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In a cellular network, direct Device-to-Device (D2D) communication enhances Quality of Service (QoS) in terms of coverage, throughput and amount of power consumed. Since theD2D pairs involve cellular resources for communication, the chances of interference are high. D2D communications demand minimum interference along with maximum throughput and sum rate which can be achieved by employing optimal resources and efficient power allocation procedures. In this research, a hybrid optimization model called Genetic Algorithm-Adaptive Bat Optimization (GA-ABO) algorithm is proposed for efficient resource allocation in a cellular network with D2D communication. Simulation analysis demonstrates that the proposed model involves reduced interference with maximum sum rate and throughput. The performance of the proposed model is compared with the existing Ant Colony Optimization-based resource exchange and GAME (ACO-GAME) theory models, Trader-assistedResource EXchange mechanism-RadioAccess Network (TREX-RAN) and De-centralized Radio Access Network (TREXDRAN), and greedy CYcle-Complete preferences (CYC) models. The proposed model offers a maximum sum rate of 83 kB/s, which is much better than the existing techniques. [ABSTRACT FROM AUTHOR]

Device-to-device communication (D2D-C) is one of the breakthrough technologies of the fifth-generation (5G) network that has attracted researchers working in data-regroup applications. It offers great advantages, such as minimum delay, base station load balancing, improved spectral efficiency, and many more. Despite these benefits, efficient resource allocation is one of the major concerns. Existing state-of-the-art solutions are based on game theory, graph theory, etc. The one-to-one Maximum matching scheme offers the best solution in graph theory and has not been explored to its potential. Also, the number of eavesdroppers in the system can affect the existing resource allocation schemes and degrade the system's performance. This can be taken care of by implementing a D2D-C user access control mechanism, which restricts D2D-C users from having eavesdropping intentions. So, considering these issues, we propose a Fisher Jenks natural break (FJNB) optimization and kernel density estimation clustering-based resource allocation scheme with a D2D-C user access control mechanism. It improves the overall system's total sum rate and computation time performance. [ABSTRACT FROM AUTHOR]

We consider a four-node cooperative, detect-and-forward (DaF) relay-assisted device-to-device (D2D) system. For it, we propose a simple, novel, and intuitive probabilistic relay selection policy. We analyze fading-averaged symbol error rate (FASER) of the policy. Specifically, we derive closed form expressions of FASER for two different constellations, namely, M-ary phase shift keying (MPSK) and M-ary quadrature amplitude modulation (MQAM). Besides the FASER analysis, we also analyze fading-averaged spectral efficiency. We extend our analysis and present an insightful result on the diversity order of the proposed relay selection policy. In order to validate our theoretical derivations, we present numerical results. For the in-depth analysis of the proposed probabilistic relay selection policy, various effects like small scale fading, large scale fading, and the combination of both small and large scale fading are considered with path loss. The proposed relay selection policy and its performance analysis are useful for cooperative D2D wireless DaF relay systems and networks. [ABSTRACT FROM AUTHOR]

Resource sharing is one of the main goals achieved by network virtualization technology to enhance network resource utilization and enable resource customization. Though resource sharing can improve network efficiency by accommodating various users in a network, limited infrastructure capacity is still a challenge to ultra-low latency service operators. In this paper, we propose an inter-slice resource borrowing schema based on the device-to-device (D2D) potentiality especially for ultra-low latency transmission in cellular networks. An extended and modified Kuhn-Munkres bipartite matching algorithm is developed to optimally achieve inter-slice resource borrowing. Simulation results show that, proper D2D user matching can be achieved, satisfying ultra-low latency (ULL) users' quality of service (QoS) requirements and resource utilization in various scenarios. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs), acting as mobile base stations (BSs), can be deployed in the typical fifth-generation mobile communications (5G) scenarios for the purpose of substantially enhancing the radio coverage. Meanwhile, UAV aided underlay device-to-device (D2D) communication mode can be activated for further improving the capacity of the 5G networks. However, this UAV aided D2D communication system is more vulnerable to eavesdropping attacks, resulting in security risks. In this paper, the D2D receivers work in full-duplex (FD) mode, which improves the security of the network by enabling these legitimate users to receive their useful information and transmit jamming signal to the eavesdropper simultaneously (with the same frequency band). The security communication under the UAV coverage is evaluated, showing that the system’s (security) capacity can be substantially improved by taking advantage of the flexible radio coverage of UAVs. Furthermore, the closed-form expressions for the coverage probabilities are derived, showing that the cellular users (CUs)’ secure coverage probability in downlink transmission is mainly impacted by the following three factors: its communication area, the relative position with UAV, and its eavesdroppers. In addition, it is observed that the D2D users or DUs’ secure coverage probability is relevant to state of the UAV. The system’s secure capacity can be substantially improved by adaptively changing the UAV’s position as well as coverage. [ABSTRACT FROM AUTHOR]

Abstract In the blooming era of Pervasive and Mobile Computing, trust has been accepted as a vital factor for provisioning secure, reliable and seamless communications between pervasive computing elements. However, advancing research in the area of trust-based protocol for distributed Pervasive and Mobile Computing might be challenging due to the ambiguity of the concept of trust as well as the variety of divergent trust models, protocols and algorithms in different contexts. In this research, we augment the trust concept and definition from various field of studies and proposed models in the literature and provide general conceptual phases and methods of trust management toward-trust-based protocols, in the context of Pervasive and Mobile Computing. The paper addresses a broad range of techniques, methods, models, applications and desired futures of trust-based protocols. A number of the currently used trust-based protocols are critically reviewed, and this further leads our discussion to the security attacks and mitigation strategies used with trust-based protocols for pervasive and mobile computing. Finally, the paper discusses open research issues. [ABSTRACT FROM AUTHOR]

Device-to-device (D2D) communication offloads the base station (BS) traffic, enhances spectral efficiency, and provides efficient data transmission with low latency between devices in close proximity. However, there are many issues in D2D communication, such as mode selection, device discovery, security, privacy, resource allocation, and interference management. At the time of the resource allocation, there is an issue of interference and eavesdropping by the malicious user on D2D pairs. Here, an eavesdropper can decrypt the data exchanged between the D2D user devices. This paper focuses on the efficient resource allocation in D2D communication that improves sum rate, computational complexity, and information secrecy capacity by reusing cellular user's (CU) resources. Here, we propose an efficient resource allocation scheme incorporating the artificial intelligence (AI) algorithm-based autoencoder that overcomes information ambiguity when there is the same weight in the data rate matrix of the Hungarian algorithm. First, we identify cellular and D2D users' communication data rates and generate a data rate matrix using the channel gain, received signal, and signal-to-interference-plus-noise ratio (SINR) values. The generated data rate matrix is passed as an input into an autoencoder. An autoencoder performs the dimensionality reduction using latent space and reconstructs the optimal cost matrix. The AI model's result shows that the autoencoder achieves 83% training and 90% validation accuracy using the mean squared error (MSE) loss function. Then, we determine the optimal cost using the Hungarian algorithm. As we aim to maximize the sum rate and reduce the computation cost, our simulation result shows that the resource allocation performs efficiently using the proposed scheme. [ABSTRACT FROM AUTHOR]

There are many scenarios that have been proposed for fifth generation (5G) networks. Some of them, if implemented, will bring fundamental changes at the architectural and node level. One example of such proposed technologies is device-to-device (D2D) communications which will change the nature of conventional cellular network design. D2D permits direct communication between two or more user devices without intervention of the base station (i.e. eNB). D2D can ensure network performance improvement over the traditional cellular network, because it can offload the mobile data traffic from the other devices. However, applying D2D features in a cellular network will bring about more complex interference problems, since D2D communication uses the same band as its underlying cellular communication network. The aim of this research is to investigate interference-related problems caused by D2D communications, affecting the underlying cellular networks, during downlink and uplink transmissions. The paper examines the use of power control methods to mitigate interference. A comparison is offered between fixed power level (FC) with or without power control, and adaptive power controls using two methods (AC1 and AC2), on a base station or on each of the D2D devices, based on the measured signal to interference plus noise ratio (SINR). The simulation results show that both power control methods contribute to improvement of network performance. AC1 and AC2 can improve SINR by about 1 dB and 0.5 dB compared to FC in a down-link transmission, and by 0.5 dB in an uplink transmission. [ABSTRACT FROM AUTHOR]

Along with the surge of data traffic amount, Long Term Evolution (LTE)-based Device-to-Device (D2D) communication is emerging as a key data traffic offloading technology. However, current LTE-based D2D communication has limitations such as the lack of feedback mechanism, causing difficulty for efficient radio resource use. In this paper, we propose a feedback mechanism to increase the spectral efficiency of LTE-based D2D communication. In particular, the proposed feedback mechanism is designed to minimize signaling overhead and D2D Rxs can use the proposed feedback mechanism without any connection to Base Station (BS). On top of the proposed mechanism, we also propose feedback-aided rate adaptation and recovery schemes. Through extensive simulations, we verify that the proposed solutions achieve solid performances, e.g., goodput and latency, under various channel environments. [ABSTRACT FROM AUTHOR]

Device to device (D2D) communication has attracted enormous attention for future cellular networks which helps to increase the cellular capacity, improve the user throughput, and extend the battery lifetime of user equipments (UEs) by reusing the spectrum resources. However, D2D devices provide interferences in the system while reusing the resources. Proper control of interferences helps to increase the performance of the overall system. Adaptive power allocation among cellular and D2D users contributes to providing an efficient interference management system. In this paper, we propose an online power allocation method, i.e., multi-armed bandit solver for D2D communication. We explore the proposed method to improve the system throughput and D2D throughput as well. We incorporate the set of states for this learning algorithm with the appropriate number of system-defined variables, which increases the observation space and consequently improve the balance of spectrum usage. Finally, we compare our proposed work with existing distributed reinforcement learning and random allocation of resources. Simulation results depict that the proposed resource allocation method outperforms the existing works regarding overall system throughput as well as D2D throughput by efficiently controlling the interference levels. [ABSTRACT FROM AUTHOR]

The energy efficiency (EE) of Device-to-Device (D2D) communication underlay cellular networks has become a significant issue because of increasing the resource utilization and extending the battery life of user equipment. However, the interference caused by sharing the same resources with the cellular users will descend the performance of the system. Therefore, D2D users should be allocated reasonable sub-carrier and suitable power to improve the performance of the cellular networks. In this paper, D2D communication can directly transmit information or transmit dates through an assisted relay based on the outage probability of D2D users. Meanwhile, we propose an algorithm to study the problem of EE of D2D communication under the condition of the required QoS (Quality of Services) of both cellular users and D2D users and the maximum transmission power threshold of D2D users. To solve the problem efficiency, we divide the algorithm into two stages to allocate sub-carrier and optimize power, respectively. By numerical simulation, we also prove the good performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

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In this paper, we study the cooperative communication of a cognitive underlay network by utilizing the diversity of multiple spectrum bands. In particular, we assume that the transmission power of the secondary user (SU) is subject to different joint constraints, such as peak interference power of the multiple primary users (PUs), peak transmission power of the SU, outage tolerate interference, and outage probability threshold. Accordingly, two power allocation schemes are considered on the basis of the minimum interference channel from the SU to the PU and the channel state information of the primary user link. Furthermore, the SU can select one of the three transmission modes following the channel state conditions, namely as cellular, device-to-device, or switching mode, to transmit the signal to the secondary user receiver. Given this setting, two power allocation schemes over a spectrum band selection strategy are derived. In addition, closed-form expressions for the outage probability of three modes are also obtained to evaluate the performance of the secondary network. Most importantly, a closed-form expression for the peak interference power level of the PU, which is considered as one of the most important parameters to control the SU’s transmission power, is derived by investigating the relation of two considered power allocation schemes in the practise. Finally, numerical examples show that the outage performance of secondary network in the switching mode outperforms the one of the cellular and device-to-device (D2D) mode for all considered power allocation schemes. [ABSTRACT FROM AUTHOR]

Next-generation cellular networks need to provide seamless connectivity with higher data rates, increased capacity, and enhanced network coverage. As multimedia service demands in various heterogeneous devices grow rapidly compared to the underlying network's capacity and bandwidth, the adaptation in multimedia streaming services is essential for providing satisfactory Quality of Experience (QoE). This paper develops a Device-to-Device (D2D)-assisted Utility-based Adaptive Multimedia (video) Streaming scheme (UAMS) using D2D communication in a 5th Generation (5G) cellular network where low-battery users may extend their streaming duration by spending lower reception energy with the help of D2D-assisted communication. The adaptation algorithm considers four utility functions: quality, power consumption, packet error ratio, and remaining battery of the user devices to adapt the bitrate dynamically and augment viewers' experience. We formulate an optimization problem to maximize the joint utility function to provide the best adaptive multimedia content selected for transmission to the end-users either directly or via D2D Relay Nodes (DRNs) in every scheduling interval. We use a graph theoretic approach for choosing the best DRNs. Extensive simulations show the efficacy of the proposed scheme in terms of saved battery energy, churn rate, and QoE metrics compared to a few well-known existing schemes in the literature that do not use D2D communication. [ABSTRACT FROM AUTHOR]

Device-to-Device (D2D) communication is an essential element in 5G networks and beyond. It enables users to communicate either directly without network assistance or with minimum signaling through a base station. The enormous number of connected devices to the networks with high velocity of these users increases the complexity of establishing an effective and stable D2D connection when the user is moving among different available peers and modes in the network. So, the main objective for this research was to design an adaptive social-aware D2D communication mechanism to enhance the performance of D2D connection by improving procedures and efficiency of peer and mode selection. The mechanism consists of two schemes, namely the peer and mode selection schemes. The peer selection scheme includes two parts. Firstly, the peer evaluation is based on social choice theory through verifying the relationship between peers, and dividing the available peers into trusted peers and untrusted peers. The technical evaluation is based on HAW algorithm by including multi-attributes related to the connection quality to find the optimum trusted peer while excluding untrusted peers from the ranking. Secondly, the mode selection scheme evaluates the available modes based on the connection status while considering multi-attributes based on SAW algorithm to select and switch among available modes intelligently, based on the highest-ranking, to select the optimum mode. In this study, the proposed scenario considers the status of different numbers of users in the network to evaluate the proposed mechanism, and compared with two other recent approaches. The obtained results showed that the proposed mechanism outperforms other approaches in terms of delay, signal-to-noise ratio, delivery ratio, and throughput with better performance. It provides smooth switching between different modes and employs an automatic peering selection with trusted peers only. [ABSTRACT FROM AUTHOR]

Device-to-Device (D2D) communication underlaying cellular networks is a promising add-on component for future radio communication systems. It provides more access opportunities for local device pairs and enhances system throughput (ST), especially when mobile relays (MR) are further enabled to facilitate D2D links when the channel condition of their desired links is unfavorable. However, mutual interference is inevitable due to spectral reuse, and moreover, selecting a suitable transmission mode to benefit the correlated resource allocation (RA) is another difficult problem. We aim to optimize ST of the hybrid system via joint consideration of mode selection (MS) and RA, which includes admission control (AC), power control (PC), channel assignment (CA) and relay selection (RS). However, the original problem is generally NP-hard; therefore, we decompose it into two parts where a hierarchical structure exists: (i) PC is mode-dependent, but its optimality can be perfectly addressed for any given mode with additional AC design to achieve individual quality-of-service requirements. (ii) Based on that optimality, the joint design of MS, CA and RS can be viewed from the graph perspective and transferred into the maximum weighted independent set problem, which is then approximated by our greedy algorithm in polynomial-time. Thanks to the numerical results, we elucidate the efficacy of our mechanism and observe a resulting gain in MR-aided D2D communication. [ABSTRACT FROM AUTHOR]

In this paper, we consider cooperative D2D communications in cellular networks. More precisely, a cellular user leases part of its spectrum to facilitate the D2D communication with a goal of improving the energy efficiency of a D2D pair. However the D2D pair is untrusted to the cellular user, such resource sharing may result in the information of this cellular user unsecured. In order to motivate the cellular user's generosity, this D2D pair needs to help the cellular user maintain a target secrecy rate. To address this issue, we formulate a joint spectrum and power allocation problem to maximize the energy efficiency of the D2D communication while guaranteeing the physical layer security of the cellular user. Then, a theorem is proved to indicate the best resource allocation strategy, and accordingly, an algorithm is proposed to find the best solution to this resource allocation problem. Numerical results are finally presented to verify the validity and effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper analyzes the optimal user density and power allocation for Device-to-Device (D2D) communication underlaying cellular networks on multiple bands with the target of maximizing the D2D transmission capacity. The entire network is modeled by Poisson point process (PPP) which based on stochastic geometry. Then in order to ensure the outage probabilities of both cellular and D2D communication, a sum capacity optimization problem for D2D system on multiple bands is proposed. Using convex optimization, the optimal D2D density is obtained in closed-form when the D2D transmission power is determined. Next the optimal D2D transmission power is obtained in closed-form when the D2D density is fixed. Based on the former two conclusions, an iterative algorithm for the optimal D2D density and power allocation on multiple bands is proposed. Finally, the simulation results not only demonstrate the D2D performance, density and power on each band are constrained by cellular communication as well as the interference of the entire system, but also verifies the superiority of the proposed algorithm over sorting-based and removal algorithms. [ABSTRACT FROM AUTHOR]

Device-to-Device (D2D) communications in Long Term Evolution (LTE) networks has been proposed as a promising concept as part of the LTE-Advanced (LTE-A) framework, whose aim is to improve user experiences and resource utilization, taking advantage of users' proximity to each other. In order to extend the current LTE-A system to support D2D communication, there is a need to work on enhancements on the network architecture level. In this paper, we survey the work proposed so far by researchers and propose a design that extends the Third Generation Partnership Project's (3GPP) definition of proximity based services, describing by this the necessary supporting elements. [ABSTRACT FROM AUTHOR]

Device-to-device (D2D) communication is an excellent technology to improve the system capacity by sharing the spectrum resources of cellular networks. Multicast service is considered as an effective transmission mode for the future mobile social contact services. Therefore, multicast based on D2D technology can exactly improve the spectrum resource efficiency. How to apply D2D technology to support multicast service is a new issue. In this paper, a resource allocation scheme based on cognitive radio (CR) for D2D underlay multicast communication (CR-DUM) is proposed to improve system performance. In the cognitive cellular system, the D2D users as secondary users employing multicast service form a group and reuse the cellular resources to accomplish a multicast transmission. The proposed scheme includes two steps. First, a channel allocation rule aiming to reduce the interference from cellular networks to receivers in D2D multicast group is proposed. Next, to maximize the total system throughput under the condition of interference and noise impairment, we formulate an optimal transmission power allocation jointly for the cellular and D2D multicast communications. Based on the channel allocation, optimal power solution is in a closed form and achieved by searching from a finite set and the interference between cellular and D2D multicast communication is coordinated. The simulation results show that the proposed method can not only ensure the quality of services (QoS), but also improve the system throughput. [ABSTRACT FROM AUTHOR]

It is expected that device-to-device (D2D) communication is allowed to underlay future cellular networks such as IMT-Advanced for spectrum efficiency. This article studies the mechanisms of D2D communication and interference avoidance when the D2D subsystem reuses uplink resources and downlink spectrums with a cellular system, respectively. We firstly propose an effective scheme to establish and maintain D2D communication. Moreover, a novel method to deal with the resource allocation and interference avoidance issues by utilizing the network peculiarity of a hybrid network to share the uplink resource is proposed. Most research focuses on reusing the uplink spectrums, but how to share the downlink frequency bands is seldom addressed. To share the downlink spectrums and avoid the interference to the primary cellular devices, a labeled time slots based mechanism is proposed. Implementation details are described in a real cellular system and simulation results prove that satisfying performance can be achieved by using the proposed mechanisms. [ABSTRACT FROM AUTHOR]

In this paper, beamforming for device-to-device multicast communication under channel uncertainty arising from incomplete channel state information is considered. The problem is first formulated as a non-robust minimization problem subject to signal-to-interference-plus-noise ratio, transmit power and interference constraints. Using semi-definite programming relaxation, a tractable convex robust counterpart of the beamforming problem was then formulated. Cases of deterministic and probabilistic interference constraints were considered. To simplify the probabilistic constraint, a cumulative distribution function substitution was used. The results show that the channel uncertainty error affects the optimal beamforming vector compared to the negligible effect of the probabilistic constraint. [ABSTRACT FROM AUTHOR]

This paper proposes a device-to-device (D2D) enabling cellular full-duplex (FD) cooperative (DFC) protocol using non-orthogonal multiple access (NOMA) called DFC-NOMA, where an FD relay acting D2D transmitter assists in relaying a NOMA far user's signal and transmits a D2D receiver's signal simultaneously. The ergodic capacity, outage probability, and diversity order of DFC-NOMA are theoretically investigated under the assumption of both perfect and imperfect interference cancellation. The theoretical analysis is then validated by simulations. Both analysis and simulation results demonstrate the performance gain of DFC-NOMA over conventional FD cooperative NOMA and existing D2D aided FD NOMA. [ABSTRACT FROM AUTHOR]

Device-to-Device (D2D) multicast communication is a new technology of the fifth-generation networks (5G) for efficiently coping with the ever-increasing demand for content sharing among users. In fact, it enables direct communication between devices in proximity and improves spectral efficiency by reusing a licensed cellular spectrum. The existing related studies show that D2D communications increase network capacity and reduce latency. Nevertheless, the interference management should be carried out in a coordinated manner in order to realize the full potential of this technology and enable its integration into the cellular architecture. We consider the joint uplink subcarrier allocation and power control in D2D underlying cellular networks. In single rate multicast communications, the achieved data rate is greatly limited by the nodes with low channel quality. In this article, we formulate the resource allocation as a max–min optimization problem. Such an optimization problem is in general an NP-hard combinatorial problem and its solution typically requires searching enormous search trees. We propose a multicast schemes based on Genetic Algorithm (GA) and Binary Particle Swarm Optimization (BPSO). We implemented 8 different transfer functions combined with 2 update position strategies in order to assess the performance of BPSO. For the GA, we implemented Uniform and Multipoint crossover methods combined with Roulette Wheel and Tournament selectors. In addition to providing a deep understanding of the algorithm behavior, we present numerical results that demonstrates that GA outperforms BPSO in terms of minimum achieved data rate when the pressure of infeasibility is high. [ABSTRACT FROM AUTHOR]