D2D Communications In Heterogeneous Networks Research Articles

Performance of Q-learning based resource allocation for D2D communications in heterogeneous networks

This study investigates energy efficiency issues of device-to-device (D2D) communications in heterogeneous networks. To minimize the total transmitted power, an approach based on Q-learning together with adaptive ɛ-greedy is proposed to optimize the connection of user equipment (UE) with base station (BS) or access point (AP). The proposed adaptive ɛ-greedy can conduct the adequate exploration and exploitation operations for effective optimization. Simulation results indicate that in the single-cell scenario, the proposed method can attain performance close to the best solution.

Mobility-Aware Data Caching to Improve D2D Communications in Heterogeneous Networks

User Equipment (UE) is equipped with limited cache resources that can be utilized to offload data traffic through device-to-device (D2D) communications. Data caching at a UE level has the potential to significantly alleviate data traffic burden from the backhaul link. Moreover, in wireless networks, users exhibit mobility that poses serious challenges to successful data transmission via D2D communications due to intermittent connectivity among users. Users’ mobility can be exploited to efficiently cache contents by observing connectivity patterns among users. Therefore, it is crucial to develop an efficient data caching mechanism for UE while taking into account users’ mobility patterns. In this work, we propose a mobility-aware data caching approach to enhance data offloading via D2D communication. First, we model users’ connectivity patterns. Then, contents are cached in UE’ cache resources based on users’ data preferences. In addition, we also take into account signal-to-interference and noise ratio (SINR) requirements of the users. Hence, our proposed caching mechanism exploits connectivity patterns of users to perform data placement based on users’ own demands and neighboring users to enhance data offloading via cache resources. We performed extensive simulations to investigate the performance of our proposed mobility-aware data caching mechanism. The performance of our proposed caching mechanism is compared to most deployed data caching mechanisms, while taking into account the dynamic nature of the wireless channel and the interference experienced by the users. From the obtained results, it is evident that our proposed approach achieves 14%, 16%, and 11% higher data offloading gain than the least frequently used, the Zipf-based probabilistic, and the random caching schemes in case of an increasing number of users, cache capacity, and number of contents, respectively. Moreover, we also analyzed cache hit rates, and our proposed scheme achieves 8% and 5% higher cache hit rate than the least frequently used, the Zipf-based probabilistic, and the random caching schemes in case of an increasing number of contents and cache capacity, respectively. Hence, our proposed caching mechanism brings significant improvement in data sharing via D2D communications.

Joint beamforming and power allocation using deep learning for D2D communication in heterogeneous networks

Device-to-device (D2D) communication plays a significant role in cellular networks as it can increase the capacity, spectrum efficiency and energy efficiency of the system. However, the large computational complexity of D2D resource management optimisation algorithms creates a serious gap between theoretical design and real-time processing, which leads to the limited use of D2D communication technology. In this study, a novel deep learning-based optimisation method is proposed to overcome the high computational complexity of joint beamforming design and power allocation optimisation algorithms in D2D communication. Unlike existing approaches, the authors design a convolutional neural network based end-to-end network structure to solve complex computing problems for channel state information under a limited feedback scenario. The Max-SE loss function which indicates quality-of-service (QoS) constraint and interference constraint, together with the mean squared error (MSE) function, are designed to maximise the spectral efficiency of the system while minimising the total transmit power. The simulation results show that the proposed approach can achieve performance comparable to the weighted minimum MSE scheme with low computation time.

Energy Efficient Spectrum Allocation and Mode Selection for D2D Communications in Heterogeneous Networks

In this paper, we consider a heterogeneous network consisting of both macro Base Station (MBS) and pico Base Stations (PBSs) in order to provide a spectrum allocation and mode selection in device-to-device (D2D) communications. A number of Component Carriers (CC) are considered available for allocation to the MBS and PBSs that are being utilized through carrier aggregation (CA) while mode selection decisions are made by each BS in order to balance between power consumption minimization and UE data rate requirements. A power minimization (energy-efficient) problem is formulated in order to provide a joint spectrum allocation and mode selection solution. This problem is solved using a state of the art optimization method known as proximal algorithm. First, a non-cooperative (centralized) solution is provided and second, a cooperative (distributed) employing distributed proximal algorithm is devised reducing the induced complexity. The cooperative solution is achieved by implementing distributed alternating direction method of multipliers (D-ADMM). Simulation results are carried out for all cases that reveal the energy efficient spectrum allocation and mode selection according under certain channels’ conditions that can balance between achieving high data rate requirements and power minimization. Finally, useful insights are presented such as complexity, convergence, delay and actual implementation of such a solution for the future wireless networks.

D2D Communications in Heterogeneous Networks With Full-Duplex Relays and Edge Caching

This paper studies the joint optimal resource allocation and probabilistic caching design for device-to-device (D2D) communications in a wireless heterogeneous network with full-duplex (FD) relays. In particular, popular contents can be cached at user devices as well as at relays that are located close to users. A user can request contents from another user via D2D communications and also from a nearby relay equipped with FD radios. In the case that there is a caching miss (i.e., the requested contents are not found at the other users/relays within the coverage range), users can connect to the base station via a relay by using the FD communication technology. Subsequently, we develop mathematical models to analyze the throughput performance with edge caching where both cochannel system level interference and FD self-interference are considered. Due to the high complexity of stochastic optimization, we develop low-complexity optimization formulation by decomposing the original problem into three simple subproblems that can be efficiently solved. Finally, numerical results are presented to illustrate developed theoretical findings in the paper and significant performance gains of the throughput performance.

Power Control for Energy Efficient D2D Communication in Heterogeneous Networks With Eavesdropper

In general heterogeneous networks, the interference from other communication systems is a main factor for degrading the performance in terms of data rate, so that each system is required to minimize the interference to other systems. However, if the eavesdropper is additionally considered in the heterogeneous networks, the signal from other systems can be utilized for disturbing the information recovery of the eavesdropper. Based on this idea and the importance of the energy efficient communication in Internet of Things (IoT) system, we propose a power control scheme for improving the energy efficiency of device-to-device communication while assisting the secure communication of wireless local area network by interfering with the eavesdropper. We derive a closed-form expression for an optimal power control factor as a function of system parameters. The simulation results confirm the accuracy of analysis and show that the proposed scheme outperforms the conventional scheme in terms of the energy efficiency.

Enable device-to-device communications underlaying cellular networks: challenges and research aspects

Device-to-device communication underlaying a cellular network is a promising technology in future wireless networks to improve network capacity and user experience. While D2D communication has great potential to improve wireless system spectral and energy efficiency due to the proximity of communication parties and higher spectrum reuse gain, tremendous work is still ongoing to turn the promising technology into a reality. This article discusses D2D technical challenges as well as standards progress and important research aspects that enable D2D communications underlaying cellular networks. The key research areas addressed include interference management, multihop D2D communications, and D2D communications in heterogeneous networks. When enabling D2D communications underlaying cellular networks, D2D communications can use either cellular downlink or cellular uplink resources. The two resource sharing modes will create different interference scenarios. The performance evaluation on D2D communications underlaying cellular networks under these two different scenarios is provided.