Related papers: OpenRANet: Neuralized Spectrum Access by Joint Sub…
Virtualized Radio Access Network (vRAN) is one of the key enablers of future wireless networks as it brings the agility to the radio access network (RAN) architecture and offers degrees of design freedom. Yet, it also creates a challenging…
Energy consumption represents a major part of the operating expenses of mobile network operators. With the densification foreseen with 5G and beyond, energy optimization has become a problem of crucial importance. While energy optimization…
This paper considers the downlink of a cache-enabled fog radio access network (F-RAN) with limited fronthaul capacity, where user association (UA), data delivery rate (DDR) and signal precoding are jointly optimized. We formulate a…
The open radio access network (O-RAN) describes an industry-driven open architecture and interfaces for building next generation RANs with artificial intelligence (AI) controllers. We circulated a survey among researchers, developers, and…
In this paper, we propose a cross layer energy efficient resource allocation and remote radio head (RRH) selection algorithm for heterogeneous traffic in power domain - non-orthogonal multiple access (PD-NOMA) based heterogeneous cloud…
Heterogeneous network is a novel network architecture proposed in Long-Term-Evolution~(LTE), which highly increases the capacity and coverage compared with the conventional networks. However, in order to provide the best services,…
Deep neural networks (DNNs) have been introduced for designing wireless policies by approximating the mappings from environmental parameters to solutions of optimization problems. Considering that labeled training samples are hard to…
Openness and intelligence are two enabling features to be introduced in next generation wireless networks, e.g. Beyond 5G and 6G, to support service heterogeneity, open hardware, optimal resource utilization, and on-demand service…
This tutorial seeks to outline the proposed Open Radio Access Network (O-RAN) deployment for Fifth generation (5G) wireless networks. O-RAN seeks to supplant hardware-specific Radio Access Network (RAN) components (e.g., the mobility…
This paper studies a deep learning (DL) framework to solve distributed non-convex constrained optimizations in wireless networks where multiple computing nodes, interconnected via backhaul links, desire to determine an efficient assignment…
The Radio Access Network (RAN) is a critical component of modern telecommunications infrastructure, currently evolving towards disaggregated and open architectures. These advancements are pivotal for integrating intelligent, data-driven…
This paper studies fast downlink beamforming algorithms using deep learning in multiuser multiple-input-single-output systems where each transmit antenna at the base station has its own power constraint. We focus on the…
In light of the premises of beyond fifth generation (B5G) networks, the need for better exploiting the capabilities of cloud-enabled networks arises, so as to cope with the large-scale interference resulting from the massive increase of…
In modern wireless communication systems, there is a rapidly increasing demand for connectivity to wireless networks. Devices such as internet of things (IoT) devices, connected vehicles, smartphones, surveillance systems, and various other…
Distributed learning and adaptation have received significant interest and found wide-ranging applications in machine learning and signal processing. While various approaches, such as shared-memory optimization, multi-task learning, and…
The open radio access network (RAN) aims to bring openness and intelligence to the traditional closed and proprietary RAN technology and offer flexibility, performance improvement, and cost-efficiency in the RAN deployment and operation.…
Deep learning enabled semantic communication has been studied to improve communication efficiency while guaranteeing intelligent task performance. Different from conventional communications systems, the resource allocation in semantic…
In this paper, the problem of opportunistic spectrum sharing for the next generation of wireless systems empowered by the cloud radio access network (C-RAN) is studied. More precisely, low-priority users employ cooperative spectrum sensing…
In this article, we study a Radio Resource Allocation (RRA) that was formulated as a non-convex optimization problem whose main aim is to maximize the spectral efficiency subject to satisfaction guarantees in multiservice wireless systems.…
In this paper, we design a new flexible smart software-defined radio access network (Soft-RAN) architecture with traffic awareness for sixth generation (6G) wireless networks. In particular, we consider a hierarchical resource allocation…