SDP relaxed solution. Finally, the simulation results are demonstrated to validate the proposed schemes.

Location-Aware Cross-Tier Cooperation for Massive MIMO Heterogeneous Networks

This letter presents a location-aware cross-tier cooperation (CTC) scheme for downlink heterogeneous networks (HetNets), where macro base stations (MBSs) employ massive multiple-input multiple-output (MIMO) systems, and are overlaid with dense low power BSs (LPBs). We first derive an analytical expression for the average achievable rate of a typical user equipment (UE) and then derive the area spectral efficiency (SE) and energy efficiency (EE) of the proposed HetNets. Our resutls demonstrate that: 1) the proposed CTC scheme significantly improves the data rate of edge UEs in macro cell and small cell; 2) the network SE and EE can be improved by densely deployed LPBs; 3) massive MIMO enabled MBSs are capable of significantly improving the network SE. Meanwhile, the EE of HetNets with CTC can also be highly enhanced while the number of MBS antennas is configured properly.

Placement optimization of caching UAV-assisted mobile relay maritime communication

Recently, due to the deployment flexibility of unmanned aerial vehicles (UAVs), UAV-assisted mobile relay communication system has been widely used in the maritime communication. However, the performance of UAV-assisted mobile relay communication system is limited by the capacity of wireless backhaul link between base station and UAV In this paper, we consider a caching UAV-assisted decode-and-forward relay communication system in a downlink maritime communication. For the general case with multiple users, the optimal placement of UAV is obtained by solving the average achievable rate maximization problem through the one-dimensional linear search. For a special case with single user, we derive a semi closed-form expression of the optimal placement of UAV. Simulation results confirm the accuracy of analytical results and show that the optimal placement of UAV and the average achievable rate significantly depend on the cache capacity at UAV We also show the difference between the performances of the air-to-ground model and the air-to-sea model.

Heterogeneously Reconfigurable Energy Harvester: An Algorithm for Optimal Reconfiguration

We propose a heterogeneously reconfigurable energy harvester which contains multiple energy harvesting (EH) blocks, each comprised of multiple EH circuits in parallel to be optimized for different input power ranges. Practical EH circuits have their own favorable input power range due to turn-on sensitivity and saturation effects. To account for this, we present the necessary conditions for efficient configuration of an energy harvester, and then propose an algorithm for optimal reconfiguration of the energy harvester. Furthermore, adaptive time switching and mode switching problems are formulated in order to maximize the average achievable rate under the self-powering condition. Our proposed energy harvester and algorithm can be applied to low-power Internet-of-Things (IoT) devices with wireless EH capability for self-sustainability, which will be a key enabler for realizing a battery-free IoT network.

Performance Analysis of 5G Mobile Relay Systems for High-Speed Trains

To provide high data rate for high-speed trains (HSTs), it is required to use emerging wireless communication systems, such as the fifth generation (5G). An asymmetric 5G mobile relay system is investigated for HSTs, where the mobile relay is deployed at the HST to avoid high penetration loss of the direct link between the base station (BS) and the users (UE) inside carriages. The sub-6GHz frequency is utilized for the BS-relay link while the relay-UE link adopts the millimeter wave frequency. Therefore, the BS-relay link experiences $\kappa $ - $\mu $ fading and the relay-UE link experiences static fluctuating two-ray fading. Moreover, the channel aging effect is considered due to the mobility of HST. For the considered system, we first study the exact statistical characterizations of the end-to-end signal-to-noise ratios. Then, we derive exact closed-form expressions for key performance metrics, such as outage probability, average bit-error rate, and average achievable rate per unit bandwidth. The significant effects of channel aging, system and channel parameters on the mobile relay system are revealed from theoretical analysis and are further illustrated by simulation results. Our investigation reveals that the mobile relay system is a promising network architecture for HST communications and can provide steady and high-speed data provisioning to HST passengers against the significant bottleneck of channel aging.

UAV-Supported Clustered NOMA for 6G-Enabled Internet of Things: Trajectory Planning and Resource Allocation

The sixth-generation (6G) communication requires supporting massive Internet of Things (IoT) devices and extremely differentiated IoT applications for the air–space–ground integrated network. Relying on the aerial superiority, unmanned aerial vehicle (UAV) is capable of acting as an aerial base station (BS) and supporting IoT deployment in remote and disaster areas. A UAV-supported clustered nonorthogonal multiple access (C-NOMA) system is put forward in this article. Specifically, the UAV provides services to IoT terminals as an aerial BS based on the wireless-powered communication (WPC) technique. According to this system, we propose a synergetic scheme for UAV trajectory planning and subslot allocation. Our goal is to maximize the uplink average achievable sum rate of IoT terminals by synergistically planning UAV trajectory and subslot duration, while guaranteeing the uplink achievable sum rate and the UAV mobility constraints. As the formulated problem suffers nonconvexity and complication, an efficient iterative algorithm is proposed to address it. First, for fixed UAV trajectory, all the terminals are clustered and a subslot allocation algorithm based on the Lagrange multiplier and bisection method is proposed. Then, for a fixed clustering state and subslot duration, we optimize the UAV trajectory. Finally, we solve these two subproblems alternatively until the objective function converges. The effectiveness of the proposed scheme in the UAV-supported C-NOMA system is verified by the numerical results.

Performance Analysis of Massive MIMO Multi-Way Relay Networks With Low-Resolution ADCs

High power consumption and hardware cost have motivated using low-resolution analog-to-digital converters (ADCs) for practical massive multiple-input multiple-output (mMIMO) systems. In this paper, we consider a general mMIMO multi-way relaying system with a multi-level mixed-ADC architecture in which each antenna is connected to an ADC pair with an arbitrary resolution. By leveraging on Bussgang's decomposition theorem and Lloyd-Max algorithm for quantization, tight closed-form approximations are derived for the average achievable rates of zero-forcing (ZF) relaying considering both perfect and imperfect channel state information (CSI). To handle such a challenging setup, we develop a novel method for the achievable rate analysis using distributions of the singular values of Gaussian matrices and properties of Haar matrices. We demonstrate that the average achievable rate has an almost linear relation with the square of the average of quantization coefficients pertaining to the ADC resolution profile. In addition, in the medium to high SNR region, the ADC resolutions have a more significant effect on the rate compared to the number of antennas. Our work also reveals that the performance gap between the perfect and imperfect CSI cases is smaller for lower ADC resolutions, hence imperfect CSI is better tolerated at lower resolutions.

The average achievable rate of multi-antenna two-way relay networks with interference alignment

The large system analysis (LSA) has recently been shown to be a very useful tool for computing the average achievable rate. In this paper, we use LSA to derive the users' average achievable rate of multi-antenna two-way relay networks with interference alignment (IA), and we then derive the rate expressions under both equal power allocation and optimal power allocation. It is shown that the obtained closed-form rate expressions are functions of the average signal-to-noise ratio (SNR) for each data stream. Extensive simulation studies show that the average achievable rate expressions derived through LSA provide accurate estimates of the average achievable rate for two-way relay networks with interference alignment.

Deployment Model and Performance Analysis of Clustered D2D Caching Networks Under Cluster-Centric Caching Strategy

Device-to-Device (D2D) communication has become a promising candidate in future cellular networks to improve spectrum efficiency and energy efficiency, while reducing the latency. As the capacity of D2D user equipments (DUEs) increases, it makes DUEs caching possible, and it can offload traffic from macro base stations, perform computation-intensive and latency-critical tasks. In this paper, in-band communication is considered, and the Poisson cluster process is utilized to model and analyze the clustered D2D networks under cluster-centric caching strategy. Firstly, we use the Thomas cluster process to model cellular user equipments (CUEs) and DUEs, and give a deployment scheme of clustered D2D caching networks. Secondly, the aggregated interference of the typical D2D receiver is analyzed in the clustered D2D networks. Then the Laplace transform of the aggregated interference is analyzed, and the expressions of coverage probability, average achievable rate and cache hit probability of the typical D2D receiver are deduced. The simulation results show that we can adjust the path loss exponent, densities of DUEs and CUEs, transmitting power of CUEs, mean of simultaneously active transmitters in each cluster and Zipf exponent to improve the performance of clustered D2D caching networks.

Reconfigurable Intelligent Surface Assisted UAV Communication: Joint Trajectory Design and Passive Beamforming

Thanks to the line-of-sight (LoS) transmission and flexibility, unmanned aerial vehicles (UAVs) effectively improve the throughput of wireless networks. Nevertheless, the LoS links are prone to severe deterioration by complex propagation environments, especially in urban areas. Reconfigurable intelligent surfaces (RISs), as a promising technique, can significantly improve the propagation environment and enhance communication quality by intelligently reflecting the received signals. Motivated by this, the joint UAV trajectory and RIS's passive beamforming design for a novel RIS-assisted UAV communication system is investigated to maximize the average achievable rate in this letter. To tackle the formulated non-convex problem, we divide it into two subproblems, namely, passive beamforming and trajectory optimization. We first derive a closed-form phase-shift solution for any given UAV trajectory to achieve the phase alignment of the received signals from different transmission paths. Then, with the optimal phase-shift solution, we obtain a suboptimal trajectory solution by using the successive convex approximation (SCA) method. Numerical results demonstrate that the proposed algorithm can considerably improve the average achievable rate of the system.

A Novel Cooperative HARQ Protocol for Free-Space Optical Broadcasting Systems

In this paper, we propose a new hybrid automatic repeat request (HARQ) transmission protocol for broadcasting systems over free space optical (FSO) channels, which is applicable to both incremental redundancy (IR) and chase combining (CC) schemes. In traditional optical HARQ systems, upon receiving a non-acknowledgment (NACK) signal from a given user, the corresponding data packet is retransmitted from the central node to that user. However, in the proposed transmission protocol, called cooperative interuser retransmission protocol (CIRP), the optical users cooperate in the ARQ process. Specifically, instead of relying on the central node, a user who successfully decoded the original data packet and whose distance from the NACK issuing user is smaller than that of the central node, is invited to retransmit this packet to the latter user. This interuser cooperation, in fact, leverages the distance-dependent scintillation effect and path loss, which critically impact FSO channels and degrade the receiver's signal-to-noise ratio (SNR) as distance increases. We provide a detailed performance analysis of both the proposed and traditional protocols in terms of the achievable average sum rate and the next round probability of success. Our numerical results demonstrate that the former outperforms the latter for both IR and CC schemes under various turbulence conditions as well as in the presence of pointing errors.

Molecular communication in three-dimensional diffusive channel with mobile nanomachines

A three-dimensional (3-D) diffusive mobile-molecular communication system is considered inside the unbounded environment. We consider a point transmitter and a perfectly absorbing spherical receiver which can move randomly in any of the three coordinates. The closed-form expression for expected hitting rate for 3-D unbounded communication channel with nanomachines mobility is derived. The performance of considered system is further evaluated in terms of probability of detection (PD), probability of false alarm (PFA), and probability of error (Pe). The system is further analyzed in terms of average mutual information and average maximum achievable rate. Furthermore, an optimum decision threshold, at which minimum probability of error and maximum information rate occur is also derived. The analytical results are verified through particle-based and Monte-Carlo simulations.

Performance analysis and SINR‐based power allocation strategies for downlink NOMA networks

This study analyses the performance of downlink non-orthogonal multiple-access (NOMA) networks over independent but not necessarily identically distributed Rayleigh fading channels by deriving closed-form expressions for the average signal-to-interference-plus-noise ratio (SINR), average achievable rate, and outage probability of all network users. Moreover, SINR-based power allocation strategies are studied. Specifically, the optimisation problems of max–min SINR, multi-objective SINR, sum-SINR and proportional-fairness-SINR maximisation under minimum SINR constraints are formulated and shown to be non-convex. Additionally, the problems of total power and sum-SINR minimisation are also formulated. Particularly, the formulated problems take the form of linear-fractional programming problems. By applying intelligent reformulation techniques, these problems have been reformulated into convex optimisation problems, and thus efficiently solved. Numerical evaluations are presented to validate the derived closed-form expressions for the different performance metrics, which are found to be in agreement with the network simulation results. More importantly, it has been demonstrated that the user with the best channel conditions achieves full diversity order, whereas all the other users achieve diversity orders equivalent to their ordered channel conditions. Finally, the reformulated power allocation strategies are evaluated, and shown to coincide with the original problem formulations.

Secure Communication in Cooperative SWIPT NOMA Systems with Non-Linear Energy Harvesting and Friendly Jamming.

This paper studies the secure communication of a non-orthogonal multiple-access (NOMA) relaying system in the presence of an eavesdropper in which the NOMA communication between a source and two users is assisted by an energy-harvesting (EH) relay. The relay extracts a part of its received signal strength using a power-splitting (PS) policy then harvests energy using a non-linear EH (NLEH) circuit. A friendly jammer sends jamming signals to help secure communication. The jammer is exploited as an additional energy source. A store-and-transmit (SaT) scheme which allows the EH relay to perform energy storing and information transmitting is proposed. For performance evaluation, the closed-form expressions for three metrics, secrecy outage probability (SOP), average achievable secrecy rate (AASR) and average stored energy (ASE) are derived. These results enable studies on the effects of various system parameters, such as NOMA power-allocation factors, target secrecy rates, jammer’s location, and relay’s power levels, on the system performance.

Achievable Secrecy Rate Region for Buffer-Aided Multiuser MISO Systems

In this paper, we consider a buffer-aided multiuser multiple-input single-output (MISO) network consisting of one multi-antenna access point (AP) and multiple single-antenna users, in which the AP is provisioned with data buffers for temporarily storing the data for each user either from the upper layer applications or the message by the AP. The data for one specific user must be kept confidential from all other unintended users. For such a system, we aim at maximizing the long-term average achievable secrecy rate region by carefully designing the flow control, the information signal and artificial noise beamforming, as well as the user selection. To address this issue, we first transform the time average optimization problem into a real-time one by using the Lyapunov optimization framework. Then it is proposed to decompose the optimization problem into several sub-problems by using the optimization decomposition technique. Although the information signal and artificial noise beamforming sub-problem is non-convex, we show that it can be decomposed into a two-stage optimization problem to effectively solve it by using the exact line search and DC (difference of two convex functions) algorithms. Moreover, we extend the average secrecy rate region maximization problem to the worst-case scenario, in which all unintended users are colluding in eavesdropping. Our analysis discloses that, there exists an inherent tradeoff between the average achievable secrecy rate region and the average queueing length. It is shown that a better average secrecy rate region can be realized by fully taking advantage of the buffer-aided transmission potentials in the MISO network, if a certain queueing delay is tolerable.