D2D Pairs Research Articles

Deep Reinforcement Learning-Based Dynamic Spectrum Access for D2D Communication Underlay Cellular Networks

This letter investigates a deep reinforcement learning (DRL)-based spectrum access scheme for device-to-device (D2D) communication underlay cellular networks. Specifically, cellular users (CUEs) and D2D pairs attempt to access the time slots (TSs) of a shared spectrum, and TSs are dynamically scheduled to CUEs in different frames. Based on the DRL theory, D2D pairs can be seen as a centralized agent which aims to learn an optimal spectrum access strategy to maximize the sum throughput without any prior information. In particular, with different locations of CUEs, the spectrum access manners for D2D communication are changed to ensure the communication quality of CUEs at the cell edge. Then, a double deep Q-network (DDQN) based D2D spectrum access (D <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> SA) algorithm is proposed, which makes D2D pairs learn to decide whether to access the spectrum in different TSs. Moreover, to ensure the fairness of resource allocation among D2D pairs, we improve the proposed algorithm and incorporate fairness into the objective function. Simulation results show that our proposed algorithm can achieve an optimal sum throughput close to the theoretical upper bound, where the performance is significantly improved compared to the scheme based on base station cooperation.

Resource Allocation for Downlink Full-Duplex Cooperative NOMA-Based Cellular System with Imperfect SI Cancellation and Underlaying D2D Communications.

In this paper, the interplay between non-orthogonal multiple access (NOMA), device-to-device (D2D) communication, full-duplex (FD) technology, and cooperation networks is proposed, and a resource allocation problem is investigated. Specifically, a downlink FD cooperative NOMA-based cellular system with underlaying D2D communications is proposed, where, in each NOMA group, the strong user assists the weak user as an FD relay with imperfect self interference (SI) cancellation. In terms of reaping spectral efficiency benefits, the system sum rate is to be maximized by optimizing channel allocation. This optimization is based on quality of service (QoS) constraints of D2D pairs and cellular users (CUs), power budget of base station and strong user (cooperative phase), and successive interference cancellation (SIC) constraints. Since the maximization formulated problem is computationally challenging to be addressed, a two-sided stable many-to-one matching algorithm, based on Pareto improvement, performs sub-channel assignment. Extensive simulations are implemented to demonstrate the system performance indicated by different metrics.

Improper Gaussian Signaling for D2D Communication Coexisting MISO Cellular Networks

Improper Gaussian signaling (IGS) has shown its capability of improving the rate of interference-limited networks by exploiting the additional degrees of freedom in signal processing. This article considers a system of a multiple-input single-output (MISO) cellular network coexisting with device-to-device (D2D) communication, where the former employs proper Gaussian signaling (PGS) but the latter employs IGS to improve D2D's rate and also to mitigate interference to the former. Both non-orthogonal and orthogonal bandwidth sharing between cellular users (CUs) and D2D pairs are considered. The problems of joint bandwidth allocation and signal beamforming to maximize the minimum CUs' rate subject to the transmit power budget and D2D's rate threshold are addressed, which pose critical computational challenges. Path-following algorithms of low complexity are developed for computational solutions. Two distinct scenarios, i.e., unmanned aerial vehicle (UAV)-enabled networks, and MISO cellular networks are simulated to give insight into the superiority of using IGS over PGS. Our results reveal that in UAV-enabled networks, orthogonal sharing produces a higher D2D's rate, while non-orthogonal sharing offers better CUs' rate under practical levels of D2D's rate. In MISO systems, IGS is a game-changer, which enables the orthogonal sharing to uniformly outperform the non-orthogonal sharing in terms of CUs' rate.

Distributed pricing‐based resource allocation for dense device‐to‐device communications in beyond 5G networks

AbstractConsidering the dramatic increase of data rate demand in beyond fifth generation (5G) networks due to the numerous transmitting nodes, dense device‐to‐device (D2D) communications where multiple D2D pairs can simultaneously reuse a cellular link can be considered as a communication paradigm for future wireless networks. Since distributed methods can be more practical compared to complex centralized schemes, we propose a low‐complexity distributed pricing‐based resource allocation algorithm to allocate power to cellular user equipments (CUEs) and D2D pairs constrained to the minimum quality‐of‐service (QoS) requirements of CUEs and D2D pairs in two phases. The price of each link is set by the base station (BS). CUEs and D2D pairs maximize their rate‐and‐interference‐dependent utility function by adjusting their power in the first phase, while the price of each link is updated at the BS based on the minimum QoS requirements of CUEs and D2D pairs in the second phase. The proposed utility function controls D2D admission, hence it is suitable for dense scenarios. The proposed method is fast due to the closed‐form solution for the first phase power allocation. Numerical results verify the effectiveness of the proposed method for practical dense beyond 5G scenarios by allocating resources to multiple D2D pairs and taking advantage of the spatial reuse gain of D2D pairs. Furthermore, the utility function definition is discussed to illustrate its effectiveness for SE maximization. Finally, the SE of the proposed method is compared to other centralized and distributed algorithms to demonstrate the higher sum‐rate performance of the proposed algorithm.

Mode Selection and Cooperative Jamming for Covert Communication in D2D Underlaid UAV Networks

The integration of unmanned aerial vehicle (UAV) networks and device-to-device (D2D) communications is expected to provide ubiquitous connectivity and high-speed rates for sensitive information transmission in future wireless networks. However, the traditional cryptography and physical layer security techniques still cannot prevent adversaries from knowing the existence of information transmission such that they further launch attacks on transmitters and receivers. Covert communication can offer an even stronger level of security via hiding the information transmission process of wireless networks. In this article, we first integrate D2D communications into UAV networks, and then investigate the fundamental issues of mode selection and cooperative jamming for covert communication in such networks, aiming to provide a powerful security solution to support widespread securi-ty-sensitive applications of such networks. To this end, we propose two promising D2D underlaid UAV network architectures, whereby each UAV acts as either a flying BS or an aerial UE. Then, we propose a covert communication strategy by combining mode selection and cooperative jamming, where mode selection allows each user equipment to adaptively switch between half-du-plex and full-duplex communication modes, and cooperative jamming means that idle D2D pairs inject interference to confuse adversaries. The goal of the proposed strategy is to enhance covert capacity performance (i.e., the maximum channel rate) while maintaining a high detection error probability at adversaries in the promising network architectures. Numerical results are presented to evaluate our strategy of mode selection and cooperative jamming, and to illustrate performance gains in terms of covert capacity and detection error probability in these two network architectures. Finally, a vision is discussed for our future research in D2D underlaid UAV networks.

Content Independent Location Based Clustering for 5G Device to Device Communications

In this paper we have addressed a content independent location based clustering technique for fifth generation device-to-device (D2D) communications. Our objective is to serve a suitable number of requesting D2D pairs through an overlay cluster based communication irrespective of their content. To do so we have described a framework for the proposed approach addressing the required parameters. We then developed an analytical model of a novel cluster-head selection strategy using the concept of sparse matrix. Based on these, a location based cluster formation (LBCF) algorithm has been designed for maximizing the service coverage taking care of the inter-cluster interference through proper power tuning and appropriate resource allocation. Extensive simulations have been performed using network simulator 2 for the evaluation of our proposed LBCF approach. It has been shown that LBCF confirms notable service coverage and achieves desirable throughput in comparison to a non-cluster approach. The efficiency of resource utilization is also established. Simulation results show that the proposed approach is efficient enough to provide uniform signal coverage to the members of the same cluster and gives a comparable performance with other existing approaches. Finally the novelty of the proposed LBCF is established through a sensitivity analysis.

An Efficient Channel and Power Allocation Scheme for D2D Enabled Cellular Communication System: An IoT Application

The Device-to-device (D2D) networks bear a close resemblance to future Internet of Things (IoT) networks. Resource management is an important aspect for realization of D2D communication in upcoming IoT networks. In this article, we select underlay in-band D2D communication as it is more beneficial in terms of spectral efficiency even though it comes at the cost of interference with cellular communication. To deal with this difficulty, we propose a novel downlink resource sharing strategy, where multiple D2D users (D2Ds) share the resource of a single cellular user (CU), and each D2D pair reuses multiple channels from different cellular users (CUs). The proposed scheme adopts a channel selection technique, wherein multiple channels of CU can be shared by each D2D user. Furthermore, optimal power for each D2D user is determined through the Lagrangian dual optimization method. The formulated power control maximization scheme nicely balances the total transmission power of D2D and D2D sum-rate. The proposed channel and power allocation problem aims at maximizing the D2D sum-rate by increasing the number of active D2D links while preserving the quality of service (QoS) of CU. Finally, a relationship between energy efficiency (EE) and transmit power of D2D is investigated through an EE maximization problem. The overall system performance is evaluated in terms of the D2D shared ratio, throughput gain of the network, and computational complexity of the proposed optimal strategy. Further, the merits of using the proposed resource sharing scheme over the existing schemes are also verified through numerical results.

Throughput maximization for UAV-assisted wireless powered D2D communication networks with a hybrid time division duplex/frequency division duplex scheme

In this paper, we investigate a low-altitude unmanned aerial vehicle (UAV)-assisted wireless power- ed device-to-device (D2D) network with the “harvest-transmit-store” model, where a UAV broadcasts energy to all D2D transmitters and the transmitters then store or use the energy for transmission information. In the proposed model, the UAV does not transmit energy in the transmission information time, resulting in a limited charging time. In addition, the interference may be caused by communicating information of an arbitrary number of D2D pairs simultaneously. In this paper, we propose a hybrid time division duplex/frequency division duplex communication scheme, which performs the power transfer and information transmission simultaneously in the transmission information time. The scheme cancels the cochannel interference by using the time division duplex scheme and guarantees the charging time by using the frequency division duplex. We consider optimizing the throughput based on the scheme via joint power control, spectrum allocation, and scheduling time. We propose a two-step algorithm to solve the formulated nonconvex problem. The simulation results show that the proposed algorithm improves the average throughput compared to the other schemes.

Distributed Opportunistic Scheduling With Interference Mitigation Antenna Selection for Ultra-Dense D2D Networks

This letter proposes a novel distributed opportunistic scheduling with interference mitigation antenna selection (DOS-IMAS) to achieve the optimal multi-user diversity in ultra-dense device-to-device (D2D) networks. The proposed DOS-IMAS opportunistically and sequentially selects K D2D pairs in a fully distributed manner based on interference and desired signal power thresholds. We prove that the proposed DOS-IMAS achieves the optimal multi-user diversity K log SNR log ( n) under n=ω((MN) <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1/κ-1</sup> SNR <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K/(K-1)1-κ</sup> ), where SNR, n, M, and N denote the signal-to-noise ratio, the total number of D2D pairs in the network, the number of transmit antennas, the number of receive antennas, respectively, and κ ∈(0, 1). The numerical results validate that the proposed technique outperforms existing scheduling schemes in terms of sum rates.

Greedy Based Radio Resource Allocation Algorithm with Water Filling Power Control Scheme in D2D Underlaying Communication

Device to Device (D2D) is communication between two devices directly without the intervention of eNodeB.This communication can improve sum-rate, spectral efficiency, and decrease the workload of eNodeBbecause using the same spectrum frequency with Cellular User Equipment (CUE). But this communicationshould use the same resource simultaneously with CUE which is called D2D underlaying. This sharingresources also causes interference and should be managed using the resource allocation algorithm. In thiswork, the resource allocation is allocated in a single cell and uplink communication using joint greedyalgorithm with water filling power control scheme. This algorithm is compared with greedy, joint greedy,and greedy algorithm with water filling power control scheme. Joint greedy algorithm works based on thecapacity of eNodeB and D2D pair. While in water filling power control, the power of the user is managedbased on the channel condition and impact to energy efficiency. After all the resource is allocated, theparameter performance of the system is calculated, such as spectral efficiency, energy efficiency, and D2Dfairness. From the simulation result, joint greedy algorithm with water filling power control scheme result29,34 bps/Hz in spectral efficiency, 0.939 x 107 bps/watt in energy efficiency, and 0,996 in D2D fairness.

Joint Optimization of Spectral Efficiency and Energy Harvesting in D2D Networks Using Deep Neural Network

In this work, we study the joint optimization of energy harvesting and spectrum efficiency in wireless device-to-device (D2D) networks where multiple D2D pairs adopt simultaneous wireless information and power transfer (SWIPT) functionality with a power-splitting policy. To observe the trade-off relationship between spectrum efficiency and energy harvesting via SWIPT, we construct an objective function using the weighted sum method, which scalarizes the dominant with spectrum efficiency and energy harvesting, and attempt to find the optimal transmit power and power-splitting ratio to maximize the objective function. Typical iterative search algorithms such as exhaustive search (ES) or gradient search (GS) with a log barrier function are employed to find the global optimum and sub-optimum, respectively. Furthermore, we apply a deep neural network (DNN) learning algorithm to deal with the non-convexity of the objective function with an effective loss function. The simulation results verify the trade-off relationship between spectrum efficiency and energy harvesting, and show that the DNN-based algorithm can achieve a near-global optimal solution with computational complexity much lower than that of the optimization-based iterative algorithms.

D2D-enabled resource management in secrecy-ensured 5G and beyond Heterogeneous networks

Integration of Device-to-Device communication in 5G Heterogeneous networks (HetNets) promises to increase resource utilization and spectrum efficiency (SE). However, the broadcast nature of wireless communication makes it vulnerable to an eavesdropper, who can steal useful information from the transmission channel. Hence, ensuring secure communication for both cellular users (CUs) and D2D pairs is the need of the time. In this paper, we study the optimization problem of resource allocation in 5G and beyond wireless networks to maximize the secrecy rate of both CUs and D2D links from the physical layer security perspective. We consider multiple eavesdroppers overhearing the CUs and D2D pairs. Two optimization problems are formulated: one considering separate channels for CUs and D2D user (DU), and second, considering the shared channel between CU and DU. The nature of the formulated problems is mixed-integer non-linear programming (MINLP) problem and to solve it, we propose an ϵ-optimal based successive linearization algorithm. This algorithm decomposes our original problem into finite sub-problem branches and solves each separately. Simulation results show that the proposed technique can significantly improve the secrecy rate, throughput, and energy efficiency of the network especially in the case of separate channels for CUs and DUs.

Device-to-device and mobile user communication with queuing in NOMA-based network

Abstract In this paper, device-to-device (D2D) pairs use the uplink resource of a mobile user. The transmission is done using a non-orthogonal multiple access (NOMA) technology. The D2D pairs are placed in a queue with maximum threshold time. The channel is allocated to D2D pairs using the TDMA scheme with the first in first out (FIFO) principle. Considering the slots of time division multiple access (TDMA) and channel state, the channel is shared by one D2D pair with the mobile user. The signal to interference (SIC) is employed for D2D pair or mobile user based on NOMA. A hybrid of TDMA and NOMA is used in which time and bit allocation are judiciously adopted. The results are simulated for four different scenarios of power and rate requirements with reduced latency and interference.

Joint Interference Alignment and Power Allocation Based on Stackelberg Game in Device-to-Device Communications Underlying Cellular Networks

As a promising wireless communication technique, Device-to-Device (D2D) can improve the utilization of spectrum resources, overall system throughput and reduce end-to-end delay, energy consumption by exploiting the direct radio link between local devices. Meanwhile, introducing D2D in cellular networks is very challenging due to the complex interference problem. To deal with the complex interference of D2D Underlying Cellular Networks, Interference alignment (IA) as an efficient interference management technique is extensively studied for D2D communications underlaying the cellular networks. However, most of the previous researches on IA only consider the equal power allocation for users, which leads to suboptimal overall system throughput. In order to further improve the system performance, in this paper, we propose a joint power allocation based on stackelberg game and interference alignment algorithm (STPA-IA) to eliminate the complex interference in D2D communications underlaying cellular networks. In this joint approach, the base station (BS) is modeled as the leader while the D2D pairs are followers. The performance of network system and that of D2D users are regarded as the revenues of leader and followers in stackelberg game. The strategy of the leader (BS) is to get the maximum benefits by reducing the interference, while the followers tend to (D2D pairs) maximize their own utility according to leader's strategy. The non-cooperative game is proved to get the nash equilibrium by the above strategies. Moreover, the close-form expression of the allocated power by maximum the unity function of leader and followers is derived. Extensive simulation results demonstrate that the proposed algorithm outperforms previous works in terms of sum-rate with lower time complexity.

Enabling Device‐to‐Device (D2D) Communication for the Next Generation WLAN

Device‐to‐device (D2D) communication technology is widely acknowledged as an emerging candidate to alleviate the wireless traffic explosion problem for the next generation wireless local area network (WLAN) IEEE 802.11ax. In this paper, we integrate D2D communication into IEEE 802.11ax for maximizing the spectrum efficiency. Due to the spectrum scarcity, the number of available resource units (RUs) is typically less than D2D pairs and stations (STAs), which makes the management of spectrum resources more complex. To tackle this issue, we design an efficient resource management algorithm for uplink random access and resource allocation in D2D‐enabled 802.11ax, which provides more channel access and resource reuse opportunities for STAs and D2D pairs. Specifically, we propose an enhanced back‐off mechanism and derive the optimal contention window (CW) by a theoretical model, which improves the uplink random access efficiency. To tackle the complex interference problem in RU scheduling phase, we develop an efficient and low‐complexity resource allocation algorithm based on the maximal independent set (MIS), which can schedule multiple D2D pairs to share the same RU with the specific STA. Simulation results demonstrate that the proposed algorithm significantly improves the network performance in terms of system throughput, collision rate, complete time, and channel utilization.

Joint Resource Allocation and Mode Selection for Device-to-Device Communication Underlying Cellular Networks

Device to device (D2D) communication has recently been established in the literature as an effective means to increase the frequency spectrum and enhance the efficiency of energy consumption in future cellular systems. However, certain issues, resulting from reusing resources in the same cell, have caused serious perturbations. We study issues pertaining to D2D communication, such as dual mode selection, channel allocation and power control, aiming at the maximization of the overall throughput of the system, while at the same time ensuring that the generated interference is kept minimized. This is an NP-Hard problem that decomposes the optimization problem into two layers: the inner layer, where the DQN algorithm is used as an indicator of the optimal transmission power that should be allocated to the D2D pairs in accordance with their mode of operation, and the outer layer, where strategic decisions, such as which communication mode to use and how to allocate the channels, are made. We have proved the superiority of the proposed scheme, in terms of both system throughput and performance, through simulating experiments involving different scenarios.

A Joint Channel Allocation and Power Control Scheme for D2D Communication in UAV‐Based Networks

With the increasing application of unmanned aerial vehicles (UAVs), UAV‐based base stations (BSs) have been widely used. In some situations when there is no ground BSs, such as mountainous areas and isolated islands, or BSs being out of service, like disaster areas, UAV‐based networks may be rapidly deployed. In this paper, we propose a framework for UAV deployment, power control, and channel allocation for device‐to‐device (D2D) users, which is used for the underlying D2D communication in UAV‐based networks. Firstly, the number and location of UAVs are iteratively optimized by the particle swarm optimization‐ (PSO‐) Kmeans algorithm. After UAV deployment, this study maximizes the energy efficiency (EE) of D2D pairs while ensuring the quality of service (QoS). To solve this optimization problem, the adaptive mutation salp swarm algorithm (AMSSA) is proposed, which adopts the population variation strategy, the dynamic leader‐follower numbers, and position update, as well as Q‐learning strategy. Finally, simulation results show that the PSO‐Kmeans algorithm can achieve better communication quality of cellular users (CUEs) with fewer UAVs compared with the PSO algorithm. The AMSSA has excellent global searching ability and local mining ability, which is not only superior to other benchmark schemes but also closer to the optimal performance of D2D pairs in terms of EE.

Power allocation for NOMA in D2D relay communications

Non-orthogonal multiple access (NOMA) is considered as one of the key technologies for the fifth generation (5G) wireless communications. The integration of NOMA and device-to-device (D2D) communications has recently attracted wide attention. In this paper, a relaying D2D communications assisted with cooperative relaying systems using NOMA (DRC-NOMA) is considered. We analyze the ergodic sum-rate for the proposed system and then derive the closed-form expressions. In addition, an optimal power allocation strategy maximizing the ergodic sum-rate is proposed based on these analysis results. Numerical results show the good agreement between the results of analysis and Monte Carlo method. The proposed DRC-NOMA has a great improvement of the ergodic sum-rate in the small regime of average channel gain of D2D pair.

Resource Allocation for D2D Communication in Cellular Networks Based on Stochastic Geometry and Graph-coloring Theory

In a device-to-device (D2D) underlaid cellular network, there exist two types of co-channel interference. One type is inter-layer interference caused by spectrum reuse between D2D transmitters and cellular users (CUEs). Another type is intra-layer interference caused by spectrum sharing among D2D pairs. To mitigate the inter-layer interference, we first derive the interference limited area (ILA) to protect the coverage probability of cellular users by modeling D2D users’ location as a Poisson point process, where a D2D transmitter is allowed to reuse the spectrum of the CUE only if the D2D transmitter is outside the ILA of the CUE. To coordinate the intra-layer interference, the spectrum sharing criterion of D2D pairs is derived based on the (signal-to-interference ratio) SIR requirement of D2D communication. Based on this criterion, D2D pairs are allowed to share the spectrum when one D2D pair is far from another sufficiently. Furthermore, to maximize the energy efficiency of the system, a resource allocation scheme is proposed according to weighted graph coloring theory and the proposed ILA restriction. Simulation results show that our proposed scheme provides significant performance gains over the conventional scheme and the random allocation scheme.

Greedy Based Radio Resource Allocation Algorithm with SARSA Power Control Scheme in D2D Underlaying Communication

Device-to-Device (D2D) underlaying communication system is a solution in reducing the workload of eNodeB and increasing the system data rate. This communication system consists of two users, namely Cellular User Equipment (CUE) and D2D pair, where CUE will share its resources with the D2D pair. This sharing resources also causes interference and should be managed using the resource allocation algorithm. In this work, the resource allocation scheme occurs in a single cell with an uplink communication direction. The resource allocation process uses greedy and joint greedy algorithms. After CUE allocates all of its resources, SARSA algorithm performs the power allocation process. The resource allocation process involves the scheduled CUE and D2D pair. After all the resource and power are allocated, parameter performance of the system is calculated. Based on the work results, joint greedy algorithm with power allocation using SARSA algorithm have performance results 1.375 × 107 bps/Watt in energy efficiency, 43.105 bps/Hz in spectral efficiency, and 0.993 in D2D fairness index.