Related papers: Bandwidth and Power Allocation for Task-Oriented S…
As the scarce spectrum resource is becoming over-crowded, cognitive radios (CRs) indicate great flexibility to improve the spectrum efficiency by opportunistically accessing the authorized frequency bands. One of the critical challenges for…
This letter investigates the problem of energy efficient collaborative strategy for mobile embodied artificial intelligence network (MEAN) over wireless communication. In the considered model, the agents execute the tasks through…
Spectrum management has been identified as a crucial step towards enabling the technology of a cognitive radio network (CRN). Most of the current works dealing with spectrum management in the CRN focus on a single task of the problem, e.g.,…
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.…
We address the problem of resource allocation (RA) in a cognitive radio (CR) communication system with multiple secondary operators sharing spectrum with an incumbent primary operator. The key challenge of the RA problem is the…
In this paper, we adopt a multiobjective optimization approach to jointly optimize the rate and power in OFDM-based cognitive radio (CR) systems. We propose a novel algorithm that jointly maximizes the OFDM-based CR system throughput and…
In this paper, the sum-rate maximization problem is studied for wireless networks that use downlink rate splitting multiple access (RSMA). In the considered model, each base station (BS) divides the messages that must be transmitted to its…
Optimizing distributed learning systems is an art of balancing between computation and communication. There have been two lines of research that try to deal with slower networks: {\em communication compression} for low bandwidth networks,…
We optimize resource allocation to enable communication security in simultaneous wireless information and power transfer (SWIPT) for internet-of-things (IoT) networks. The resource allocation algorithm design is formulated as a non-convex…
Large model has emerged as a key enabler for the popularity of future networked intelligent applications. However, the surge of data traffic brought by intelligent applications puts pressure on the resource utilization and energy…
Artificial intelligence (AI) is ushering in a new era for communication. As a result, the establishment of a semantic communication framework is putting on the agenda. Based on a realistic semantic communication model, this paper develops a…
In a multi-robot system, the appropriate allocation of the tasks to the individual robots is a very significant component. The availability of a centralized infrastructure can guarantee an optimal allocation of the tasks. However, in many…
We consider a class of resource allocation problems given a set of unconditional constraints whose objective function satisfies Bellman's optimality principle. Such problems are ubiquitous in wireless communication, signal processing, and…
In recent years, semantic communication is progressively emerging as an effective means of facilitating intelligent and context-aware communication. However, current researches seldom simultaneously consider the reliability and timeliness…
The increasing deployment of agentic artificial intelligence (AI) systems has intensified the demand for efficient agent to agent communication, particularly over bandwidth limited wireless links. In embodied AI applications, agents must…
This paper presents a Semantic Feature Multiple Access (SFMA) framework for multi-user semantic communication in downlink wireless systems. By extending SwinJSCC to a two-user superimposition paradigm, SFMA enables simultaneous semantic…
The integrated radar and communication system is promising in the next generation wireless communication networks. However, its performance is confined by the limited energy. In order to overcome it, a wireless powered integrated radar and…
Semantic communication (SemCom) has emerged as a promising paradigm that leverages Deep Neural Networks (DNNs) to extract task-relevant information, thereby substantially reducing the volume of transmitted data. In existing implementations,…
This paper studies the resource allocation algorithm design for multiuser coordinated multipoint (CoMP) networks with simultaneous wireless information and power transfer (SWIPT). In particular, remote radio heads (RRHs) are connected to a…
Mobile edge computing (MEC) enables the provision of high-reliability and low-latency applications by offering computation and storage resources in close proximity to end-users. Different from traditional computation task offloading in MEC…