Enhanced PSO based energy-efficient resource allocation and CQI based MCS selection in LTE-A heterogeneous system

Abstract

Trajectory modeling, which includes research on trajectory data pattern mining and future prediction, has widespread applications in areas such as life services, urban transportation, and public administration. Numerous methods have been proposed to address specific problems within trajectory modelling. However, due to the heterogeneity of data and the diversity of trajectory tasks, achieving unified trajectory modelling remains an important yet challenging task. In this paper, we propose TrajAgent, a large language model-based agentic framework, to unify various trajectory modelling tasks. In TrajAgent, we first develop UniEnv, an execution environment with a unified data and model interface, to support the execution and training of various models. Building on UniEnv, we introduce TAgent, an agentic workflow designed for automatic trajectory modelling across various trajectory tasks. Specifically, we design AutOpt, a systematic optimization module within TAgent, to further improve the performance of the integrated model. With diverse trajectory tasks input in natural language, TrajAgent automatically generates competitive results via training and executing appropriate models. Extensive experiments on four tasks using four real-world datasets demonstrate the effectiveness of TrajAgent in unified trajectory modelling, achieving an average performance improvement of 15.43% over baseline methods.

Multi‐objective strategy‐based resource allocation and performance improvements in 5G and beyond wireless networks

“…Generally, the Long Term Evolution‐Advanced (LTE‐A) networks degrade because of its lagging in QoS and energy efficiency. To manage these issues, Du et al 5 made an RB allocation process by combining the genetic algorithm (GA) with the particle swarm optimization (PSO) algorithms. It divided and examined as three subproblems, namely, the Modulation and Coding Scheme (MCS), the RB allocation, and the power distribution.…”

“…To attain the alike, the best location of cat (i.e., node) is mutated. The Cauchy mutation operator is described by means of Equations ( 4) and (5).…”

Optimal location management in LTE networks using evolutionary techniques

“…The two techniques have been jointly used to enhance the speed of the convergence while finding the optimal solution. A more detailed study by the same authors which follows the same approach was addressed in another study . The proposed study uses the same techniques to solve the radio resource allocation problem in order to maximize the energy efficiency in the system under the quality of service constraints.…”

“…A more detailed study by the same authors which follows the same approach was addressed in another study. 7 The proposed study uses the same techniques to solve the radio resource allocation problem in order to maximize the energy efficiency in the system under the quality of service constraints. The problem consisted of three subproblems, namely resource blocks allocation, power distribution, and modulation schemes assignment problem.…”

A Joint Modulation-Coding Scheme and Resource Allocation in LTE Uplink

“…There are few studies focused on the performance of joint MCS and PRBs assignment for the LTE UL. In [9], a downlink (DL) FDPS, together with the MCS assignment algorithm, provide system reliability by the allocation of a lower order MCS to users who have poor channel quality. Nevertheless, the DL FDPS does not comply with the contiguity constraint of a UL FDPS.…”