Resource Allocation in Multi-User Cellular Networks:A Transformer-Based Deep Reinforcement Learning Approach

To meet the communication services with diverse requirements,dynamic resource allocation has shown increasing importance.In this paper,we consider the multi-slot and multi-user resource allocation(MSMU-RA)in a downlink cellular scenario with the aim of maximizing system spectral efficiency while guaranteeing user fairness.We first model the MSMURA problem as a dual-sequence decision-making process,and then solve it by a novel Transformerbased deep reinforcement learning(TDRL)approach.Specifically,the proposed TDRL approach can be achieved based on two aspects:1)To adapt to the dynamic wireless environment,the proximal policy optimization(PPO)algorithm is used to optimize the multi-slot RA strategy.2)To avoid co-channel interference,the Transformer-based PPO algorithm is presented to obtain the optimal multi-user RA scheme by exploring the mapping between user sequence and resource sequence.Experimental results show that:i)the proposed approach outperforms both the traditional and DRL methods in spectral efficiency and user fairness,ii)the proposed algorithm is superior to DRL approaches in terms of convergence speed and generalization performance.

Downlink Resource Allocation for NOMA-Based Hybrid Spectrum Access in Cognitive Network

To solve the contradiction between limited spectrum resources and increasing communication demand,this paper proposes a wireless resource allocation scheme based on the Deep Q Network(DQN)to allocate radio resources in a downlink multi-user cognitive radio(CR)network with slicing.Secondary users(SUs)are multiplexed using non-orthogonal multiple access(NOMA).The SUs use the hybrid spectrum access mode to improve the spectral efficiency(SE).Considering the demand for multiple services,the enhanced mobile broadband(eMBB)slice and ultrareliable low-latency communication(URLLC)slice were established.The proposed scheme can maximize the SE while ensuring Quality of Service(QoS)for the users.This study established a mapping relationship between resource allocation and the DQN algorithm in the CR-NOMA network.According to the signal-to-interference-plusnoise ratio(SINR)of the primary users(PUs),the proposed scheme can output the optimal channel selection and power allocation.The simulation results reveal that the proposed scheme can converge faster and obtain higher rewards compared with the Q-Learning scheme.Additionally,the proposed scheme has better SE than both the overlay and underlay only modes.

Joint Optimization of Satisfaction Index and Spectrum Efficiency with Cache Restricted for Resource Allocation in Multi-Beam Satellite Systems

Dynamic resource allocation(DRA) is a key technology to improve system performances in GEO multi-beam satellite systems. And, since the cache resource on the satellite is very valuable and limited, DRA problem under restricted cache resources is also an important issue to be studied. This paper mainly investigates the DRA problem of carrier resources under certain cache constraints. What's more, with the aim to satisfy all users' traffic demands as more as possible, and to maximize the utilization of the bandwidth, we formulate a multi-objective optimization problem(MOP) where the satisfaction index and the spectrum efficiency are jointly optimized. A modified strategy SA-NSGAII which combines simulated annealing(SA) and non-dominated sorted genetic algorithm-II(NSGAII) is proposed to approximate the Pareto solution to this MOP problem. Simulation results show the effectiveness of the proposed algorithm in terms of satisfaction index, spectrum efficiency, occupied cache, and etc.

A Resource Scheduling Scheme for Spectrum Aggregation in Cognitive Radio Based Heterogeneous Networks

In spectrum aggregation(SA), two or more component carriers(CCs) of different bandwidths in different bands can be aggregated to support wider transmission bandwidth. The current resource scheduling schemes for spectrum aggregation are not optimal or suitable for CR based heterogeneous networks(Het Nets). Consequently, the authors propose a novel resource scheduling scheme for spectrum aggregation in CR based Het Nets, termed as cognitive radio based resource scheduling(CR-RS) scheme. CR-RS has a three-level structure. Under a dynamic traffic model, an equivalent throughput of the CCs based on the knowledge of primary users(PUs) is given. On this basis, the CR users data transmission time of each CC is equal in CR-RS. The simulation results show that CR-RS has the better performance than the current resource scheduling schemes in the CR based Het Nets. Meanwhile, CR-RS is also effective in other spectrum aggregation systems which are not CR based HetNets.

Screening of Broad-spectrum Resistance Resources against Rice Bacterial Leaf Streak

[ Objectives] Rice materials with broad-spectrum resistance against several pathogenic strains of Xanthomans oryzae pv. Oryzicola （Xooc） at multiple growth stages were screened, in order to provide reliable resistance sources for variety breeding against rice bacterial leaf streak. [ Methods] A total of 1 100 rice lines with rich genetic background were offered as selective objects, and highly susceptible cultivar Jingang 30 was used as the control. Inoculation was carried out with five strong pathogenic strains of Xooc through acupuncture method at various growth stages for resistance identification. [ Results] Fourteen disease-resistant materials were obtained through preliminary screening, accounting for 1.27% of the total materials. Nine materials moderately resistant to bacterial leaf streak were obtained via secondary screening, accounting for 0.82% of the total materials. Besides, three of them （ RL6, RL9 and RLL4） were resistant to a number of pathogenic strains of Xooc at three growth stages. In particular, RL16 presented broad-spectrum resistance to multi-strains with high resistance levels. Six of them （ RI2, RIA, RIS, RL8, RL11 and RL12） were resistant to single strain at single growth stage. [ Conclusions] The obtained three materials have broad-spectrum resistance to bacterial leaf streak at multiple growth stages, which can be served as an important source to cultivate disease-resistant rice varieties. RL6 maintains high broad-spectrum resistance at all growth stages, which can be used as a prior resistance source for rice variety breeding. Six materials obtained with resistance against bacterial leaf streak at particular growth stages can be used as candidate resistance sources.

Spectrum Resource Management of Cognitive Radio

As the most important technology of CR, the wireless spectrum resource management technology is the key to CR performance improvement. By introducing the concept of resource space to describe wireless spectrum resource management in the field of CR technology, a data system of wireless resource management is formed that covers wireless spectrum resource space, resource grid and available resource atlas. Besides, the corresponding lamination distributional management structure and the resource management database are constructed. The resources description system and the management structure will become the theoretical concept foundation and reference of the CR spectrum resources management technology.

基于硬件损伤的认知反向散射通信网络鲁棒安全资源分配算法

为了提高反向散射通信网络频谱效率、传输鲁棒性及信息安全性,该文提出一种基于硬件损伤的认知反向散射通信网络鲁棒安全资源分配算法。首先,考虑认知反向散射用户的最小安全速率、传输时间、能量收集和反射系数等约束,基于有界信道不确定性和频谱感知误差模型,建立一个多变量耦合的吞吐量最大化非凸资源分配问题。其次,利用最坏准则、连续凸近似和交替优化方法,将原问题转换为凸优化问题,并提出一种基于迭代的鲁棒资源分配算法。仿真结果表明,与现有算法对比,所提算法具有较好的鲁棒性。

波谱分析一流课程建设与课堂教学改革探索

一流课程建设是高校质量工程建设的中心工作,是保证高校人才培养目标实现的重要举措,是促进高校教学改革和提升人才培养质量的关键,是高等学校“双一流”建设的核心内容。从课程建设历程、一流教材、一流师资、一流教学方法及一流教学管理等方面对波谱分析一流课程建设进行探讨,以期为同行的一流课程建设提供参考。

山东半岛南部海域鱼类群落生物量粒径谱季节变化

为了解山东半岛南部海域鱼类群落粒径结构特征,本文根据2016—2017年渔业资源底拖网季度调查数据,构建了山东半岛南部海域鱼类生物量粒径谱,分析了该海域鱼类群落的粒径结构特征及其季节变化。研究表明,山东半岛南部海域Sheldon型鱼类生物量粒径谱呈双峰模式,鱼类粒径范围为2~12粒径级,粒径分布相对均匀,出现波峰的粒径区间存在季节差异,春、夏季第一个波峰出现在3~4粒径级,主要由细纹狮子鱼(Liparis tanakae)、方氏云鳚(Pholis fangi)和大泷六线鱼(Hexagrammos otakii)等种类组成。秋、冬季第一个波峰出现在5~6粒径级,主要由小眼绿鳍鱼(Chelidonichthys spinosus)、长蛇鲻(Saurida elongata)和斑鰶(Konosirus punctatus)等种类组成。四个季节的第二个波峰均由细纹狮子鱼、黄鮟鱇(Lophius litulon)和大头鳕(Gadus macrocephalus)等鱼类个体组成。全部鱼类群落标准化生物量粒径谱的斜率和截距存在季节差异,其中夏季粒径谱陡峭,截距值显著高于其他季节,而冬季粒径谱最平缓,截距值最小,粒径谱斜率和截距的变化主要受当年生幼鱼群体的影响。在山东半岛南部海域,底层鱼类群落与全部鱼类群落的标准化生物量粒径谱的变化趋势相似。在同一季节,底层鱼类群落与全部鱼类群落的标准化生物量粒径谱斜率和截距之间无显著性差异(P>0.05),而暖温性鱼类群落与全部鱼类群落之间存在显著性差异(P<0.05)。山东半岛南部海域的全部鱼类群落粒径结构以小粒径鱼类为主,大型鱼种和大个体较少。鱼类的种类组成有明显的季节变化,当年生幼鱼及洄游性鱼类的个体数量变化是影响该海域鱼类群落粒径结构的主要因素。

面向6G网络的频谱定价机制演进与展望

6G网络的异构性和复杂性将进一步提高,可用频段愈渐短缺,迫切需要更为灵活高效的频谱资源管理模式。使用市场化定价手段促进频谱资源的高效利用,为纾解6G频谱短缺困境提供了解决方案。首先简要分析了6G移动网络的频谱资源新特点,接着梳理了数十年来频谱管理和定价机制的演进进程,包括基于博弈论、拍卖模型的定价机制研究和基于人工智能的定价机制研究等成果。最后,对面向6G移动网络的频谱定价机制进行了展望,为标准化工作提供借鉴和参考。

面向非完全电磁信息的智能频谱分配技术研究

针对电磁对抗过程中环境动态变化,多节点自主用频决策频谱利用率低的问题,该文开展面向非完全电磁信息的智能协同频谱分配技术研究,通过多节点智能协同提升频谱利用率。首先将复杂电磁环境频谱分配问题建模为最大化用频设备的优化问题,其次提出一种基于多节点协同分流经验回放机制的资源决策算法(CoDDQN),算法基于协同分流函数对历史经验数据进行评估,并通过分级经验池进行训练,使各智能体在仅观测自身状态信息条件下形成轻量级协同决策能力,解决低视度条件下多节点决策优化方向与整体优化目标不一致的问题,提升频谱利用率;设计了一种基于置信分配的混合奖励函数,各节点决策兼顾个体的奖励,能够减少惰性节点的出现,探索更优的整体动作策略,进一步提升系统效益。仿真结果表明:当节点数为20时,所提算法的可接入设备数优于全局贪婪算法与遗传算法,并与信息完全共享的集中式频谱分配算法的差距在5%内,更适用于低视度节点的协同频谱分配。

基于频谱效用的频率优化分配算法及策略分析

针对联合作战条件下多业务用频装备频率分配问题,引入频谱效用的概念,设计了能够综合考量装备用频优先级、用频效能、用频需求等频率分配关键影响因素的频谱效用函数。以频谱效用最大化为优化目标,可用频谱资源、整数决策变量和公平分配限制为约束条件,建立了频率优化分配模型,并给出了不完全约束条件下的近似解析解,以及完全约束条件下基于最大边际效用的准最优算法。仿真实验验证了算法的有效性,对频率分配公平性的调节作用,以及对频谱容量优先、任务优先、用频效能优先等频率分配典型策略的支撑作用。

文山壮族苗族自治州无线电监测工作分析与思考

随着社会经济的不断发展,特别是以数字经济为代表的新型经济得到蓬勃发展,社会用频设台需求激增,民航、水运、气象以及森林防火等重要无线电业务的安全保障任务日趋繁重,保护良好的电磁环境和电磁频谱空间安全任务更加艰巨,给地方无线电监管工作提出更高要求。文章针对云南省文山州无线电监管技术力量建设现状进行分析,剖析存在的不足和问题,提出提升文山州无线电监测能力的相关建议,为文山州无线电监管能力提升提供参考。

雷达通信感知一体化研究综述

随着第五代移动通信技术的迅猛发展,军事和民用领域对于无线电频谱资源的需求不断增长。在这一时代背景下,雷达与通信的融合技术成为国内外学者关注的研究热点。对此,深入分析雷达通信一体化技术的发展现状,涵盖国内外的研究动态和技术进展。首先详细梳理雷达通信一体化技术的发展历程,阐释其在现代通信系统中的重要性及应用前景。其次,重点论述信号处理的一体化。最后,在分析现有成果的基础上,展望雷达通信一体化技术的未来走向。针对在推动雷达通信一体化技术商业化和实际应用中可能遇到的挑战,提出相应的解决策略和建议,为未来的研究和应用提供重要的思路和方向。

基于自学习机制的广电频谱资源配置模型设计与仿真

频谱资源在广电领域乃至整个无线通信领域都是不可或缺的宝贵资源,如何通过高效的资源配置提升频谱资源的利用率是通信史上一个亘古不变的问题.本文通过基于博弈的自学习机制对广电频谱资源配置模型进行了设计与仿真,即将传统自学习机制与博弈相融合并运用在广电资源频谱分配中提高频谱分配效率.随着迭代次数的增加,从记忆长度、用户数量以及用户占有不同频段等角度,通过对用户收益、频谱利用率等参数的计算、仿真来观察自学习机制对于频谱资源分配的效益的影响,进而得出就分配效率和收敛速度而言,优化后的自学习机制优于传统自学习机制.

基于人工智能的高速公路通信系统中的频谱资源分配与优化

随着高速公路通信系统的快速发展,有效利用频谱资源成为一项重要挑战。文章深入研究基于人工智能的高速公路通信系统中的频谱资源分配与优化的策略。主要介绍我国高速公路通信系统的结构,分析频谱资源的独特性及其面临的挑战,详细探讨人工智能在通信系统中的作用。本研究综合考察了当前频谱资源分配策略,包括传统模式和优化算法。进一步提出了基于人工智能技术的新型频谱资源配置与优化方案,涵盖神经网络和强化学习等算法,以及混合智能优化策略和自适应频谱资源管理方法。

基于5G技术的广电传输网络优化策略研究

文中探讨了基于5G技术的广电传输网络优化策略。首先,概述了5G技术的核心特性,并分析了其在广电传输网络中的应用潜力。接着,详细讨论了网络架构优化、频谱资源优化、传输技术升级等方面的优化策略。该研究旨在为广电传输网络的优化提供理论支持和实践指导。

Cooperative Spectrum Allocation with QoS Support in Cognitive Cooperative Vehicular Ad Hoc Networks

To solve the contradiction between the increasing demand of diverse vehicular wireless applications and the shortage of spectrum resource,a novel cognitive cooperative vehicular ad-hoc network(CCVANET) framework is proposed in this paper.Firstly,we develop an adaptive cognitive spectrum sensing(ACSS) mechanism which can help to trigger and adjust the spectrum sensing window according to network traffic load status and communication quality.And then,Generalized Nash Bargaining Solution(GNBS),which can achieve a good tradeoff between efficiency and weighted fairness,is proposed to formulate the asymmetric intercell resource allocation.Finally,GNBSSafety(GNBS-S) scheme is developed to enhance the Quality of Service(QoS) of safety applications,especially in the heavy load status,where the bandwidth demanded and supplied cannot be matched well.Furthermore,the primary user activity(PUA)which can cause rate loss to secondary users,is also considered to alleviate its influence to fairness.Simulation results indicate that the proposed CC-VANET scheme can greatly improve the spectrum efficiency and reduce the transmission delay and packet loss rate on the heavy contention status.And GNBS spectrum allocation scheme outperforms both the Max-min and Max-rate schemes,and can enhance the communication reliability of safety service considerably in CC-VANET.

Dynamic System Level Frequency Spectrum Allocation Scheme Based on Cognitive Radio Technology

Cognitive radio is being widely discussed,and resource allocation scheme is drawing a lot of attention.Although the existed resource allocation strategies have successfully enhanced spectrum efficiency,some critical challenges still remain unanswered such as the jointly consideration of the efficiency and fairness,the rational description of the spectrum resources,and the execution mode of the spectrum allocation.This paper presents a system level dynamic frequency spectrum allocation scheme based on a central heterogeneous network architecture,evaluates the matching degree of the spectrum demand and the available spectrum resources with corresponding matrices,jointly considers the efficiency and fairness of different cognitive radio systems.Simulation results and the application scenario are also presented and analyzed.

Training Plan for Software Engineering Top Talents Based on the Demand for High-end Talents in the Industry

The paper illustrates the reason of the lack of talents with outstanding innovative practice ability and engineering leadership has become a great obstacle for many industries, represented by the software industry, to develop along with the new era, and restricted the evolution of these industries toward the high end. With the target of training talents with innovation capacity and engineering leadership, the training plan for top talents based on the demand for high-end talents in the software engineering industry is put forward, and analyses are given on significant aspects including the development of the training resource system, the screening of students and the selection of enterprises, the teaching staff construction for university-enterprise cooperation, the establishment of a management system with joint effort for talents development, and the construction of process quality guarantee mechanism. In the end, for the implementation of the training plan, it is pointed out that the university-enterprise cooperative development mechanism should be perfected, the talents development practice should be enhanced, the personalized training of students should be emphasized, and the innovative ability in practice and the engineering leadership of students should be practically improved.