In large-scale Internet of Things (IoT) deployments, efficiently allocating computing resources to IoT devices, while preserving the integrity and utility of their data, remains a critical challenge. This paper introduces a novel online probabilistic model designed to handle uncertainties in both demand and resource availability within IoT networks, where the computing tasks of requesting devices (RDs) are fulfilled by serving devices (SDs). The proposed model integrates stochastic elements and formulates an optimization problem that aims to minimize the number of active serving devices required for task offloading, subject to the constraints of available computing resources. To further enhance decision-making, the model incorporates the concept ofValue of Information (VoI)to ensure that the informational utility of each device’s data remains above a predefined threshold during task processing. The optimization problem is addressed using a heuristic algorithm. In scenarios where no serving device is immediately available, tasks are temporarily stored in a buffer and deferred to the next time slot, with their waiting time being tracked. This task allocation process is inspired by bin-packing algorithms, which are known for their efficiency in resource management and task scheduling. Moreover, the paper evaluates the performance of the proposed solution under worst-case conditions through feasibility analysis, thereby demonstrating its robustness. Two buffering strategies, First-In First-Out (FIFO) and Last-In First-Out (LIFO), are also examined to model task retrieval and execution behavior. Results show that adopting the FIFO strategy can reduce the average waiting time by approximately 50%. Overall, the proposed framework provides a reliable and scalable task computing service, with each serving device capable of supporting, on average, four requesting devices under typical operating conditions.

Reliable, ultra-low-latency communication in Vehicular Ad-hoc Networks (VANETs) is critical for autonomous vehicle safety, yet existing routing protocols struggle with high overhead and frequent link disruptions in dynamic environments. A key limitation is their failure to leverage the rich sensor data already available in modern vehicles for network-level coordination. This paper introduces a novel segmentation-based routing framework that directly addresses these challenges by transforming in-vehicle sensor data into a shared, high-resolution network topology. Our core contribution is a dynamic road occupancy matrix, created by dividing roadways into velocity-adaptive, single-vehicle segments, which provides all nodes with a unified and near real-time view of the traffic environment. This matrix is disseminated efficiently using a Time Division Integrated Sensing and Communication (TD-ISAC) framework inspired by 5G Sidelink. We propose a hybrid Lagrangian Relaxation and Branch-and-Bound algorithm to dynamically optimize the TD-ISAC frame, balancing the trade-off between sensing accuracy and communication throughput. To further enhance topological precision and mitigate vehicle mobility effects, the framework integrates a Kalman Filter and Transformer model for predictive position estimation and employs a reserve relay mechanism to ensure multi-hop link stability. Comprehensive simulations demonstrate that our framework significantly outperforms state-of-the-art protocols. Notably, it reduces end-to-end delay by up to 68% compared to ZRP and 41% against the TD-ISAC-based Starling Flocks, while simultaneously decreasing routing overhead. This dual improvement enables a more efficient and robust network for safety-critical applications.

Covert communication is an emerging security solution to prevent or decrease the warden’s detection rate. Unmanned aerial vehicle (UAV), as an aerial covert transmitter, should jointly optimize the trajectory to ensure covertness. The eavesdropper-equipped UAV attempts to adversarially detect covert communication by adjusting its distance and setting the detection threshold. Due to the variation of the air-to-ground channel, the data status may have an expiration time. Information freshness is important in guaranteeing covertness, such as identifying threats and tracking movements. To quantify information freshness, age of Information (AoI), is represents the elapsed time since the most recent successfully decoded information was updated. We investigate UAV-assisted covert communication to minimize AoI with an aerial eavesdropper for the first time. However, to ensure the eavesdropper’s error detection rate, UAV-enabled beamforming employs the power-domain non-orthogonal multiple access (PD-NOMA) technique to cover the covert user by a public user. PD-NOMA technique significantly improves the user’s AoI, too. The joint optimization problem contains non-convex constraints and coupled optimization variables, including UAV trajectory, beamforming design, and the user’s AoI. We have developed an efficient alternating optimization technique to address it. Numerical results demonstrate the impact of the main parameters on the performance of the proposed system.

In this paper, the physical layer security (PLS) in visible light communication (VLC) is investigated where the eavesdropper (ED) is assisted with the reconfigurable intelligent surface (RIS). Here, in the relay-aided system model, the ED is equipped with a new RIS type. The model also accounts for the received signal-dependent noise. For various trusted relaying schemes such as decode-and-forward (DF), amplify-and-forward (AF), and cooperative jamming (CJ), closed-form expressions of the lower and upper bounds on secrecy rate regions are derived under power constraints. Moreover, the effect of channel state information (CSI) uncertainty is analysed, as a practical condition. Considering this effect, it is demonstrated that the CJ scheme resists eavesdropping by increasing the noise and interference on the illegitimate user. The simulation results show that applying the RIS technique does not increase the signal-to-noise ratio of the ED in the CJ scheme in comparison with DF and AF schemes.

Mutual random phase injection can be considered an appropriate solution for tackling the low key generation rate issue in physical layer key generation schemes. In this paper, the confidentiality of a phase-based group secret key generation scheme has been analyzed by employing a geometric secrecy approach in a static environment. Accordingly, we exploit this approach to achieve some common randomness quantities in our group model. For this purpose, the process of key generation is defined for a star topology. Next, both vulnerability and secrecy regions are identified. To address the challenge of security vulnerability in non-proximity areas due to the spatial correlation in static environments with dominant line-of-sight (LoS), multiple carrier frequencies have been employed at the channel probing stage to enhance the secrecy regions. Finally, the key error probability is provided not only to establish an appropriate evaluation of the quality of the generated keys but also to show the efficiency of our proposed scheme in comparison with previous works.

This paper presents an analysis of the Age of Information (AoI) in a wireless sensor network consisting of multiple IoT sensors. This network consists of three nodes: a wireless power source (WPS), sensors, and an access point (AP). We exploit hybrid visible light communication/radio frequency (VLC/RF) for the sensors with the orthogonal frequency bands. Power domain non-orthogonal multiple access (PD-NOMA) and successive interference cancellation (SIC) are also adopted for the sensors and the AP. Finally, we present two main optimization problems for average AoI with the sensor's transmit power constraint. We analyze the average AoI in a hybrid VLC/RF network, and we obtain the global optimum value for the average AoI of each sensor by considering the probability of sensors being charged, the probability of choosing the links, calculating the probability of successful decoding. According to the optimization results based on the Particle Swarm Optimization (PSO) method, the average AoI for each sensor and the total average AoI in the proposed system are reduced by 10% and 15%, respectively.

In this paper, we propose a novel cooperative resource sharing technique in multi-tier edge slicing networks which is robust to imperfect channel state information (CSI) caused by user equipments’ (UEs) mobility. Due to the mobility of UEs, the dynamic requirements of their tasks, and the limited resources of the network, we propose a smart joint dynamic pricing and resources sharing (SJDPRS) scheme that can incentivize the infrastructure provider (InP) and mobile network operators (MNOs). Aiming to maximize the profits of UEs, MNOs and the InP under the task fulfillment constraints, we formulate an optimization problem by deploying the multi-objective optimization method where in addition to the resource allocation variables, the price values are also the optimization variables. To solve the problem, we adopt a new deep reinforcement learning (DRL) method based on a carefully designed reward function. The simulation results indicate that the proposed resource sharing scenario can increase total profits for the UEs, MNOs, and InP in comparison to non-cooperative case, while also providing almost complete fairness among the players. In particular, as compared to the baselines and benchmarks, the profits for each network component (MNO, InP, and UEs), under fairness considerations, are enhanced by 75%, 79%, and 76%, respectively.

In practice, Internet of Things (IoT) applications may face two different hostile attacks, i.e., overhearing the broadcasted data and detecting the presence of data communication. Previous works have assumed that only one of these attacks is present in the network and have addressed these attacks separately. In this article, we investigate the security of a simple but practical IoT-based point-to-point communication which is facing with the above-mentioned two attacks under some realistic assumptions. In other words, we aim to protect the data against two adversary nodes, namely Eve (who tries to capture the broadcasted data) and warden Willie (who tries to detect the presence of data communication between legitimate nodes). To tackle these attacks, we jointly employ the information-theoretic security and covert communication techniques. To hide information from Willies, we force the source to transmit its message in the selected time slot and the multiple-antennas cooperative jammer to inject jamming during all time slots contentiously which leads to deceive Eves and Willies jointly. To enhance the performance of this security design, we formulate an optimization problem, with the goal of maximizing the secrecy rate subject to power constraints at the source and jammer, while satisfying a covert communication requirement. Since the mentioned optimization problem is nonconvex, we propose an algorithm to solve it. Then, to obtain further insights, we extend our proposed system model to noncolluding and colluding Willies. Next, we study a practical communication scenario, where the source has uncertainty about Willie’s location and knows the channel state information (CSI) of Eves imperfectly. Our numerical results highlight that a more accurate estimation of Willie’s location has a more positive efficacy on the secrecy performance compared to the case with more accuracy of Eves’ CSI estimation.

A visible light communication (VLC) system with an improved noise model applied to physical layer security (PLS) is investigated, where secure beamforming signals with superposition coding are used. In the improved model, the output signal follows Gaussian distribution, but its variance is signal-dependent. Two different methods are proposed to obtain lower and upper bounds on the secrecy rate of the strong user for direct transmission. Under some constraints, closed-form expressions of the lower and upper bounds on secrecy rate regions for various (trusted cooperative half-duplex) relaying schemes are derived. Moreover, the scenarios of blockage/outside coverage are included, and the relevant security performances are discussed. Numerical results show that the lower and upper bounds on secrecy rate regions are tight enough, and the cooperative jamming is superior over other relaying schemes.

5G and beyond wireless networks are the upcoming evolution for the current cellular networks to provide the essential requirement of future demands such as high data rate, low energy consumption, and low latency to provide seamless communication for the emerging applications. Heterogeneous cloud radio access network (H-CRAN) is envisioned as a new trend of 5G that uses the advantages of heterogeneous and cloud radio access networks to enhance both spectral and energy efficiency. In this paper, building on the notion of effective capacity (EC), we propose a framework in orthogonal frequency division multiple access (OFDMA)- non-orthogonal multiple access (NOMA) based H-CRAN to meet these demands simultaneously. Our proposed approach is to maximize the effective energy efficiency (EEE) while considering spectrum and power cooperation between a macro base station (MBS) and radio remote heads (RRHs). To solve the formulated problem and to make it more tractable, we transform the original problem into an equivalent subtractive form via Dinkelbach algorithm. Afterward, the combinational framework of distributed stable matching and successive convex algorithm (SCA) is then adopted to obtain the solution of the equivalent problem. Hereby, we propose an efficient resource allocation scheme to maximize energy efficiency while maintaining the delay quality of service (QoS) requirements for all users. The simulation results show that the proposed algorithm can provide a non-trivial trade-off between delay and energy efficiency in OFDMA-NOMA based H-CRAN systems in terms of EC and EEE and the spectrum and power cooperation improves EEE of the proposed network. Moreover, our proposed solution complexity is much lower than the optimal solution and it suffers a very limited gap compared to the optimal method.

Network slicing (NwS) is one of the main technologies in the fifth-generation of mobile communication and beyond (5G+). One of the important challenges in the NwS is information uncertainty which mainly involves demand and channel state information (CSI). Demand uncertainty is divided into three types: number of users requests, amount of bandwidth, and requested virtual network functions workloads. Moreover, the CSI uncertainty is modeled by three methods: worst-case, probabilistic, and hybrid. In this paper, our goal is to maximize the utility of the infrastructure provider by exploiting deep reinforcement learning (DRL) algorithms in end-to-end NwS resource allocation under demand and CSI uncertainties. Enhanced mobile broadband (eMBB) requires high data rates. The uncertainties we argued above have a direct negative impact on the data rate and our objective function. Therefore, we focus primarily on eMBB. Additionally, we also consider ultra-reliable low latency communications (uRLLC) and massive machine-type communication (mMTC). The proposed formulation is a non-convex mixed-integer non-linear programming problem. To perform resource allocation in problems that involve uncertainty, we need a history of previous information. To this end, we use a recurrent deterministic policy gradient (RDPG) algorithm, a recurrent and memory-based approach in DRL. Then, we compare the RDPG method in different scenarios with soft actor-critic (SAC), deep deterministic policy gradient (DDPG), distributed, and greedy algorithms. The simulation results show that the SAC method is better than the DDPG, distributed, and greedy methods, respectively. Moreover, the RDPG method out performs the SAC approach on average by 70%.

In this article, we investigate joint information-theoretic secrecy and covert communication in a single-input-multioutput (SIMO) system where a transmitter (Alice) is communicating with two legitimate users (Bob and Carol). We consider that an untrusted user and a warden node are also present in the network attempting to attack the secure and covert communications to Bob and Carol, respectively. Specifically, Bob requires secure communications such that his messages from Alice are not decoded by the untrusted user, while Carol requires covert communications such that her messages from Alice are not detected by the warden. To do so, we consider that Alice transmits Carol's messages during selected time slots to hide them from the warden while also transmitting Bob's messages in each time slot contentiously. We formulate an optimization problem with the aim of maximizing the average rate subject to a covert communication requirement and a secure communications constraint. Since the proposed optimization problem is nonconvex, we utilize successive convex approximation to obtain a tractable solution. Moreover, we extend our proposed system model to multiple antenna Alice scenario and find beamforming vectors so that the average sum rate is maximized. Furthermore, we consider practical assumptions that Alice has imperfect knowledge of the warden's location and imperfect channel state information (CSI) of Bob and Carol. Our numerical examples highlight that the imperfect CSI at Carol has a more detrimental impact on the average rate compared to imperfect CSI at Bob.

In this paper, we consider a cooperative multiple-input single-output (MISO) heterogeneous communication network based on the power domain non-orthogonal multiple access (PD-NOMA). We aim to investigate a resource allocation problem regarding the uncertainty of the channel state information at the transmitter (CSIT) and the imperfect SIC case. Since there is an essential need for low-complexity algorithms with reasonably good performance for the extremely complex access architectures, we propose two novel methods based on matching game with externalities and successive convex approximation (SCA) to realize the hybrid scheme where the number of the cooperative nodes is variable. Moreover, we propose a new matching utility function to manage the interference caused by cooperative networks and PD-NOMA. We also devise two robust beamforming techniques to cope with the channel uncertainty based on the worst-case and stochastic-case scenarios. Simulation results evaluate the performance and the sensibility of the proposed methods and demonstrate that although the performance of the proposed distributed matching algorithm is slightly inferior to that of the SCA type, the complexity of the matching theory approach is substantially lower than that of the latter one.

In this paper, we address the problem of joint covert communication and secure transmission in untrusted relaying networks when multiple wardens exist in the network. We first consider a system model consisting of one source, one untrusted amplify-and-forward relay, one destination, and one warden. For covert communications, our aim is to prevent the warden from detecting the presence of communications via the source-relay-destination link. For secure transmission, our aim is to prevent the untrusted relay from decoding the source signal. To satisfy these requirements, we propose that the destination and the source inject jamming signals during the source-to-relay and relay-to-destination transmission phases, respectively. For the considered system model, we propose a power allocation strategy to maximize the secrecy rate and satisfy the covert requirements in both of the phases. Given that the proposed optimization problem is non-convex, we employ the successive convex approximation (SCA) approach to derive a tractable solution. To obtain further insights, we generalize our analytical results to consider multiple untrusted relays and multiple wardens. We focus on two scenarios of non-colluding and colluding wardens. Our results highlight that as the number of relays increases, the achievable secrecy rate increases while the average detection error probability decreases. This is a novel observation of a fundamental trade-off between covert requirement and secrecy performance.

Diffusion-based molecular communication (DMC) is one of the most promising approaches for realizing nano-scale communications for healthcare applications. The DMC systems in in-vivo environments may encounter biological entities that release molecules identical to the molecules used for signaling as part of their functionality. Such entities in the environment act as external noise sources from the DMC system's perspective. In this paper, the release of molecules by external bio-inspired noise sources is particularly modeled as a compound Poisson process. The impact of compound Poisson noise sources (CPNSs) on the performance of a point-to-point DMC system is investigated. To this end, the noise from the CPNS observed at the receiver is characterized. Considering a simple on-off keying modulation and formulating symbol-by-symbol maximum likelihood (ML) detector, the performance of the DMC system in the presence of the CPNS is analyzed. For the special case of CPNS in a high-rate regime, the noise received from the CPNS is approximated as a Poisson process whose rate is normally distributed. In this case, it is proved that a simple single-threshold detector is an optimal ML detector. Our results reveal that in general, adopting the conventional simple homogeneous Poisson noise model may lead to overly optimistic performance predictions, if a CPNS is present.

In this paper, we propose a cross layer energy efficient resource allocation and remote radio head (RRH) selection algorithm for heterogeneous traffic in power domain-non-orthogonal multiple access (PD-NOMA) based heterogeneous cloud radio access networks (H-CRANs). The main aim is to maximize the EE of the elastic users subject to the average delay constraint of the streaming users and the constraints, RRH selection, subcarrier, transmit power, and successive interference cancellation. The considered optimization problem is non-convex, NP-hard, and intractable. To solve this problem, we transform the fractional objective function into a subtractive form. Then, we utilize successive convex approximation approach. Moreover, in order to increase the processing speed, we introduce a framework for accelerating the successive convex approximation for low complexity with the Lagrangian method on graphics processing unit. Furthermore, in order to show the optimality gap of the proposed successive convex approximation approach, we solve the proposed optimization problem by applying an optimal method based on the monotonic optimization. Studying different scenarios show that by using both PD-NOMA technique and H-CRAN, the system energy efficiency is improved.

This study deals with investigating the chirp signal detection obtained from the moving target in the presence of the destructive factor (leakage) and Gaussian noise using the generalised almost‐cyclostationary (GACS) and Hough transform (HT) signal processing altogether (i.e. GACS–HT) approaches. To do so, a receiver was designed hierarchically using the above approach in this study. In this receiver, the detection and extraction of linear frequency modulation takes place in the subspace of the cyclostationary and Hough which have unique characteristics. In order to detect the target, the relative velocity was analysed in the cyclostationary subspace while the relative acceleration was analysed in the Hough space. Due to using the simulation, the behaviour of this receiver was measured by different subspaces for different parameters in the presence of noise and destructive factor. Ultimately, the efficiency of the presented approach was analysed and compared with other approaches. The results indicated that the GACS–HT approach is more efficient than the energy detector approach and in terms of complexity it is almost as complex as the LV transform approach.

In this paper, the tradeoff among the energy efficiency, fairness, harvested energy, and system sum rate is studied. In this regard, various fairness methods, namely, max-min fairness, proportional fairness, and minimum delay potential fairness in power-domain non-orthogonal multiple access-based heterogeneous cellular networks are investigated. In order to perform successive interference cancellation (SIC), we use two ordering approaches and compare their performance. To this end, we propose joint subcarrier and power allocation algorithms to achieve fair energy efficient resource allocation for each fairness method and SIC ordering. Since the proposed optimization problems are non-convex and intractable, the existing methods to solve the convex problems could not be directly used. To overcome this difficulty, an iterative algorithm based on successive convex approximation is used. Moreover, to show the optimality gap of the proposed solution method, an optimal approach based on the monotonic optimization is applied in which we first transform each of the proposed optimization problems into a monotonic optimization problem of canonical form, and then, we obtain the optimal solution of each problem, which coincides with the optimal solution of the original non-convex problem. We finally study the performance of the proposed schemes using simulations for different values of the system parameters.

This study proposes a power control scheme to obtain minimum aggregate power in a system composing of interfering links ( N ‐link) while a target sum‐rate is met. The authors develop an analytical framework for two interfering links which results in the optimal transmission policy. For N > 2, they propose a suboptimal solution based on successive convex approximation for low‐complexity (SCALE) algorithm. They modify the SCALE algorithm to converge to a point satisfying Karush–Kuhn–Tucker conditions when high signal‐to‐noise‐and‐interference approximation of rate function is not valid. They also provide a suboptimal solution based on the geometric programming. They perform numerical evaluations in a dense interference environment and compare the performance of the modified SCALE with that of the SCALE algorithm. They also compare the performance of proposed power control with that of sum‐rate maximisation of interfering links, in which the individual power constraint on each user is considered. The simulation results indicate that the modified SCALE performs better than the SCALE algorithm. The results also demonstrate that the proposed power control can save power comparing to the sum‐rate maximisation in most considered cases.

This paper proposes an iterative detector for uncoded OFDM signals in cooperative networks, where the information symbols are simply partitioned through a time-domain matrix at the OFDM transmitter. We analytically show that our proposed iterative detector at the partner node converges and can completely recover the user's data from its partitioned version, if sufficient redundancy is inserted in the user's data. For efficient use of the redundancy in the user's data, a coded cooperative transmission based on superposition modulation is proposed. Additionally, a closed-form input-output relationship for the partitioning and reconstruction algorithm in the proposed cooperative scenario is derived. We also obtain closed-form expressions for symbol error rate performance of the proposed coded cooperative scenario over Rayleigh frequency-selective fading channels. Numerical comparisons shed light on the relative merits of the proposed coded cooperation under various inter-user and uplink channel conditions.

In this paper, we consider a cooperative diffusion-based molecular communication (MC) network consisting of single source, single decode-and-forward relay, and single destination. The source and the relay nodes use different types of molecules for information transmission. Considering both the relay and the direct links at the destination node, we have two different received signals that can be used by the destination node to retrieve the data transmitted by the source node. Therefore, diversity arises at the destination node. For detection, we adopt the energy detector applying the diversity combining technique. Since the optimum relay position in relay-aided networks plays a crucial role to enhance their performance, we study the relay location optimization problem. We first derive a closed-form expression for the bit error probability of the proposed detection scheme in which the received energy from the source and the relay nodes are linearly combined at the destination node. Then, in order to find the optimum relay position as well as the optimal destination decision threshold for a given number of molecules released by the source and the relay nodes, we formulate a joint optimization problem whose objective is to minimize the bit error probability of the network. To solve this optimization problem, we propose an iterative algorithm based on the block coordinate descent algorithm and study its convergence behavior. Numerical results show that the error performance can be improved by optimizing the position of the relay node. Our analyses help us in designing a reliable cooperative diffusion-based MC network.

In this study, the authors consider the downlink radio resource allocation for heterogeneous traffic in generalised frequency division multiplexing (GFDM)‐non‐orthogonal multiple access (NOMA) based heterogeneous cellular networks. In this scheme, multiple number of users can be allocated on each subcarrier. Two types of traffic are considered, elastic and streaming. The problem of maximising the weighted sum‐rate of elastic users is addressed subject to streaming users minimum rate in addition to subcarrier and transmit power constraints. This problem is a non‐convex NP‐hard optimisation problem. To solve this problem, the authors divide it into two subproblems, subcarrier allocation and power allocation then an iterative algorithm is proposed. Subcarrier allocation is updated by solving an integer linear program, where a successive convex approximation approach is adopted to transform the power allocation subproblem to a sequence of convex subproblems, using one of the three methods, successive convex approximation for low ComplExity, arithmetic‐geometric mean approximation (AGMA) and difference of two concave functions to find the power allocation optimal solutions. Numerical experiments show that the proposed algorithms can improve the system performance. Furthermore, they show that AGMA can achieve a sum‐rate near to the global optimal solution, at the expense of more computational time.

The ergodic resource allocation (ERA) problem for uplink transmission in underlay cognitive radio networks (CRNs) is investigated. The objective is to maximize the ergodic sum-rate of secondary users (SUs) considering the unavailability of perfect channel state information (CSI), and subject to transmit power limitations of SUs, and the interference threshold constraint to guarantee the quality of service of primary users. Since with average-based formulation of ERA, the interference threshold constraint and transmit power limitations of SUs do not hold instantaneously, one can replace the average-based constraints in ERA with their outage-based counterparts. For the uncertainty on the CSI values, we utilize the robust optimization theory where the uncertain parameters are modeled as a sum of the estimated value and error which is assumed to be bounded. We then map the considered ERA problems to their robust counterparts. Generally, the robust approaches degrade the performance (e.g., sum rate of SU), as they conservatively consider the error to be in the maximum extent and try to preserve the constrains under any condition of error (worst-case scenario). We aim to moderate this effect by using appropriate models for uncertain parameters, relaxing the worst-case scenario, and stochastically preserving the constraints. Moreover, robust problems are in general non-convex and suffer from high computational complexity due to the existence of uncertain system parameters. Therefore, we use effective suboptimal approaches to solve them with a reasonable complexity. This includes methods based on chance constraint approach as well as an iterative scheme. The proposed solutions provide a trade-off between robustness, performance, and complexity. Simulation results reveal that by using the proposed schemes, stable sum-rate of SUs in the presence of CSI uncertainties can be achieved while the instantaneous power and interference constraints are met with a desired probability.

The purpose of this paper is analyzing and improving delay quality of service (QoS) provisioning of adaptive selection relaying protocol (SRP) and adaptive incremental relaying protocol (IRP) in single relay networks. In relation to delay QoS provisioning, the concept of effective capacity (EC) is utilized. So, as the first step, we find the EC functions of SRP and IRP and mathematically analyze the ECs to derive the closed form expressions of them which reduce the computational complexity. Then, by the goal of maximizing the ECs or equivalently improving delay QoS provisioning, we propose cross layer adaptive power allocation (APA) schemes as two closed form algorithms for both SRP and IRP strategies. The proposed cross layer APA algorithms depend on the delay QoS constraint and instantaneous channel conditions. Also, by applying the closed form ECs, two cross layer fixed power allocation (FPA) schemes are represented over both SRP and IRP that depend on delay QoS constraint and statistical channel conditions. The numerical results validate the derived closed form equations for the ECs of the protocols and also show that our proposed APA schemes achieve a significant improvement in EC performance of the system with both protocols, especially for stringent QoS requirements.

Abstract Quality of service (QoS) guarantee is the main performance metric for designing future wireless networks. For real time applications over wireless links, statistical delay QoS guarantee is the most important QoS metrics. The main goal of this paper is studying the effects of multi‐decode‐and‐forward‐relaying transmission on delay QoS guarantee and user satisfaction. For this end, we first propose an approach to simplify the analysis of statistical delay QoS guarantee by the use of a curve named QoS analysis curve. The QoS analysis curve of any system is based on its effective capacity (EC) function. So, we derive a closed‐form expression for the EC function of a multi‐decode‐and‐forward‐relay network to reduce the computational complexity of finding this quantity. After that, for improving the QoS guarantee performance of a multi‐decode‐and‐forward‐relaying system, the EC of the system is maximized by the use of power allocation (PA) technique. At first, an adaptive PA (APA) algorithm is proposed in which the source and relays PA policies are derived analytically. Although, the overhead of this algorithm is large, it significantly improves the statistical delay QoS guarantee performance. Then, for the systems that cannot tolerate the required large overhead of APA, a fixed PA scheme is presented, which is based on particle swarm optimization algorithm. There is a tradeoff between providing the delay QoS guarantee and the required overhead, in selecting APA or fixed PA schemes. The numerical results validate our analytical outcomes and evaluate our proposed algorithms.

In this work, we present a mode selection scheme in a hybrid cellular-device to device system. Our model includes a cellular user, a potential device to device user and its receiver. The potential device to device user has different options for its transmission. We introduce a new criteria for mode selection, which has the advantage of being implemented in distributed form. We provide simulation results to evaluate the system performance in terms of sum-rate and individual rates.

Statistical quality of service (QoS) provisioning is a performance metric that determine the user satisfaction as the main purpose of future wireless networks. Effective capacity (EC) is a valuable quantity which helps analysing delay QoS performance as the most popular QoS metric. In this study, the authors concentrate on characterising the delay QoS performance via the EC of uplink transmission mode of individual users in multiuser centralised networks in which the user's transmitted signals may interfere with each other. To reduce the computational complexity of finding EC, the authors first propose closed form expressions for the EC of each user, with or without considering the inter‐symbol interference (ISI). Then, two general algorithms are presented to clarify the relation of EC and QoS guarantee performance of a system in which the way of analysing QoS guarantee performance is explained step‐by‐step. By the use of these algorithms and the obtained closed form EC functions, the authors investigate the statistical delay QoS performance of individual users and the effects of channel conditions and ISI on their performance. The numerical results validate our analytical outcomes in deriving closed form equations and evaluate the offered schemes in characterising delay QoS performance.

In this paper, the effect of channel distribution information (CDI) imperfectness on the performance of wireless networks is investigated. In the literature, ergodic resource allocation problems are solved assuming that perfect CDI is available which might not be a practical assumption. Therefore, we adopt the nonparametric density estimation methods for estimating the channel gain distribution. The estimation is first carried out through the well-known kernel density estimation (KDE) method. Since KDE is too sensitive to contaminated data, we adopt the robust kernel density estimation (RKDE) method. The analysis is performed over an ergodic resource allocation problem framework in the uplink of an orthogonal frequency division multiple access based network. In the proposed problem, the objective is to maximize the average total rate subject to total power constraint for each user. Simulation results indicate that for large enough number of nominal data and a reasonable number of outlier data, RKDE can provide a sum rate very close to the one obtained based on the actual CDI.

A robust Ergodic Resource Allocation (ERA) scheme is proposed in this paper in the framework of an orthogonal frequency division multiple access (OFDMA) based underlay heterogeneous network in which the allocations are made so as to maximize the average network sum-rate while guaranteeing the macro network interference requirements with any desired high probability. In previously proposed ERA schemes, both in conventional and heterogeneous networks, the optimal solution is obtained assuming that average of constraints are satisfied. In a heterogeneous network, this is translated into the fact that instantaneous level of interference on macro users can not be guaranteed, i.e., there is an uncontrolled probability of collision which is not acceptable by macro network. In this paper, we reformulate the ERA problem by replacing the average based constraints, in our case, femto total power constraint and macro interference threshold constraint, with their probabilistic counterparts so that both constraints are satisfied instantaneously with any desired high probability. We consider both cases of continuous and quantized channel state information. The proposed problems are then solved based on three methods, namely, iterative, analytical, and hybrid approaches. The optimality of the proposed methods is also assessed and the iterative approach is shown to have a performance quite close to that of the optimal solution. Simulation results confirm the effectiveness of the proposed scheme to provide a robust instantaneous imposed interference on macro network and a robust femto total transmit power. We also investigate the convergence properties of the proposed iterative approach.

In this paper, we introduce a new cooperative paradigm for secure communication in cognitive radio networks (CRNs) where secondary users (SUs) are allowed to access the spectrum of primary users (PUs) as long as they preserve the secure communication of PUs in the presence of malicious eavesdroppers. To do so, the SU transmission is divided into two hops: at first hop, the SU transmitter sends the information to a relay set and the SU receiver acts as a friendly jammer to disturb the overhearing of eavesdroppers and at the second hop, one of the relays is selected to pass the information to the SU receiver and the SU transmitter acts as a friendly jammer for the PU. In this new setup, the time duration for each hop, the power transmissions of all nodes in CRN, and relay selection at the second hop are allocated in such a way that the secrecy rate of the SU is maximized subject to the minimum required PU's secrecy rate. From primary service perspective, this transforms the possibly disturbing secondary service activities into a beneficial network element. We investigate instantaneous and ergodic resource allocation problems for perfect and imperfect channel state information (CSI). Since these problems are non-convex, we propose a solution based on decomposition of main optimization problem into three subproblems related to the power allocation, time allocation, and relay selection. We show that the power allocation problem can be transformed into a generalized geometric programming (GGP) model via the so-called scaled algorithm and it can be solved very efficiently. Simulation results indicate that in terms of the secondary secrecy rate, the proposed setup outperforms the conventional setup in which the secrecy rate of the PU is not guaranteed.

In this study, the authors present a method to design efficient full‐rate linear dispersion space‐time block codes (LD‐STBCs) in correlated Rayleigh fading channels with simple detection at the receiver. The authors first derive a formula for the achievable capacity of an LD‐STBC coded multi‐input multiple‐output (MIMO) system as a function of correlation at the transmitter and the receiver. Moreover, the authors compute closed‐form bit‐error rate equations for multiple phase shift keying ( M ‐PSK) and multiple quadrature amplitude modulation ( M ‐QAM) schemes. Then, the authors present a method to construct LD‐STBCs over correlated Rayleigh fading MIMO channels. Finally, the authors design LD‐STBCs for two and four transmit antennas. The designed LD‐STBCs enjoy full‐rate, minimum power fluctuation, simple structure, simple processing at the receiver. Moreover, the designed LD‐STBCs for two transmit antennas provide better performance than Alamouti and LYC codes and the designed LD‐STBCs for four transmit antennas provide better performance than TV codes at practical signal‐to‐noise ratios. Simulation results show that when the proposed LD‐STBC for two transmit antennas is concatenated with an efficient outer channel encoder, it provides better performance than LYC code over correlated fading channels.

In this paper, the downlink ergodic resource allocation (ERA) in a relay-assisted OFDMA-based cognitive network is considered with the objective of maximizing the average secondary service sum-rate. This is subject to the average total transmission power constraint and the collision probability constraint on each subcarrier at each hop of transmission to guarantee the primary quality of service with any arbitrarily high probability. In the proposed scheme, no interaction between secondary and primary networks is necessary as opposed to previously proposed frameworks. To reduce the signaling overhead between secondary base station and secondary users, which is considerably higher in relay-assisted networks compared to ordinary networks, we propose to use channel quantization. In channel quantization instead of channel gain values, the index of the fading region corresponding to that value is fed back. Due to the probabilistic nature of the collision probability constraint, the proposed ERA problem cannot be solved by conventional methods such as the dual decomposition method. Hence, we propose two novel sub-optimal solutions called Iterative Approach and Analytical Approach. Simulations results indicate the efficiency of the proposed solutions with the iterative approach slightly outperforming the analytical approach at the expense of higher complexity. We also compare continuous and quantized ERA. Simulation results demonstrate a trade-off between the volume of required feedback information and performance.

This paper proposes a new utility-based fairness criteria for radio resource allocation in underlay CDMA cognitive radio networks based on harmonic mean concept. Then joint rate and power allocation problem is considered for secondary users subject to the QoS and interference threshold constraints. It is shown that the proposed approach yields a better balance between throughput and fairness compared with conventional fairness criteria, namely max-min and proportional fairness.

In this article, radio resource allocation in underlay spectrum sharing based on the orthogonal frequency-division multiple access is studied. A cellular-based secondary service is considered in which the licensed spectrum is opportunistically accessed provided that the imposed interference at the primary service receivers because of secondary service transmissions stays below an interference threshold constraint. The main objective here is to maximise the sum capacity of the secondary service and to find the optimal allocated power, subcarrier and rate across all subcarriers and different secondary users. Three different scenarios are considered based on the availability of the channel state information (CSI) between the secondary service base station and primary receivers. The optimal resource allocation for the case of accurate CSI between the secondary base station and the primary receivers is obtained. To manage more practical situations, in the second considered scenario the authors assume that only the channel distribution information information between the secondary base station and the primary receivers is available at the secondary service base station. In the third scenario the authors further propose a novel algorithm, which controls the collision incidences caused by secondary transmissions owing to lack of CSI in secondary base station. Simulation analyses are also conducted in order to investigate the system performance based on the proposed resource allocation algorithms.

Reliable detection of primary users (PUs) in the presence of interference and noise is a crucial problem in cognitive radio networks. To address the above issue, cooperative spectrum sensing based on cyclostationary feature detection that can robustly detect weak primary signals has been proposed in the literature. Among different cooperative techniques, in this study the authors focus on combination of soft decisions derived based on asymptotic properties of cyclic autocorrelation estimates. The objective is to maximise deflection coefficient performance metric at the fusion centre, where linear combination of cyclostationary soft decisions is performed. Since the proposed method allows for distributed cyclostationarity spectrum sensing, it is more reliable and faster than non-cooperative traditional multi-cycle cyclostationarity detection schemes. To reduce the computational complexity of the exact distribution of proposed test statistic at fusion centre, the authors derive efficient approximations for the distribution under null and alternative hypotheses. Extensive simulation results in different scenarios demonstrate the advantage of the proposed method and confirm the analytic performance characterisations. In addition, the authors study the impact of mobility of cognitive devices on the cyclostationarity of received signals and verify our analysis via simulation.

The authors investigate the effects of an imperfect channel estimate, rendered through the employment of a practical, online training-based minimum mean square error estimator, on uncoded multiple input–multiple output Vertical Bell Laboratories Space-Time architecture with a zero-forcing receiver in the presence of uncorrelated frequency-non-selective Rayleigh block fading. The post-processing signal to interference plus noise ratio and its probability distribution function will be derived using no approximation. Exact closed-form expressions will be provided for the average symbol probability of error for M-ary PAM modulation. For quadrature phase shift keying (QPSK) modulation, the symbol error probability is derived in the form of an integral, which has an analytical solution only when the number of receive antennas equals or exceeds that of the transmit antennas by one and may otherwise be numerically calculated. The average outage probability will be exactly calculated. All this is accomplished by an approximation-free mathematical approach and by taking into account the fundamental limitations between the accuracy of the channel estimate and the channel capacity. Perfect agreement is seen to exist between our analysis and Monte Carlo simulations.

A novel weighted high data rate single-user ultra-wideband transmitted-reference (UWB-TR) system is proposed and its performance in log-normal slow fading channels is investigated, which has not been addressed before. This system employs a novel signalling scheme, which provides a nearly inter-symbol interference (ISI) free-channel response at the receiver and eliminates the need for equalisation. It also enhances the reference pulse quality by employing optimum power allocation. The performance of the proposed system is compared with that of the differential transmitted-reference (DTR) system in IEEE 802.15.3a Channel Model 1 (CM1) both analytically and via simulations by taking into account noise, log-normal slow fading, inter-path/pulse interference (IPI) and ISI. Both analytical and simulation results show that our system significantly outperforms the DTR one. It is shown that the proposed method is robust against small changes in both weighting coefficients and integration interval, whereas the UWB-DTR scheme is too susceptible to such changes in the integration interval.

Abstract In mobile communication systems, mobility modeling is involved in several aspects such as signaling and traffic load analysis. In particular, accurate mobility models are essential for the evaluation of the system design alternatives and network implementation cost issues. In this paper, we propose a mobility model that is appropriate for practical analysis of the mobile systems' design issues. Our model provides different levels of details for the user mobility behavior and can be adapted to any environmental topology. This model considers direction and velocity of the user mobility. The motion direction is modeled based on real street patterns and is described by discrete state Gauss–Markov technique whose parameters are calculated by combining the information derived by the topological map and wireless network performance report (WNPR) of the simulation area. In the proposed method, the user velocity is assumed to be the average velocity that is found based on traffic condition and type of the street. The computational complexity of our model is to the extent that can be used not only in mobility management test procedures but also in order to calculate some useful parameters of these procedures. In this paper, we apply real data to validate the proposed model by simulation which is used to confirm the accuracy of the proposed model and its analytical analysis. Copyright © 2008 John Wiley & Sons, Ltd.

An iterative reconstruction method that was proposed for clipping noise cancellation in orthogonal frequency domain multiplexing (OFDM) systems is applied to multilevel quadrature amplitude modulation-based multi-carrier (MC) code division multiple access signals in downlink. The iterative method uses a known distortion function, maybe a nonlinear one such as a successive clipping and filtering process, in the iterations to give an approximation of inverse of the distortion process and then the iterative method removes distortion under a convergence condition. The authors show that MC signal with properly chosen clipping threshold satisfies convergence conditions of the iterative method. In contrast to some of the other reconstruction-based techniques, this method requires no extra bandwidth and side information and it can be implemented with reasonable complexity. Furthermore, the authors show that the proposed iterative scheme can be enhanced by using an extra frequency bandwidth. Exploiting extra bandwidth improves the performance of the reconstruction-based methods in case of using successive clipping and filtering. Simulation results will be used to demonstrate achievable bit-error-rate improvement by the proposed enhanced iterative scheme.

The presence of multiple access interference and hardware complexity of the mobile terminal are two major burdens for multi-carrier code division multiple access schemes. Both burdens can be overcome in downlink by precoding the transmitted signal using the knowledge of the channel state information. In multi-user precoding techniques, the transmitter is optimised to combat channel impairments through the use of new spreading sequences that are obtained by solving an optimisation problem based on some criterion. Among these optimisation problems, the problem based on maximum likelihood is hard and complex to solve. In the proposed precoding scheme, the well-suited expectation maximisation algorithm is used to solve this problem. The proposed precoding technique is simulated and its performance is analysed and compared with some other precoding and detecting techniques. The results show that the proposed scheme considerably outperforms the previous precoding schemes.

In this paper, we analyze performance of a special kind of multitone CDMA (MT-CDMA) systems that is Replica MT-CDMA. It is shown that with the same bandwidth, Replica MT-CDMA system outperforms the conventional system that we name it as S/P MT-CDMA. We also propose a low-rate bandwidth efficient channel coding scheme for Replica MT-CDMA communication system so that by using it, coded Replica MT-CDMA system needs to the same bandwidth as the uncoded one. In this paper, we compare low-rate coded and uncoded Replica MT-CDMA systems with S/P MT-CDMA system over uplink and downlink Rayleigh fading channels. Our results show that with the same bandwidth, performance of coded Replica MT-CDMA system with the proposed channel coding scheme is considerably better than performance of both uncoded MT-CDMA systems.

This paper proposes two different transmit precoding schemes for downlink of overloaded CDMA systems i.e. CDMA systems in which the number of users is more than the processing gain of the system. These schemes are based on user grouping technique. In this technique, K users in the system are partitioned into G groups and a unique spreading sequence is assigned to each group. Using multiple antenna in the base station transmitter, we can separate users in each group by their different spatial characteristics. This separation is performed by some linear spatial pre-processing techniques in the transmitter. In addition, to suppress the multiple access interference between users in different groups, we use temporal linear transmit precoding method. Using precoding method in the base station's transmitter makes the mobile receivers very simple and low cost. We present the bit error rate (BER) performance of the proposed schemes in a flat fading channel by computer simulations. It is demonstrated that a considerable improvement in the performance and increasing in the system capacity will be obtained by using the proposed group transmission schemes

In this paper we propose a new vehicle mobility modeling method in which many important real world environment issues such as topologies and traffic conditions are considered to model the user movement in a real environment. For this purpose, we also propose a scenario to extract necessary information for this model by using of data captured from an appropriate BTS in wireless networks. Collected data are available from counters which are settled in wireless networks and also are monitored in Operation and Maintenance Center (OMC).

In mobile communications, mobility modeling is involved in several aspects such as signaling and traffic load analysis. In particular, accuracy of mobility models become essential for the evaluation of system design alternatives and network implementation cost issues. In this paper we propose a new method in which many important issues such as streets topology and traffic conditions are considered to model the user movement in a real environment. By using this model we also propose a new intelligent algorithm based on a sub-optimum path finding method to find a proper path between source and destination. The proposed model is suitable for modification for random waypoint model and can be applied in mobile network simulation and intelligent transport system control

We propose a novel decoding technique for DFT-based error control codes, which is robust against quantization and additive noise. The proposed algorithm simultaneously determines the number and the positions of the corrupted samples. We show that in contrast to conventional decoding techniques, the proposed decoding method is stable in the presence of quantization and additive noise.

It is well known that clipping the OFDM signals in digital part of the transmitter is one of the simplest methods to reduce the peak to mean envelop power ratio. However, it suffers from additional clipping distortion, peak regrowth after digital to analog conversion, and out-of-band distortion. Recently, to combat the effect of in-band distortion and peak regrowth, it is proposed that before clipping, oversampling is performed by padding the modulating sequence with zeros. In this paper, we propose a robust DFT-based method (DBM) to reconstruct the clipped samples and mitigate the clipping distortion in the presence of channel noise at the expense of bandwidth expansion. We show through extensive simulations that by slightly increasing the bandwidth of the system, we can significantly improve the performance while limiting the maximum of the analog signal. Furthermore, we compare the performance of the DBM and the channel coding methods. It can be seen that for lower bandwidth expansions, the DBM outperforms the channel coding methods at moderate SNR values while for higher bandwidth expansions, the channel coding methods seem to be more efficient. Furthermore, we introduce a hybrid system which outperforms both the DBM and the channel coding methods at most SNR values.

We consider using a soft-input decoder for internally bandwidth efficient convolutionally coded fiber-optic code division multiple access (CDMA) communication systems using optical orthogonal codes (OOC). The convolution codes that are used for demonstrating the capabilities of the soft-input decoder are super orthogonal codes (SOC). These codes are near optimal and have a relatively low complexity. We evaluate the upper bounds on the bit error probability of the internally coded fiber-optic CDMA system using soft-input and hard-input decoders, assuming both on-off keying (OOK) and binary pulse position modulation (BPPM) schemes. It is shown that the soft-input decoder significantly outperforms the hard-input decoder.

We propose using a soft-input decoder for the decoding of internally convolutional coded Poisson noise-dominated fiber-optic code-division multiple-access (CDMA) communication systems using optical orthogonal codes. We first compute the coded symbol log-likelihoods at the output of the Poisson noise-dominated channel, which is then used by a soft-input maximum-likelihood decoder, for a fiber-optic CDMA system assuming both on-off keying and binary pulse position modulation schemes. Furthermore, we develop a discrete soft-output channel model for a Poisson noise-dominated channel, with which we evaluate the upper bound on the bit error probability of the internally coded Poisson noise-dominated fiber-optic CDMA system using a soft-input decoder. It is shown that the soft-input decoder significantly outperforms the hard-input decoder. Furthermore, the performance of the soft-input decoder is also evaluated in the presence of different values of dark current.