Related papers: Deep Learning Based Resource Allocation for Full-d…
The 5G cellular wireless systems will have a multi-tier architecture consisting of macrocells, different types of licensed small cells and D2D networks to serve users with different quality-of-service (QoS) requirements in a spectrum…
This paper shows that deep neural network (DNN) can be used for efficient and distributed channel estimation, quantization, feedback, and downlink multiuser precoding for a frequency-division duplex massive multiple-input multiple-output…
This paper presents a novel deep reinforcement learning-based resource allocation technique for the multi-agent environment presented by a cognitive radio network where the interactions of the agents during learning may lead to a…
The concept of device-to-Device (D2D) communication as an underlay coexistence with cellular networks gains many advantages of improving system performance. In this paper, we model such a two-layer heterogenous network based on stochastic…
Device-to-device (D2D) communication is a promising approach to efficiently disseminate critical or viral information. Reaping the benefits of D2D-enabled networks is contingent upon choosing the optimal content dissemination policy subject…
Resource allocation has a direct and profound impact on the performance of vehicle-to-everything (V2X) networks. In this paper, we develop a hybrid architecture consisting of centralized decision making and distributed resource sharing (the…
In this paper, we investigate the resource allocation problem for D2D communications underlaying wireless powered communication networks, where multiple D2D pairs harvest energy from a power station equipped with multiple antennas and then…
This paper studies the benefits of incorporating underlaid full-duplex (FD) device-to-device (D2D) communications into massive multiple-input-multiple-output (MIMO) downlink systems. Due to the nature of cellular downlink and FD D2D…
With the current exponential growth in traffic and service demands, device-to-device (D2D) cooperation is identified as a major mechanism to enable 5G networks to effectively and efficiently augment network resources. The effectiveness of…
Federated learning (FL) encounters scalability challenges when implemented over fog networks that do not follow FL's conventional star topology architecture. Semi-decentralized FL (SD-FL) has proposed a solution for device-to-device (D2D)…
A novel content caching strategy is proposed for a cache enabled device-to-device (D2D) network where the user devices are allowed to communicate using millimeter wave (mmWave) D2D links (> 6 GHz) as well as conventional sub 6 GHz cellular…
The recent significant progress in realizing full-duplex~(FD) systems has opened up a promising avenue for improving quality of service (QoS) and quality of experience (QoE) in future wireless networks. There is an urgent need to address…
Federated Learning (FL), an emerging paradigm for fast intelligent acquisition at the network edge, enables joint training of a machine learning model over distributed data sets and computing resources with limited disclosure of local data.…
Device-to-Device (D2D) communications underlaying cellular networks is a viable network technology that can potentially increase spectral utilization and improve power efficiency for proximitybased wireless applications and services.…
In frequency-division duplex (FDD) massive multiple-input multiple-output (MIMO) systems, the growing number of base station antennas leads to prohibitive feedback overhead for downlink channel state information (CSI). To address this…
Device-to-device (D2D) communications is expected to be a critical enabler of distributed computing in edge networks at scale. A key challenge in providing this capability is the requirement for judicious management of the heterogeneous…
The integration of local device-to-device (D2D) communications and cellular connections has been intensively studied to satisfy co-existing D2D and cellular communication demand. In future cellular networks, there will be numerous standby…
This paper investigates the general problem of resource allocation for mitigating channel fading effects in Free Space Optical (FSO) communications. The resource allocation problem is modeled as the constrained stochastic optimization…
This paper studies energy efficiency maximization in device-to-device (D2D) communications underlaying cellular networks in millimeter-wave (mm-wave) band. A stochastic geometry framework has been used to extract the results. First,…
Tremendous growing demand for high data rate services is the main driver for increasing traffic in wireless cellular networks. Device-to-Device (D2D) communications have recently been proposed to offload data via direct communications by…