The increasing diversity of vertical applications in Beyond 5G (B5G) networks has driven widespread adoption of wireless network emulators for developing and evaluating innovative solutions. However, the effectiveness of these solutions heavily depends on the precise parameters configuration, accurate network model design, and the fidelity of the emulation process. Furthermore, achieving real-time resource allocation for heterogeneous traffic remains a significant challenge. To address these complexities, the Open Radio Access Network (O-RAN) concept has gained prominence, leveraging enhanced programmability of RAN functionalities to enable data-driven, intelligent control loops in cellular networks. In this context, we propose ORBIT-DT, an Open RAN-Based Intelligent Twin - Digital Twin, to address the challenges of accurate modeling and resource allocation in B5G networks. Leveraging the open-source Colosseum platform, we design and emulate the ORBIT-DT of POWDER, a publicly available over-the-air sub-6GHz indoor/outdoor testbed. Through extensive experiments, we validate the performance of the proposed ORBIT-DT across various wireless scenarios including eMBB, mMTC, and URLLC slices, comparing it with its Physical Twin (PT). Results demonstrate the ORBIT-DT's ability to support large-scale data collection and achieve a high degree of fidelity, with an average similarity of up to 98.8% in downlink throughput, underscoring its effectiveness as a realistic and reliable representation of the PT.

In this paper, we investigate the feasibility of utilizing distributed reconfigurable intelligent surfaces (RISs) to assist the broadcast communication between a multiple-antenna base station (BS) and multiple users. In this context, JoBNet, a novel deep neural network (DNN) that aims at solving the non-convex optimization problem of maximizing the total spectral efficiency is proposed for the first time. In particular, unlike existing DNNs which are only capable of computing one configuration at a time, JoBNet is able to jointly output the beamforming at BS and phase shifts at multiple RISs simultaneously. Moreover, JoBNet operates based on unsupervised deep learning, hence, it requires no label for training. The numerical results show that JoBNet enjoys a satisfactory while providing a low-latency. In addition, the distributed RIS system provides a substantial enhancement in the spectral efficiency compared to the collocated RIS system where all the phase shift elements are utilized in a compact area.

This article studies secure communication in an Internet of Things (IoT) network, where the confidential signal is sent by an active refracting reconfigurable intelligent surface (RIS)-based transmitter, and a passive reflective RIS is utilized to improve the secrecy performance of users in the presence of multiple eavesdroppers. Specifically, we aim to maximize the weighted sum secrecy rate by jointly designing the power allocation, transmit beamforming (BF) of the refracting RIS, and the phase shifts of the reflective RIS. To solve the nonconvex optimization problem, we propose a linearization method to approximate the objective function into a linear form. Then, an alternating optimization (AO) scheme is proposed to jointly optimize the power allocation factors, BF vector, and phase shifts, where the first one is found using the Lagrange dual method, while the latter two are obtained by utilizing the penalty dual decomposition method. Moreover, considering the demands of green and secure communications, by applying Dinkelbach’s method, we extend our proposed scheme to solving a secrecy energy maximization problem. Finally, simulation results demonstrate the effectiveness of the proposed design.

This article presents a general system framework that lays the foundation for reconfigurable intelligent surface (RIS)-enhanced broadcast communications in Industrial Internet of Things (IIoTs). In our system model, we consider multiple sensor clusters co-existing in a smart factory where the direct links between these clusters and a central base station (BS) are blocked completely. In this context, a RIS is utilized to reflect signals broadcast from BS toward cluster heads (CHs) which act as a representative of clusters, where BS only has access to the statistical distribution of the channel state information (CSI). An analytical upper bound of the total ergodic spectral efficiency (SE) and an approximation of outage probability are derived. Based on these analytical results, two algorithms are introduced to control the phase shifts at RIS, which are the Riemannian conjugate gradient (RCG) method and the deep neural network (DNN) method. While the RCG algorithm operates based on the conventional iterative method, and the DNN technique relies on unsupervised deep learning (DL). Our numerical results show that both algorithms achieve satisfactory performance based on only statistical CSI. In addition, compared to the RCG scheme, using DL reduces the computational latency by more than ten times with an almost identical total ergodic SE achieved. These numerical results reveal that while using the conventional RCG method may provide unsatisfactory latency, and the DNN technique shows much promise for enabling RIS in ultrareliable and low-latency communications (URLLC) in the context of IIoTs.

This article proposes a novel Industrial Internet of Things framework to monitor the machine health conditions (MHCs) in a smart factory. The framework utilizes the reconfigurable intelligent surface (RIS) to address propagation blockages while employing a novel power mapping scheme and an autoencoder to facilitate the transmission and classification of the MHCs. Analytical and numerical analyses are then performed to study the ergodic capacity (primary information) and the MHC accuracy (secondary information) in terms of the RIS size ($K$) and the transmit power ($P$). We observe that the accuracy of detecting MHCs does not change significantly with$K$and$P$, implying that the MHC alerts can be efficiently conveyed in parallel with the primary information. In contrast, a careful choice of different power mapping levels is necessary in order to achieve the two main goals: 1) reasonably high data rate for primary transmission and 2) high accuracy for secondary MHC information.

Digital twin (DT) technology has recently gathered pace in the engineering communities as it allows for the convergence of the real structure and its digital counterpart throughout their entire life-cycle. With the rapid development of supporting technologies, including machine learning (ML), 5G/6G, cloud computing, and Internet of Things, DT has been moving progressively from concept to practice. In this article, a DT framework based on cloud computing and deep learning (DL) for structural health monitoring is proposed to efficiently perform real-time monitoring and proactive maintenance. The framework consists of structural components, device measurements, and digital models formed by combining different submodels, including mathematical, finite element, and ML ones. The data interaction among physical structure, digital model, and human interventions are enhanced by using cloud computing infrastructure and a user-friendly web application. The feasibility of the proposed framework is demonstrated via case studies of damage detection of model bridge and real bridge structures using DL algorithms, with high accuracy of 92%.

Smart structural health monitoring (SHM) for large-scale infrastructure is an intriguing subject for engineering communities thanks to its significant advantages such as timely damage detection, optimal maintenance strategy, and reduced resource requirement. Yet, it is a challenging topic as it requires handling a large amount of collected sensors data continuously, which is inevitably contaminated by random noises. Therefore, this study developed a practical end-to-end framework that makes use of physical features embedded in raw data and an elaborated hybrid deep learning model, namely 1-DCNN-LSTM, featuring two algorithms—convolutional neural network (CNN) and long-short term memory (LSTM). In order to extract relevant features from sensory data, the method combines various signal processing techniques such as the autoregressive model, discrete wavelet transform, and empirical mode decomposition. The hybrid deep learning 1-DCNN-LSTM is designed based on the CNN’s capacity of capturing local information and the LSTM network’s prominent ability to learn long-term dependencies. Through three case studies involving both experimental and synthetic data sets, it is demonstrated that the proposed approach achieves highly accurate damage detection, as accurate as the powerful 2-D CNN, but with a lower time and memory complexity, making it suitable for real-time SHM.Note to Practitioners—This article aims to develop a practical data-driven method for automatically monitoring the operational state of structures. In order to achieve consistently and highly accurate results in performing different tasks for diverse structures, we combine underlying features in both time and frequency domains extracted from measured signal vibration data. Three popular data featuring methods are combined to achieve the diversity gain which would not be possible with each individual method. As the vibration is usually measured by long time-series signals, the most efficient deep learning architecture for time-series signal, namely long-short term memory (LSTM), is considered for this work. Besides, each structure has its own dynamic properties, i.e., eigenfrequencies, around which the most relevant information is in the frequency domain, thus convolutional neural network specifically designed for capturing local information is used in combination with LSTM, forming a hybrid deep learning architecture. The applicability and effectiveness of the proposed approach are supported by three case studies with different types of structures, showing highly accurate damage detection with reduced resource requirements. These advantages can be valuable for developing a model for live monitoring of structural health in the future life-line infrastructures.

This paper investigates a secure wireless-powered multiantenna multicasting system, where multiple power beacons (PBs) supply power to a transmitter in order to establish a reliable communication link with multiple legitimate users in the presence of multiple eavesdroppers. The transmitter has to harvest radio frequency energy from multiple PBs due to the shortage of embedded power supply before establishing its secure communication. We exploit a novel and practical scenario that the PBs and the transmitter may belong to different operators and a hierarchical energy interaction between the PBs and the transmitter is considered. Specifically, the monetary incentives are required for the PBs to assist the transmitter for secure communications. This leads to the formulation of a Stackelberg game for the secure wireless-powered multiantenna multicasting system, where the transmitter and the PB are modeled as leader and follower, respectively, each maximizing their own utility function. The closed-form Stackelberg equilibrium of the formulated game is then derived, where we study various scenarios of eavesdroppers and legitimate users that can have impact on the optimality of the derived solutions. Finally, numerical results are provided to validate our proposed schemes.

In this paper, motivated by recent developments in physical layer (PHY) security, we study the achievable secrecy rate of a multi-power level cognitive radio network (CRN) based on stochastic geometry distribution. We consider a realistic transmission scheme with multiple levels of transmission power. Additionally, having multi-level power strategy can help improve security as eavesdroppers will find it more difficult to recognize the exact power level of the legitimate users. We derive the achievable secrecy rate in an additive white Gaussian noise channel for a cognitive radio model. Furthermore, the cumulative distribution function of the achievable secrecy rate between the primary transmitter and receiver is studied. Finally, we investigate the outage probability of secrecy capacity of the legitimate user from a secure communication graph point of view.

Considering simultaneous wireless information and power transfer (SWIPT), we study a multiple-input- single-output (MISO) secrecy channel which consists of a multi-antenna trans- mitter and a cooperative jammer (CJ), multiple multi-antenna energy receivers (ERs), i.e., potential eavesdroppers, and multiple single-antenna co-located receivers (CRs). Both transmitter and CJ send the intend signal with artificial noise (AN) and jamming signal to interfere with the ERs. All receivers (CRs and ERs) adopt a power splitter to decode information and harvest power simultaneously. We exploit AN and CJ to facilitate efficient wireless energy transfer and secure transmission. Our aim is to maximize the minimum harvested energy among all ERs and CRs subject to the total power constraints at the transmitter and CJ while guaranteeing the minimum secrecy rate for each CR above its requirement. By incorporating norm-bounded channel uncertainty model, we propose a joint design of robust secure transmission. The original problem is solved by a two- step approach. In the first step, the proposed problem is reformulated as a sequence of semidefinite programs (SDPs). In the second step, the proposed problem can be handled by one-dimensional search to attain the optimal solution. Simulation results indicate that the performance of the proposed scheme outperforms that of separated AN-aided or CJ-aided scheme.

This paper investigates a wireless powered sensor network (WPSN), where multiple sensor nodes are deployed to monitor certain external environment. A multi-antenna power beacon (PB) provides the power to these sensor nodes during wireless energy transfer (WET) phase, and then the sensor nodes employ the harvested energy to transmit their own monitoring information to one fusion center (FC) during wireless information transfer (WIT) phase. We maximize the system sum throughput of the sensor network considering two different scenarios, i.e., PB and the sensor nodes belong to the same/different service operator(s). For the first scenario, we propose an approach to jointly design the energy beamforming and the energy time allocation which is a convex optimization problem. We further develop a closed- form solution for the proposed sum throughput maximization. For the second scenario, where PB and the sensor nodes belong to the different service operators, we formulate the sum throughput maximization as Stackelberg-game-based and Social welfare schemes, in which we are then able to derive their equilibriums in closed-form solutions. Finally, numerical results are provided to validate the performance of our proposed schemes.

In order to provide ubiquitous communication, seamless connectivity is now required in all environments including highly mobile networks. By using vertical handover techniques, it is possible to provide uninterrupted communication as connections are dynamically switched between wireless networks as users move around. However, in a highly mobile environment, traditional reactive approaches to handover have been found to be inadequate. Therefore, the proactive handover techniques are actively being investigated in the context of next generation mobile networks. This paper presents a new methodology to support proactive resource allocation for emerging future networks such as 5G by allowing base stations to calculate the probability of contention based on the demand for network resources. The proposed approach uses Markov chains to model the contention and results are obtained showing enhanced system performance in terms of throughput and mean response time.

This paper considers multiple-input multiple-output (MIMO) full-duplex (FD) two-way secrecy systems. Specifically, both multi-antenna FD legitimate nodes exchange their own confidential message in the presence of an eavesdropper. Taking into account the imperfect channel state information (CSI) of the eavesdropper, we formulate a robust sum secrecy rate maximization (RSSRM) problem subject to the outage probability constraint of the achievable sum secrecy rate and the transmit power constraint. Unlike other existing channel uncertainty models, e.g., norm- bounded and Gaussian-distribution, we exploit a moment-based random distributed CSI uncertainty model to recast our formulate RSSRM problem into convex optimization frameworks based on a Markov's inequality and robust conic reformulation, i.e., semidefinite programming (SDP). In addition, difference-of-concave (DC) approximation is employed to iteratively tackle the transmit covariance matrices of these legitimate nodes. Simulation results are provided to validate our proposed FD approaches.

In this paper, we propose beamforming schemes to simultaneously transmit data to multiple information receivers (IRs) while transfering power wirelessly to multiple energy-harvesting receivers (ERs). Taking into account the imperfection of the instantaneous channel state information, we introduce a probabilistic-constrained optimization problem to minimize the total transmit power while guaranteeing data transmission reliability, secure data transmission, and power transfer reliability. As the proposed optimization problem is non-convex and has an infinite number of constraints, we propose two robust reformulations of the original problem adopting safe-convex-approximation techniques. The derived robust formulations are in semidefinite programming forms, hence, they can be effectively solved by standard convex optimization packages. Simulation results confirm the superiority of the proposed approaches to a baseline scheme in guaranteeing transmission security.

This paper considers an underlay access strategy for coexisting wireless networks where the secondary system utilizes the primary spectrum to serve its users. We focus on the practical cases where there is uncertainty in the estimation of channel state information (CSI). Here the throughput performance of each system is limited by the interference imposed by the other, resulting in conflicting objectives. We first analyze the fundamental tradeoff between the tolerance interference level at the primary system and the total achievable throughput of the secondary users. We then introduce a beamforming design problem as a multiobjective optimization to minimize the interference imposed on each of the primary users while maximizing the intended signal received at every secondary user, taking into account the CSI uncertainty. We then map the proposed optimization problem to a robust counterpart under the maximum CSI estimation error. The robust counterpart is then transformed into a standard convex semi-definite programming. Simulation results confirm the effectiveness of the proposed scheme against various levels of CSI estimation error. We further show that in the proposed approach, the trade-off in the two systems modelled by Pareto frontier can be engineered by adjusting system parameters. For instance, the simulations show that at the primary system interference thresholds of -10 dBm (-5 dBm) by increasing number of antennas from 4 to 12, the secondary system throughput is increased by 3.3 bits/s/channel-use (5.3 bits/s/channel-use).

This paper investigates the security at the physical layer of cooperative relay communications. Inspired by the principle of physical-layer network coding (PNC), we propose a new secure relaying scheme, namely secure PNC-based modify-and-forward (SPMF). In the proposed scheme, the relay node linearly combines the decoded data from the source node with an encrypted key before conveying the mixed data to the destination node. As both the linear PNC operation and encrypted key at the relay are unknown to the eavesdropper, the SPMF scheme provides a double security level in the system. Particularly, taking into account the practical scenario of the imperfect knowledge shared between the relay and destination, the secrecy outage probability (SOP) of the proposed SPMF scheme is analysed and evaluated in comparison with modify-and-forward, cooperative jamming, decode-and- forward and direct transmission schemes. The proposed scheme is shown to achieve a performance improvement of up to 3 dB when compared to the conventional schemes under imperfect knowledge of shared information between the nodes.

Device to Device (D2D) communication has been proposed as an underlay to Long-Term evolution (LTE) network as a means of harvesting the proximity, reuse and hop gains. However, D2D communication can also serve as a technology for providing public safety and disaster relief services. In this article, the basic concepts of D2D communications are first introduced and then existing fundamental works on disaster communication are discussed. We focus on the performance of the network architecture by utilizing the relay assisted transmission which can effectively enhance the capacity and power saving of the network. We also propose the distance based strategy to reduce the computational complexity and power transmission. Finally, simulation results are provided to verify the proposed architecture.

In this paper, we consider a multi-level power allocation scheme for cognitive users in the cognitive radio networks. The proposed system uses a new frame structure to improve overall throughput of the cognitive radio systems. We propose a strategy in which, the licensed user can transmit with multiple levels of power which seems to be more realistic and practical. In this work, the proposed strategy also allows cognitive users to choose different power levels according to their receiving energy. The optimal achievable rate under the constraints of average transmit power at the cognitive users and average interference temperature to the licensed users is investigated. Simulation results indicate the enhancement in the throughput of the system compared to conventional strategy.

This study investigates cooperative spectrum sensing (CSS) in cognitive wireless radio networks (CWRNs). A practical system is considered where all channels experience Nakagami‐ m fading and suffers from background noise. The realisation of the CSS can follow two approaches where the final spectrum decision is based on either only the global decision at fusion centre (FC) or both decisions from the FC and secondary user (SU). By deriving closed‐form expressions and bounds of missed detection probability (MDP) and false alarm probability (FAP), the authors are able to not only demonstrate the impacts of the m ‐parameter on the sensing performance, but also evaluate and compare the effectiveness of the two CSS schemes with respect to various fading parameters and the number of SUs. It is interestingly noticed that a smaller number of SUs could be selected to achieve the lower bound of the MDP rather using all the available SUs while still maintaining a low FAP. As a second contribution, they propose a SU selection algorithm for the CSS to find the optimised number of SUs for lower complexity and reduced power consumption. Finally, numerical results are provided to demonstrate the findings.

In this paper, a game theory-based cooperation scheme is investigated to enhance the physical layer security in both primary and secondary transmissions of a cognitive radio network (CRN). In CRNs, the primary network may decide to lease its own spectrum for a fraction of time to the secondary nodes in exchange of appropriate remuneration. We consider the secondary transmitter node as a trusted relay for primary transmission to forward primary messages in a decode-and-forward fashion and, at the same time, allows part of its available power to be used to transmit artificial noise (i.e., jamming signal) to enhance primary and secondary secrecy rates. In order to allocate power between message and jamming signals, we formulate and solve the optimization problem for maximizing the secrecy rates under malicious attempts from eavesdroppers. We then analyze the cooperation between the primary and secondary nodes from a game-theoretic perspective where we model their interaction as a Stackelberg game with a theoretically proved and computed Stackelberg equilibrium. We show that the spectrum leasing based on trading secondary access for cooperation by means of relay and jammer is a promising framework for enhancing security in CRNs.

This paper investigates double-threshold-based energy detector for cooperative spectrum sensing mechanisms in cognitive wireless radio networks. We first propose a hybrid double-threshold-based energy detector (HDTED) to improve the sensing performance at secondary users (SUs) by exploiting both the local binary/energy decisions and global binary decisions feedback from the fusion center (FC). Significantly, we derive closed-form expressions and bounds for the probabilities of missed detection and false alarm considering a practical scenario where all channel links suffer from Rayleigh fading and background noise. The derived expressions not only show the improved performance achieved with the HDTED scheme but also enable us to analyze the impacts of the number of the SUs and the fading channels on the cooperative spectrum sensing performance. Furthermore, based on the derived bounds, we propose an optimal SU selection algorithm for forwarding the local decisions to the FC, which helps reduce the number of forwarding bits for a lower-complexity signaling. Finally, numerical results are provided to demonstrate the validity of the analytical findings.

In this paper, we study simultaneous data transmission and power transfer for multiple information receivers (IRs) and energy-harvesting receivers (ERs) in cellular networks. We propose an optimization problem to maximize a linear combination of the useful signal power at each IR and total received power at each ER subject to the following three sets of constraints: i) data reliability by maintaining the required level of signal to interference plus noise ratio (SINR) for all IRs; ii) information security by keeping leakage SINR levels of all IRs at every ER below a predefined value, which helps prevent possible eavesdroppers, i.e., ERs, from detecting information aimed for the IRs; and iii) power consumption by guaranteeing that the transmit power at each base station is within its available budget. Using semidefinite relaxation (SDR) technique, we then transform the proposed problem into a convex form. We further prove that the transformed problem always yields rank-one optimal solution. Hence, our approach does not require any computationally expensive randomization procedure, as usually utilized in a typical SDR method, in obtaining optimal solutions. Simulation results indicate that the proposed approach prevails conventional scheme in terms of providing higher IRs' total throughput, higher received power level at each ER and more secure for the transmission of information.

This paper investigates the game theory based cooperation method to optimize the PHY security in both primary and secondary transmissions of a cognitive radio network (CRN) that include a primary transmitter (PT), a primary receiver (PR), a secondary transmitter (ST), a secondary receiver (SR) and an eavesdropper (ED). In CRNs, the primary terminals may decide to lease its own given bandwidth for a fraction of time to the secondary nodes in exchange for appropriate remuneration. We consider the ST as a trusted relay for primary transmission in the presence of the ED. The ST forwards the source message in a decode-and-forward (DF) fashion and, at the same time, allows part of its available power to be used to transmit an artificial noise (i.e., jamming signal) to enhance secrecy rates and avoid the employment of a separate jammer. In order to allocate power between message and jamming signals, we formulate and solve optimization problem of maximizing the primary secrecy rate (PSR) and secondary secrecy rate (SSR). We then analyse the cooperation between the primary and secondary transmitters from a game-theoretic perspective, where we model their interaction as a Stackelberg game. Finally, we apply numerical examples to illustrate the impact of the Stackelberg game on the achievable PSR and SSR. It shows that spectrum leasing based on trading secondary access for cooperation by means of relay and jammer is a promising framework for enhancing secrecy rate in cognitive radio.

Due to the enormous potential of improving the spectral utilization by using Cognitive Radio (CR), designing adaptive access system and addressing its physical layer security are the most important and challenging issues in CR networks. Since CR transceivers need to transmit over multiple non-contiguous frequency holes, multi-carrier based system is one of the best candidates for CR's physical layer design. In this paper, we propose a combined chaotic scrambling (CS) and chaotic shift keying (CSK) scheme in Orthogonal Frequency Division Multiplexing (OFDM) based CR to enhance its physical layer security. By employing chaos based third order Chebyshev map which allows optimum bit error rate (BER) performance of CSK modulation, the proposed combined scheme outperforms the traditional OFDM system in overlay scenario with Rayleigh fading channel. Importantly, with two layers of encryption based on chaotic scrambling and CSK modulation, large key size can be generated to resist any brute-force attack, leading to a significantly improved level of security.

The rapid advances in technology lead to a mass-market adoption of the multi-radio high-end smartphone devices and an exponential increase in the mobile broadband data traffic. In the search for a solution to cope with this explosion of data traffic, Device-to-Device (D2D) communications become an attractive approach for enhancing the performance of cellular networks. The emerging of WiFi Direct framework introduced new opportunities for mobile-to-mobile opportunistic offloading. In this context, this paper proposes ECO-M, an Energy-efficient Cluster-Oriented solution for Multimedia delivery in a LTE D2D environment using WiFi Direct. Experimental test-bed measurements and numerical results show the efficiency of such a solution in terms of energy efficiency, battery discharge and battery lifetime when compared with a standard LTE environment. Subjective tests were carried out to study not only the impact of user perceived quality on the various multimedia quality levels choices but also the impact of user preferences in terms of energy conservation versus multimedia quality.

This paper investigates downlink performance of a heterogeneous wireless cellular network (HWCN) consisting of multi-tier cells operating within various indoor and outdoor propagation environment models. The coverage probability of the practical HWCN is derived using stochastic geometry modeling. The derived expressions not only characterise the effects of building infrastructures and transmission environment on the coverage region in practice but also enable us to propose an optimal power allocation at cells in different tiers. Specifically, a heuristic algorithm is developed for the power allocation at the tiered cells within various propagation models to minimise the total power consumption. The proposed scheme is shown to achieve a lower total power consumption saving up to 45% for a given target coverage probability of a specific region when compared to the equal power allocation technique.

This paper proposes a hybrid double-threshold based energy detector (HDTED) for cooperative spectrum sensing over imperfect channels in cognitive wireless radio networks (CWRNs). The proposed HDTED improves the sensing reliability in CWRNs by exploiting both local decisions at secondary users (SUs) in either binary or energy values and global binary decisions feedback from fusion centre. Particularly, we consider a practical scenario where all channel links suffer from fading and noise. By deriving closed-form expressions and bounds for the probabilities of missed detection and false alarm, we not only show the improved performance achieved with the HDTED scheme but also validate the effects of the number of the SUs and the fading channels on the overall sensing performance.

This paper investigates power allocation for reliable downlink transmission in cellular networks subject to quality-of-service (QoS) constraints. The reliability of data transmissions is assured by hybrid automatic repeat request protocol with incremental redundancy (HARQ-IR). By developing and evaluating the effective throughput of the HARQ-IR protocol for the downlink transmission under buffer-limited QoS constraints, we propose a novel adaptive power allocation algorithm to efficiently exploit the available resources when only limited channel state information (CSI) is available. The proposed algorithm, based on monotonic optimisation, allows near-optimal performance to be achieved with reasonably low complexity.

This paper investigates power allocation for reliable downlink transmission in cellular networks subject to quality-of-service (QoS) constraints. The reliability of data transmissions is assured by hybrid automatic repeat request protocol with incremental redundancy (HARQ-IR). By evaluating the effective throughput of the HARQ-IR protocol for the downlink transmission under QoS constraints, we propose a novel power allocation policy to efficiently exploit the available resources. Furthermore, based on the derived effective throughput, optimization problem is formulated and solved, in which all channels are effectively allocated to all users. Finally, numerical results are provided to support theoretical findings.

One of the main challenges towards reliable multicast transmissions over wireless networks is the dynamics of the wireless links (e.g. wireless errors, fading, interference, collisions, etc.) that can cause retransmissions overhead over the limited available bandwidth. To this end this paper considers the scenario of wireless multicast networks where network coding is applied to improve network throughput. We first propose a novel cross-layer optimisation framework for network topology design in order to optimise the wireless multicast rate, data flow of the wireless links, energy supply and node lifetime. The performance of the proposed solution is evaluated and compared against other solutions from the literature in terms of system throughput, total energy, and network lifetime. The results show that the proposed cross-layer design outperforms the other schemes involved, reaching up to 50% increase in the system throughput.

This paper is concerned with cooperative spectrum sensing (CSS) in cognitive wireless radio networks (CWRNs). A practical scenario is investigated where all channels suffer from Nakagami-m fading. Specifically, we analyse the probabilities of missed detection and false alarm for two CSS schemes where the collaboration is carried out either at fusion centre (FC) only or at both the FC and secondary user (SU). By deriving closed-form expressions and bounds of these probabilities, we not only show that there are significant impacts of the m-parameter of Nakagami fading realisation for different channel links on the sensing performance but also evaluate and compare the effectiveness of the two CSS schemes with respect to various fading parameters and the number of SUs. Finally, numerical results are provided to validate the theoretical analysis and findings.

This paper investigates double-threshold based energy detection for cooperative spectrum sensing in cognitive wireless radio networks. We first propose a hybrid double-threshold based energy detector (HDTED) to improve sensing performance at the secondary users (SUs) by exploiting both their local decisions and the global binary decisions at the fusion centre (FC). We then derive closed- form expressions for the probability of missed detection and the probability of false alarm considering a practical scenario where all channel links suffer from Rayleigh fading. The derived expressions not only show the improved performance but also enable us to develop an optimal SU selection algorithm for forwarding the local decisions to the FC. Finally, numerical results are provided to demonstrate the validity of the analytical findings.

This paper investigates relay selection for reliable data transmission in relay-assisted multisource multicast networks (RMMNs) where multiple source nodes distribute information to a set of destination nodes with the assistance of multiple relay nodes. Hybrid automatic repeat request with incremental redundancy (HARQ-IR) is used and supported by either a physical-layer network coding (PNC) or an analog network coding (ANC) technique employed at the relays. By deriving efficiency metrics of the HARQ-IR protocols, we propose relay selection schemes for RMMNs to minimize the transmission delay and energy consumption. Simulation results are provided to analyse each relay selection scheme.

In this study, the authors consider cooperative transmission in cognitive wireless relay networks (CWRNs) over frequency‐selective fading channels. They propose a new distributed space‐time–frequency block code (DSTFBC) for a two‐hop non‐regenerative CWRN, where a primary source node and multiple secondary source nodes convey information data to their desired primary destination node and multiple secondary destination nodes via multiple cognitive relay nodes with dynamic spectrum access. The proposed DSTFBC is designed to achieve spatial diversity gain as well as allow for low‐complexity decoupling detection at the receiver. Pairwise error probability is then analysed to study the achievable diversity gain of the proposed DSTFBC for different channel models including Rician fading and mixed Rayleigh–Rician fading.

This paper considers channel quality indicator (CQI) reporting for data exchange in a two-way multi-relay network. We first propose an efficient CQI reporting scheme based on network coding, where two terminals are allowed to simultaneously estimate the CQI of the distant terminal-relay link without suffering from additional overhead. In addition, the transmission time for CQI feedback at the relays is reduced by half while the increase in complexity and the loss of performance are negligible. This results in a system throughput improvement of 16.7% with our proposed CQI reporting. Upper and lower bounds of the mean square error (MSE) of the estimated CQI are derived to study performance behaviour of our proposed scheme. It is found that the MSE of the estimated CQI increases proportionally with the square of the cardinality of CQI level sets although an increased number of CQI levels would eventually lead to a higher data rate transmission. On the basis of the derived bounds, a low-complexity relay selection (RS) scheme is then proposed. Simulation results show that, in comparison with optimal methods, our suboptimal bound-based RS scheme achieves satisfactory performance while reducing the complexity at least three times in case of large number of relays.

In this paper, we consider cooperative transmission in cognitive wireless relay networks (CWRNs) over frequency-selective fading channels. We propose a new distributed space-time-frequency block code (DSTFBC) for a two-hop nonregenerative CWRN, where a primary source node and multiple secondary source nodes convey information data to their desired primary destination node and multiple secondary destination nodes via multiple cognitive relay nodes with dynamic spectrum access. The proposed DSTFBC is designed to achieve spatial diversity gain as well as allow for low-complexity decoupling detection at the receiver. Pairwise error probability is then analysed to study the achievable diversity gain of the proposed DSTFBC for different channel models including Rician fading and mixed Rayleigh-Rician fading.

This paper considers relay positioning in wireless butterfly networks consisting of two source nodes, a relay node and two destination nodes. The relay-assisted data transmission from two source nodes to two destination nodes is carried out based on either physical-layer network coding (PLNC) or analog network coding (ANC) techniques. The reliability of communications in wireless network-coded butterfly networks (WNCBNs) is assured by applying hybrid automatic repeat request protocol with incremental redundancy (HARQ-IR). In this paper, we first evaluate the total energy consumption (EC) of both PLNC and ANC schemes in WNCBNs. Based on the derived EC, we develop algorithms that optimize the location of the relay node for PLNC and ANC schemes in order to minimize the total EC for a green communication system subject to node location and power allocation constraints. Finally, simulation results are provided which identify the optimized relay locations for various scenarios of node location and power allocation in the WNCBN.

In this paper, we investigate the energy-delay tradeoff (EDT) of data transmissions in wireless butterfly networks consisting of two source nodes, a relay node and two destination nodes. Two network coding (NC) techniques, namely physical-layer NC (PLNC) and analog NC (ANC), are exploited to reduce the number of transmissions at the relay by half. Additionally, hybrid automatic repeat request with incremental redundancy (HARQ-IR) is applied to assure the reliability of data transmissions in wireless network-coded butterfly networks (WNCBNs). By deriving the EDT of both PLNC and ANC schemes in WNCBNs, we evaluate not only their energy efficiency, but also the effectiveness of the relay positions in WNCBNs. It is found that the PLNC scheme is more energy efficient than both the ANC and direct transmission (DT) schemes when the relay is located either at the centre or close to the destinations. In addition, it is shown that both the PLNC and ANC schemes are shown to be less energy efficient than the DT scheme when the relay is located near the sources.

This study is concerned with cooperative spectrum sensing (CSS) mechanisms in three‐hop cognitive wireless relay networks (CWRNs). The data transmission from a source to a destination is realised with the aid of two layers of cognitive radio (CR) users which are in the transmission coverage of two primary users. The authors first propose a new CSS scheme for a layer of CR users to improve the spectrum‐sensing performance by exploiting both local decisions at the CR users and global decisions at the fusion centre. Particularly, the probabilities of missed detection and false alarm for a practical scenario where all sensing, reporting and backward channels suffer from Rayleigh fading are derived. The derived expressions not only show that the proposed CSS achieves a better sensing performance than the conventional scheme but also characterise the effects of the fading channels on the sensing reliability. Furthermore, the authors propose a CSS scheme for two CR layers in a three‐hop CWRN using binary operations to help reduce one phase of sensing for a higher system throughput.

This paper considers retransmission mechanisms in wireless regenerative relay networks. The retransmission can be realized in a cooperative manner with the assistance of all available relays. This may result in a high overall power consumption due to a considerable number of overlapped packets in the retransmission, especially when the number of relays is large. In this paper, we propose a cooperative retransmission (CR) scheme based on relay cooperation and binary XOR operation to significantly reduce the number of packets to be retransmitted for a more power efficient system with non-overlapped retransmission. Particularly, we derive the error probability of the retransmission decision at the source and relays, which shows that the proposed CR scheme also improves the reliability of the retransmission. Finally, simulation results are presented to verify the analytical findings and show that the proposed CR scheme reduces the number of retransmissions and removes overlapped retransmitted packets.

This paper considers data exchange between two terminals in a nonregenerative two-way relay network. We first propose two efficient channel quality indicator (CQI) reporting schemes based on XOR and superposition coding for single-relay networks. These schemes allow two terminals to simultaneously estimate the CQI of the distant link without incurring additional overhead. In addition, the transmission time for CQI feedback is reduced by half while the loss of performance is negligible. Upper and lower bounds of the mean square error (MSE) of the estimated CQI are derived to analyze various effects on the performance of the proposed schemes. We then extend our MSE analysis to multi-relay networks where a low-complexity relay selection scheme is proposed based on the derived bounds. Simulation results show that, in comparison with conventional methods, this suboptimal bound-based scheme achieves satisfactory performance while reducing the complexity at least three times in case of large number of relays.

This paper is concerned with block acknowledgement (ACK) mechanisms in wireless regenerative relay networks. In an N-relay network, a total of (2N+1) block ACK packets is required to acknowledge the data transmission between source and destination nodes via the N-relay nodes. In this paper, the authors propose a block ACK scheme based on network coding (NC) to significantly reduce the ACK overheads by N block ACK packets. In addition, this achieves a reduction of N(N–1) computational operators. Particularly, we derive the error probability of the determination of the packets to be retransmitted at the source and relays, which shows that the NC-based scheme also improves the reliability of block ACK transmissions. Furthermore, asymptotic signal-to-noise (SNR) scenarios for forward links are considered and a general expression of error probability in multi-relay networks is derived for each SNR scenario. Finally, simulation results are presented to verify the analytical findings and demonstrate a lower number of data retransmissions for a higher system throughput.

In this paper, we study the power allocation for multiband coded OFDM systems. With limited feedback, we propose an effective power allocation method across OFDM bands to maximize the throughput and achieve the quality of service target. To facilitate the proposed method, two optimization algorithms based on greedy and dynamic programming principles are discussed. The trade-off between performance and complexity is provided. Simulation results show that the proposed power allocation mechanism allows a signal to noise ratio gain of 2 dB at a goodput of 2.5 bit per second per Hz over the multiband OFDM systems with equal power allocation.

This paper considers block acknowledgement (BACK) mechanisms in wireless regenerative relay networks. Conventionally, a total of (2N+1) BACK packets are required in wireless regenerative N-relay networks to acknowledge the data transmission between the source and destination via the relays. In this paper, based on network coding (NC) we propose an efficient BACK scheme to significantly reduce the required acknowledgement load by N BACK packets. Importantly, by deriving the error probability of the determination of the packets to be retransmitted at the source or relays, it is found that the utilised NC helps improve the reliability of BACK transmissions. Furthermore, some asymptotic scenarios of the forward links are considered and a general expression of error probability in multi-relay networks is derived for each scenario. Finally, simulation results are shown to verify the analytical findings.

In this paper, we consider the minimum mean square error (MMSE)-based signal detection in the 3rd generation long term evolution (LTE) downlink systems. An analysis bound of error probability is derived. The diversity order is also obtained and analysed at high signal to noise ratios (SNRs). The analysis is then extended to the case of successive interference cancellation (SIC)-based detection. Simulation results show that the analysis bound is very tight and consistent with numerical bit error rate.

The IEEE Wireless Access in Vehicular Environments (WAVE) family of standards is the leading worldwide standardisation effort in terms of Dedicated Short Range Communications (DSRC). WAVE aims at defining a common set of requirements and functionalities, in order to enable intercommunication and interoperability between nodes in a Vehicular Ad hoc Network (VANET). Despite the concept of service as an abstraction of a shared resource or capability is central to WAVE and that the architecture it outlines spans the complete protocol stack, the standards, per se, do not provide all of the flexibility required by an otherwise heterogeneous, dynamic and distributed system built around the service abstraction. This paper extends that flexibility by describing a reactive location protocol based on existing WAVE elements, conceived in the wider context of a Service-Oriented Architecture (SOA) for VANET. The protocol complements the proactive location scheme that is already part of WAVE and exemplifies how complex objectives can be attained from the basic set of features in a WAVE-compliant node.

Abstract In this paper, we investigate multi‐group linear turbo equalization using single antenna interference cancellation (SAIC) techniques to mitigate the intercell interference for multi‐carrier code division multiple access (MC‐CDMA) cellular systems. It is important for the mobile station to mitigate the intercell interference as the performance of the users close to cell edge is mainly degraded by the intercell interference. The complexity of the proposed iterative detector and receiver is low as the one‐tap minimum mean square error (MMSE) equalizer is employed for mitigating the intracell interference, while a simple group interference canceller is used for suppressing the intercell interference. Simulation results show that the proposed iterative detector and receiver can mitigate the intercell interference effectively through iterations for both uncoded and coded signals. Copyright © 2009 John Wiley & Sons, Ltd.

In order to derive low complexity multiple input multiple output (MIMO) detectors, we combine two additional approaches, namely lattice reduction (LR) and list within the framework of the successive interference cancellation (SIC) based detection in this paper. The resulting detector, called the SICList-LR based detector, provides a near maximum likelihood (ML) performance with a significantly reduced complexity. For example, the signal-to-noise ratio (SNR) loss of the proposed detector compared to the ML detector is less than 0.3 dB for a 4 × 4 MIMO systems with 16-quadrature amplitude modulation (QAM) at a bit error rate of 10-3while complexity is about half of that of the conventional LR based detectors.

In this paper, using diagonal signal repetition with Alamouti code employed as building blocks, we propose a high-rate groupwise space-time block code (GSTBC) which can be effectively decoded by a low-complexity successive interference cancellation (SIC) based receiver. The proposed GSTBC and SIC based receiver are jointly designed such that the diversity repetition in a GSTBC can induce the dimension expansion to suppress interfering signals as well as to obtain diversity gain. Our proposed scheme can be easily applied to the case of large number of antennas while keeping a reasonably low complexity at the receiver. It is found that the required minimum number of receive antennas is only two for the SIC based receiver to avoid the error floor in performance. The simulation results show that the proposed GSTBC with SIC based receiver obtains a near maximum likelihood (ML) performance while having a significant performance gain over other codes equipped with linear decoders.

In this paper, using diagonal signal repetition, we propose a high-rate groupwise space-time block code (GSTBC) which can be effectively decoded by a low-complexity successive interference cancellation (SIC) based receiver. The proposed GSTBC and SIC based receiver are jointly designed such that the diversity repetition in a GSTBC can induce the dimension expansion to suppress interfering signals as well as to obtain diversity gain. Our proposed scheme can be easily applied to the case of large number of antennas while keeping a reasonably low complexity at the receiver. It is found that the required minimum number of receive antennas is only two for the SIC based receiver to avoid the error floor in performance. The simulation results show that the proposed GSTBC with SIC based receiver obtains a near maximum likelihood (ML) performance while having a significant performance gain over other codes equipped with linear decoders.

In this paper, a novel analytic framework of cross-layer design between physical and network layers is devised to enable an efficient communication link under various channel qualities. Based on the principle of maximum entropy (ME), the performance modelling and evaluation of a wireless channel with bursty multiple traffics and automatic repeat request (ARQ) traffic flows subject to intelligent buffer management scheme (IBMS) is investigated. As the packet error rate varies depending on channel quality, better performance of IBMS can be achieved under adaptive modulation (AM). In this context, an open queueing network model (QNM) is proposed to a GE/GE/1/N/HoL/CBS (T) queueing system with finite capacity, threshold T, head of line (HoL) and complete buffer sharing (CBS) to model the wireless channel with IBMS corresponding to ARQ protocol under various wireless channel qualities. Subject to appropriate GE-type queueing and delay theoretic mean value constraints, ME analytic solutions are characterized and new closed form expressions for the state and blocking probability distributions are determined. Typical numerical experiments are included to verify the credibility of the ME solutions at 95% confidence intervals and to compare wireless network performance with ARQ traffic handling schemes.

Facing the challenge of providing broadband access to high speed vehicle on motorway scenario, this paper discloses a fibre network employing star-tree architecture with a central control system in the middle to connect fixed line data collection part on one side and the wireless points to transmit information needed to on road vehicles on the other side. To implement the system, an effective coverage scheme is presented by using radio-over-fibre (RoF) technologies, in which time slot distributor (TSD) plays a key role in avoiding co-channel interference. With adaptive modulation approaches under different channel condition, a buffer management scheme (BMS) could achieve a better system performance. Furthermore, within new frame structure, four handover indicators are added to deal with the fast handovers involved among remote antenna units (RAUs) governed by single base station (BS) and handover between different BSs.

In this paper, we propose a novel iterative detection scheme for multiple-input multiple-output intersymbol interference (MIMO-ISI) channels using soft-decision correlations. We design a soft decision feedback detector (SDFD) combined with an additional probabilistic data association (PDA) detector to exchange the soft decisions in an iterative manner. It is shown that this combined detection scheme outperforms the conventional decision feedback detector (DFD) and approaches the ideal case where feedback decisions are perfectly correct.

In this paper, using the turbo principle, different iterative receiver designs are proposed for orthogonal frequency division multiplexing (OFDM) systems under a time-varying channel environment. In the presence of carrier frequency offset (CFO) error, the iterative receiver can improve the performance as better channel estimation and CFO compensation are available through iterations. The mitigation of the CFO is carried out via the two proposed methods - time domain compensation (TDC) and frequency domain cancellation which uses a decision feedback equalizer (DFE-FDC). The complexity of the DFE-FDC method is higher than that of the TDC approach as more operations are required to update the DFE coefficients. However, our simulation results show that the DFE-FDC outperforms the TDC for each iteration.