Joint Power Allocation and Mode Selection for D2D Communications with Imperfect CSI

Device-to-device(D2D) communications can be underlaid with a cellular infrastructure to increase resource utilization, improve user throughput and save battery energy. In such networks, power allocation and mode selection are crucial problems. To address the joint optimization of power and mode selection under imperfect CSI, we propose an optimal, energy-aware joint power allocation and mode selection(JPAMS) scheme. First, we derive the closed-form solution for the power minimization for both D2 D and cellular links while satisfying different quality of service(Qo S) constraints. Second, we address the mode selection problem in presence of imperfect CSI, based on the derived power allocation. Moreover, the theoretical analysis and simulation results are presented to evaluate the proposed scheme for the D2 D communications.

Energy Efficient Power Allocation for Relay-Aided D2D Communications in 5G Networks

As one of the key technologies for the fifth generation(5G) wireless networks,device-to-device(D2D) communications allow user equipment(UE) in close proximity to communicate with each other directly.Forwarded by a relay,the relay-aided D2D(RA-D2D) communications can not only be applied to communications in much longer distance but also achieve a high quality of service(Qo S) .In this paper,we first propose a two-layer system model allowing RA-D2 D links to underlay traditional cellular uplinks.Then we maximize the energy efficiency of the RA-D2 D link while satisfying the minimum data-rate of the cellular link.The optimal transmit power at both D2 D transmitter and D2 D relay sides is obtained by transforming the nonlinear fractional programming into a nonlinear parameter programming.Simulation results show that our proposed power allocation method is more energy efficient than the existing works,and the proposed RA-D2 D scheme outperformed direct D2 D scheme when the distance between two D2 D users is longer.

Secure Beamforming Design for SWIPT in Cooperative D2D Communications

In device-to-device(D2D) communications, device terminal relaying makes it possible for devices in a network to function as transmission relays for each other to enhance the spectral efficiency. In this paper we consider a cooperative D2D communication system with simultaneous wireless information and power transfer(SWIPT). The cooperative D2D communication scheme allows two nearby devices to communicate with each other in the licensed cellular bandwidth by assigning D2D transmitters as half-duplex(HD) relay to assists cellular downlink transmissions. In particular, we focus on secure information transmission for the cellular users when the idle D2D users are the potential eavesdroppers. We aim to design secure beamforming schemes to maximize the D2D users data rate while guaranteeing the secrecy rate requirements of the cellular users and the minimum required amounts of power transferred to the idle D2D users. To solve this non-convex problem, a semi-definite programming relaxation(SDR) approach is adopted to obtain the optimal solution. Furthermore, we propose two suboptimal secure beamforming schemes with low computational complexity for providing secure communication and efficient energy transfer. Simulation results demonstrate the superiority of our proposed scheme.

Performance Analysis in SWIPT-Based Bidirectional D2D Communications in Cellular Networks

In this paper,a novel traffic-aware cooperative cognitive radio network that can enable deviceto-device(D2D)communications in cellular system is proposed and investigated.By providing relay cooperation to cellular transmission,D2D users can realize their own two-way communication in the licensed spectrum.Unlike most existing works,in the proposed network,both wireless-powered D2D users can harvest energy via radio-frequency signals received from basic station(BS)through a hybrid protocol which can adaptively utilize both time-switching and powersplitting techniques.Specifically,D2D users perform decode-and-forward operation to transmit signals,and mobile user(MU)employs a selection combining technique.In addition,the performance of both D2D system and cellular system in the proposed network is evaluated by deriving the expressions of their exact outage probability and throughput.Numerical and simulation results validate correctness of derivations and reveal the influence of various system parameters of the proposed network.

Energy Efficiency Optimization for D2D Communications Based on SCA and GP Method

In this paper, we propose an energy-efficient power control scheme for device-to-device(D2D) communications underlaying cellular networks, where multiple D2D pairs reuse the same resource blocks allocated to one cellular user. Taking the maximum allowed transmit power and the minimum data rate requirement into consideration, we formulate the energy efficiency maximization problem as a non-concave fractional programming(FP) problem and then develop a two-loop iterative algorithm to solve it. In the outer loop, we adopt Dinkelbach method to equivalently transform the FP problem into a series of parametric subtractive-form problems, and in the inner loop we solve the parametric subtractive problems based on successive convex approximation and geometric programming method to obtain the solutions satisfying the KarushKuhn-Tucker conditions. Simulation results demonstrate the validity and efficiency of the proposed scheme, and illustrate the impact of different parameters on system performance.

Joint channel selection and power control for video streaming over D2D communications based cognitive radio networks

A joint channel selection and power control scheme is developed for video streaming in device-to-device （D2D） communications based cognitive radio networks. In particular, physical queue and virtual queue models by applying ＇M/G/1 queue＇ and ＇M/G/1 queue with vacations＇ theories are built up, respectively, to evaluate the delays experienced by various video traffics. Such delays play a vital role in calculating the packet loss rate for video streaming, which reflects the video distortion. Based on the distortion model, a video distortion minimization problem is formulated, subject to the rate constraint, maximum power constraint, primary users＇ tolerant interference constraint, and secondary users＇ minimum data rate requirement constraint. The optimization problem turns out to be a mixed integer nonlinear programming （MINLP） , which is generally nondeterministic in polynomial time. A Lagrangian dual method is thus employed to reformulate the video distortion minimization problem, based on which the sub-gradient algorithm is used to determine a relaxed solution. Thereafter, applying the iterative user removal yields the optimal joint channel selection and power control solution to the original MINLP problem. Extensive simulations validate our proposed scheme and demonstrate that it significantly increases the peak signal- to-noise ratio （PSNR） compared with the existing schemes.

A Robust Resource Allocation Scheme for Device-to-Device Communications Based on Q-Learning

One of the most effective technology for the 5G mobile communications is Device-to-device(D2D)communication which is also called terminal pass-through technology.It can directly communicate between devices under the control of a base station and does not require a base station to forward it.The advantages of applying D2D communication technology to cellular networks are:It can increase the communication system capacity,improve the system spectrum efficiency,increase the data transmission rate,and reduce the base station load.Aiming at the problem of co-channel interference between the D2D and cellular users,this paper proposes an efficient algorithm for resource allocation based on the idea of Q-learning,which creates multi-agent learners from multiple D2D users,and the system throughput is determined from the corresponding state-learning of the Q value list and the maximum Q action is obtained through dynamic power for control for D2D users.The mutual interference between the D2D users and base stations and exact channel state information is not required during the Q-learning process and symmetric data transmission mechanism is adopted.The proposed algorithm maximizes the system throughput by controlling the power of D2D users while guaranteeing the quality-of-service of the cellular users.Simulation results show that the proposed algorithm effectively improves system performance as compared with existing algorithms.

Performance analysis of graph-based scheduling for device-to-device communications overlaying cellular networks

The performance of the graph-based scheduling for device-to-device communications overlaying cellular networks is studied. The graph-based scheduling consists of two stages, the frequency assignment stage and the time slot scheduling stage. For such scheduling, a theoretical method to analyze the average spectrum efficiency of the D2D subsystem is proposed. The method consists of three steps. First, the frequency assignment stage is analyzed and the approximate formula of the average number of the D2D links which are assigned the same frequency is derived. Secondly, the time slot scheduling stage is analyzed and the approximate formula of the average probability of a D2D link being scheduled in a time slot is derived. Thirdly, the average spectrum efficiency of the D2D subsystem is analyzed and the corresponding approximate formula is derived. Analysis results show that the average spectrum efficiency of the D2D subsystem is approximately inversely linearly proportional to the second- order origin moment of the normalized broadcast radius of D2D links. Simulation results show that the proposed method can correctly predict the average spectrum efficiency of the D2D subsystem.

Ergodic Rate Analysis on Applying Antenna Selection in D2D Communication Underlaying Cellular Networks

By reusing the spectrum of a cellular network, device-to-device(D2D) communications is known to greatly improve the spectral efficiency bypassing the base station(BS) of the cellular network. Antenna selection is the most cost efficient scheme for interference management, which is crucial to D2D systems. This paper investigates the achievable rate performance of the D2D communication underlaying the cellular network where a multiple-antenna base station with antenna selection scheme is deployed. We derive an exact closed-form expression of the ergodic achievable rate. Also, using Jensen's inequality, two pairs of upper and lower bounds of the rate are derived and we validate the tightness of the two sets of bounds. Based on the bounds obtained, we analyze the ergodic achievable rate in noise-limited scenario, interference-limited high SNR scenario and larger-scale antenna systems. Our analysis shows that the presence of D2D users could be counter-productive if the SNR at cellular UE is high. Further analysis shows that the relationship between the ergodic rate and the number of antennas it positive, but keeps decreasing as the antenna number increasing. These show the inefficiency of antenna selection in D2D interference management.

Genetic Based Approach for Optimal Power and Channel Allocation to Enhance D2D Underlaied Cellular Network Capacity in 5G

With the obvious throughput shortage in traditional cellular radio networks,Device-to-Device(D2D)communications has gained a lot of attention to improve the utilization,capacity and channel performance of nextgeneration networks.In this paper,we study a joint consideration of power and channel allocation based on genetic algorithm as a promising direction to expand the overall network capacity for D2D underlaied cellular networks.The genetic based algorithm targets allocating more suitable channels to D2D users and finding the optimal transmit powers for all D2D links and cellular users efficiently,aiming to maximize the overall system throughput of D2D underlaied cellular network with minimum interference level,while satisfying the required quality of service QoS of each user.The simulation results show that our proposed approach has an advantage in terms of maximizing the overall system utilization than fixed,random,BAT algorithm(BA)and Particle Swarm Optimization(PSO)based power allocation schemes.

On Cost Minimization for Cache-Enabled D2D Networks with Recommendation

To accommodate the tremendous increase of mobile data traffic,cache-enabled device-to-device(D2D)communication has been taken as a promising technique to release the heavy burden of cellular networks since popular contents can be pre-fetched at user devices and shared among subscribers.As a result,cellular traffic can be offloaded and an enhanced system performance can be attainable.However,due to the limited cache capacity of mobile devices and the heterogeneous preferences among different users,the requested contents are most likely not be proactively cached,inducing lower cache hit ratio.Recommendation system,on the other hand,is able to reshape users’request schema,mitigating the heterogeneity to some extent,and hence it can boost the gain of edge caching.In this paper,the cost minimization problem for the social-aware cache-enabled D2D networks with recommendation consideration is investigated,taking into account the constraints on the cache capacity budget and the total number of recommended files per user,in which the contents are sharing between the users that trust each other.The minimization problem is an integer non-convex and non-linear programming,which is in general NP-hard.Therewith,we propose a timeefficient joint recommendation and caching decision scheme.Extensive simulation results show that the proposed scheme converges quickly and significantly reduces the average cost when compared with various benchmark strategies.

Collaborative D2D Communication in Relay Networks with Energy Harvesting

Although the collaborative transmission of cellular network and device-to-device(D2D)pairs can improve spectrum utilization,it also results in the matual interference,which may be fatal for low-energy D2D pairs.Based on this,we propose in this paper a collaborative D2D transmission scheme with erergy harvesting(CDTEH)in a relay network,where D2D pairs are allowed to access the spectrum of relay network to accomplish their own transmission.In particular,the relay with energy harvesting is arranged to not only expand cellular transmission range but also assist D2D and cellular users to eliminate the mutual interference.To evaluate the performance,rate-energy(R-E)region is introduced.Based on the model,a data rate maximization problem of D2D pair is formulated,subject to a transmission demand of the cellular user and the optimal solution is acquired.Finally,numerical results are provided to validate the proposed scheme improves the data rate of D2D pair ensuring the cellular transmission requirement.

Admission control based on beamforming and interference alignment for D2D communication underlaying cellular networks

An admission control algorithm based on beamforming and interference alignment for device-to-device( D2D) communication underlaying cellular networks is proposed. First, some portion of D2D pairs that are the farthest away from the base station( BS) is selected to perform joint zero-forcing beamforming together with the cellular user equipments( UEs) and is admitted to the cellular network. The interference of the BS transmitting signal to the cellular UEs and the portion of D2D pair is eliminated completely at the same time. Secondly,based on the idea of interference alignment,the definition of channel parallelism is given. The channel parallelism of the remaining D2D pairs which are not involved in joint zero-forcing beamforming is computed by using the channel state information from the BS to the D2D devices. The higher the channel parallelism,the less interference the D2D pair suffers from the BS. Finally,in a descending order of channel parallelism,the remaining D2D pairs are reviewed in succession to determine admission to the cellular network. The algorithm stops when the admission of a D2D pair decreases the system sum rate. Simulation results show that the proposed algorithm can effectively reduce the interference of the BS transmitting signal for D2D pairs and significantly improve system capacity. Furthermore, D2D communication is more applicable to short-range links.

Secure Resource Allocation in Device-to-Device Communications Underlaying Cellular Networks

With increasing the demand for transmitting secure information in wireless networks,deviceto-device(D2D)communication has great potential to improve system performance.As a well-known security risk is eavesdropping in D2D communication,ensuring information security is quite challenging.In this paper,we first obtain the closed-forms of the secrecy outage probability(SOP)and the secrecy ergodic capacity(SEC)for direct and decodeand-forward(DF)relay modes.Numerical results are presented to verify the theoretical results,and these results show the cases that the DF relay mode improves security performance compared to the direct mode at long distances between the transmitter and receiver nodes.Further,we look into the optimization problems of secure resource allocation in D2D communication to maximize the SEC and to minimize the SOP by considering the strictly positive secrecy capacity constraint as a mixed-integer non-linear programming(MINLP)problem.In the continue,we convert the MINLP to convex optimization.Finally,we solve this program with a dual method and obtain an optimal solution in the direct and DF relay modes.

An Optimal Algorithm for Resource Allocation in D2D Communication

The number of mobile devices accessing wireless networks isskyrocketing due to the rapid advancement of sensors and wireless communicationtechnology. In the upcoming years, it is anticipated that mobile datatraffic would rise even more. The development of a new cellular networkparadigm is being driven by the Internet of Things, smart homes, and moresophisticated applications with greater data rates and latency requirements.Resources are being used up quickly due to the steady growth of smartphonedevices andmultimedia apps. Computation offloading to either several distantclouds or close mobile devices has consistently improved the performance ofmobile devices. The computation latency can also be decreased by offloadingcomputing duties to edge servers with a specific level of computing power.Device-to-device (D2D) collaboration can assist in processing small-scaleactivities that are time-sensitive in order to further reduce task delays. The taskoffloading performance is drastically reduced due to the variation of differentperformance capabilities of edge nodes. Therefore, this paper addressed thisproblem and proposed a new method for D2D communication. In thismethod, the time delay is reduced by enabling the edge nodes to exchangedata samples. Simulation results show that the proposed algorithm has betterperformance than traditional algorithm.

A Joint Resource Allocation Algorithm for D2D Communication

The emergence of multimedia services has meant a substantial increase in the number of devices in mobile networks and driving the demand for higher data transmission rates.The result is that,cellular networks must technically evolve to support such higher rates,to be equipped with greater capacity,and to increase the spectral and energy efficiency.Compared with 4G technology,the 5G networks are being designed to transmit up to 100 times more data volume with devices whose battery life is 10 times longer.Therefore,this new generation of networks has adopted a heterogeneous and ultra-dense architecture,where different technological advances are combined such as device-to-device(D2D)communication,which is one of the key elements of 5G networks.It has immediate applications such as the distribution of traffic load(data offloading),communications for emergency services,and the extension of cellular coverage,etc.In this communication model,two devices can communicate directly if they are close to each other without using a base station or a remote access point.Thus,eliminating the interference between theD2Dand cellular communication in the network.The interference management has become a hot issue in current research.In order to address this problem,this paper proposes a joint resource allocation algorithm based on the idea of mode selection and resource assignment.Simulation results showthat the proposed algorithm effectively improves the systemperformance and reduces the interference as compared with existing algorithms.

Spark Spectrum Allocation for D2D Communication in Cellular Networks

The device-to-device(D2D)technology performs explicit communication between the terminal and the base station(BS)terminal,so there is no need to transmit data through the BS system.The establishment of a short-distance D2D communication link can greatly reduce the burden on the BS server.At present,D2D is one of the key technologies in 5G technology and has been studied in depth.D2D communication reuses the resources of cellular users to improve system key parameters like utilization and throughput.However,repeated use of the spectrum and coexistence of cellular users can cause co-channel interference.Aiming at the interference problem under the constraint of fair resource allocation and improving the system throughput,this paper proposes an effective resource optimization scheme based on the firework method.The main idea is to expand the weighted sum rate and convert the allocated resource expression into fireworks to determine the correlation matrix.The simulation results show that,compared with the existing scheme,this scheme improves system performance by reducing interference.

D2D communication in a cellular network based on link adaptation with truncated ARQ

A device-to-device （D2D） communication mode underlaying cellular network in a single- cell environment is introduced. A practical method based on link adaptation with automatic repeat request （ARQ） is presented. Link adaptation technique, which combines adaptive modulation and coding （ AMC ） with truncated ARQ, can maximize the cellular UEs＇ data rate under prescribed delay and performance constraints. The proposed method can maximize the total transmission rate when an outage probability is determined. Numerical results show that with proper power control, the in- terference between the two links can be coordinated to increase the sum rate without overwhelming the cellular service.

An Optimized Fuzzy Based Ant Colony Algorithm for 5G-MANET

The 5G demonstrations in a business has a significant role in today’s fast-moving technology.Manet in 5G,drives a wireless system intended at an enormously high data rate,lower energy,low latency,and cost.For this reason,routing protocols of MANET have the possibility of being fundamentally flexible,high performance,and energy-efficient.The 5G communication aims to afford higher data rates and significantly low Over-The-Air latency.Motivated through supplementary ACO routing processes,a security-aware,fuzzy improved ant colony routing optimization protocol is proposed in MANETs.The goal is to develop aMANET routing protocol that could provide a stable packet transmission ratio,less overhead connectivity,and low end-to-end latency in shared standard scenarios and attack states.MANET demonstrates effective results with hybrid architecture and proved to be effective than other state-of-the-art routing protocols of MANETs,like AODV,its routing organization implemented through Optimized Fuzzy based ACO Algorithm for 5G.Millimeter-wavelengths are required to perform a significant role in 5G.This research proposed to test the efficiency of MANET consisting of only mmWave User Equipment.MANET reduced packet transmission loss of UEs withmmWave,meaning well-transmitted SNR leads directly to a better packet delivery ratio.To verify results,simulation using the NS-3 simulator mmWave module is used.

Federated learning based QoS-aware caching decisions in fog-enabled internet of things networks

Quality of Service(QoS)in the 6G application scenario is an important issue with the premise of the massive data transmission.Edge caching based on the fog computing network is considered as a potential solution to effectively reduce the content fetch delay for latency-sensitive services of Internet of Things(IoT)devices.Considering the time-varying scenario,the machine learning techniques could further reduce the content fetch delay by optimizing the caching decisions.In this paper,to minimize the content fetch delay and ensure the QoS of the network,a Device-to-Device(D2D)assisted fog computing network architecture is introduced,which supports federated learning and QoS-aware caching decisions based on time-varying user preferences.To release the network congestion and the risk of the user privacy leakage,federated learning,is enabled in the D2D-assisted fog computing network.Specifically,it has been observed that federated learning yields suboptimal results according to the Non-Independent Identical Distribution(Non-IID)of local users data.To address this issue,a distributed cluster-based user preference estimation algorithm is proposed to optimize the content caching placement,improve the cache hit rate,the content fetch delay and the convergence rate,which can effectively mitigate the impact of the Non-IID data set by clustering.The simulation results show that the proposed algorithm provides a considerable performance improvement with better learning results compared with the existing algorithms.