相关论文: Optimizing Clustered Cell-Free Networking for Sum …

This work presents a new resource allocation optimization framework for cellular networks using neighborhood-based optimization. Under this optimization framework resources are allocated within virtual cells encompassing several…

This paper proposes a novel scheme for cell-free massive multiple-input multiple-output (CFmMIMO) networks to support any federated learning (FL) framework. This scheme allows each instead of all the iterations of the FL framework to happen…

Cell-free wireless networks have attracted significant interest for their ability to eliminate cell-edge effects and deliver uniformly high service quality through macro-diversity. In this paper, we develop an algorithm to jointly optimize…

In this paper we study energy efficient joint power allocation and beamforming for coordinated multicell multiuser downlink systems. The considered optimization problem is in a non-convex fractional form and hard to tackle. We propose to…

The problem of user scheduling and power allocation in full-duplex (FD) cellular networks is considered, where a FD base station communicates simultaneously with one half-duplex (HD) user on each downlink and uplink channel. First, we…

We study the problem of user-scheduling and resource allocation in distributed multi-user, multiple-input multiple-output (MIMO) networks implementing user-centric clustering and non-coherent transmission. We formulate a weighted sum-rate…

To relieve the stress on channel estimation and decoding complexity in cell-free massive multiple-input multiple-output (MIMO) systems, user grouping problem is investigated in this paper, where access points (APs) based on time-division…

This work proposes a new resource allocation optimization framework for cellular networks using "fog" or neighborhood-based optimization rather than fully centralized or fully decentralized methods. In neighborhood-based optimization…

This paper proposes a distributed learning-based framework to tackle the sum ergodic rate maximization problem in cell-free massive multiple-input multiple-output (MIMO) systems by utilizing the graph neural network (GNN). Different from…

We consider the interference management problem in a multicell MIMO heterogenous network. Within each cell there are a large number of distributed micro/pico base stations (BSs) that can be potentially coordinated for joint transmission. To…

We consider a heterogeneous network with mobile edge computing, where a user can offload its computation to one among multiple servers. In particular, we minimize the system-wide computation overhead by jointly optimizing the individual…

This work proposes a joint power control and access points (APs) scheduling algorithm for uplink cell-free massive multiple-input multiple-output (CF-mMIMO) networks without channel hardening assumption. Extensive studies have done on the…

This invited paper presents some novel ideas on how to enhance the performance of consensus algorithms in distributed wireless sensor networks, when communication costs are considered. Of particular interest are consensus algorithms that…

The heterogeneous cellular networks (HCNs) with device-to-device (D2D) communications have been a promising solution to cost-efficient delivery of high data rates. A key challenge in such D2D-enabled HCNs is how to design an effective…

In this paper, we develop a framework to maximize the network energy efficiency (EE) by optimizing joint user-base station~(BS) association,~subchannel assignment, and power control considering an in-band full-duplex (IBFD)-enabled…

In this paper, we tackle the problem of multi-cell resource scheduling, where the objective is to maximize the weighted sum-rate through inter-cell interference coordination (ICIC). The blanking method is used to mitigate the inter-cell…

This paper considers the uplink of user-centric cell-free massive MIMO (multiple-input multiple-output) systems. We utilize the user-centric dynamic cooperation clustering (DCC) framework and derive the achievable spectral efficiency with…

In this paper, a balanced energy consumption clustering algorithm (BECC) is proposed. This new scheme is a cluster-based algorithm designed for heterogeneous energy wireless sensor networks. A polarized energy factor is introduced to adjust…

In this paper, we propose a novel algorithm to maximize the sum rate in interference-limited scenarios where each user decodes its own message with the presence of unknown interferences and noise considering the…

Cell-free (CF) massive multiple-input-multiple-output (mMIMO) deployments are usually investigated with half-duplex nodes and high-capacity fronthaul links. To leverage the possible gains in throughput and energy efficiency (EE) of…