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.

Multi-Strategy Dynamic Spectrum Access in Cognitive Radio Networks: Modeling, Analysis and Optimization

Dynamic spectrum access(DSA) based on cognitive radios(CR) technique is an effective approach to address the "spectrum scarcity" issue. However, traditional CR-enabled DSA system employs only single DSA strategy, which might not be suited to the dynamic network environment. In this paper, we propose a multi-strategy DSA(MS-DSA) system, where the primary and the secondary system share spectrum resources with multiple DSA strategies simultaneously. To analyze the performance of the proposed MS-DSA system, we model it as a continuous-time Markov chain(CTMC) and derive the expressions to compute the corresponding performance metrics. Based on this, we define a utility function involving the concerns of effective throughput, interference quantity on primary users, and spectrum leasing cost. Two optimization schemes, named as spectrum allocation and false alarm probability selection, are proposed to maximize the utility function. Finally, numerical simulations are provided to validate our analysis and demonstrate that the performance can be significantly improved caused by virtues of the proposed MS-DSA system.

A Dynamic Distributed Spectrum Allocation Mechanism Based on Game Model in Fog Radio Access Networks

With the explosive growth of highspeed wireless data demand and the number of mobile devices, fog radio access networks(F-RAN) with multi-layer network structure becomes a hot topic in recent research. Meanwhile, due to the rapid growth of mobile communication traffic, high cost and the scarcity of wireless resources, it is especially important to develop an efficient radio resource management mechanism. In this paper, we focus on the shortcomings of resource waste, and we consider the actual situation of base station dynamic coverage and user requirements. We propose a spectrum pricing and allocation scheme based on Stackelberg game model under F-RAN framework, realizing the allocation of resource on demand. This scheme studies the double game between the users and the operators, as well as between the traditional operators and the virtual operators, maximizing the profits of the operators. At the same time, spectrum reuse technology is adopted to improve the utilization of network resource. By analyzing the simulation results, it is verified that our proposed scheme can not only avoid resource waste, but also effectively improve the operator's revenue efficiency and overall network resource utilization.

A DYNAMIC SPECTRUM ACCESS NETWORK BASED ON COGNITIVE RADIO

Dynamic spectrum access technologies based on Cognitive Radio(CR) is under intensive research carried out by the wireless communication society and is expected to solve the problem of spectrum scarcity.However,most enabling technologies related to dynamic spectrum access are con-sidered individually.In this paper,we consider these key technologies jointly and introduce a new implementation scheme for a Dynamic Spectrum Access Network Based on Cognitive Radio(DSAN-BCR).We start with a flexible hardware platform for DSAN-BCR,as well as a flexible protocol structure that dominates the operation of DSAN-BCR.We then focus on the state of the art of key technologies such as spectrum sensing,spectrum resources management,dynamic spectrum access,and routing that are below the network layer in DSAN-BCR,as well as the development of technologies related to higher layers.Last but not the least,we analyze the challenges confronted by these men-tioned technologies in DSAN-BCR,and give the perspectives on the future development of these technologies.The DSAN-BCR introduced is expected to provide a system level guidance to alleviate the problem of spectrum scarcity.

Reinforcement Learning Based Dynamic Spectrum Access in Cognitive Internet of Vehicles

Cognitive Internet of Vehicles(CIoV)can improve spectrum utilization by accessing the spectrum licensed to primary user(PU)under the premise of not disturbing the PU’s transmissions.However,the traditional static spectrum access makes the CIoV unable to adapt to the various spectrum environments.In this paper,a reinforcement learning based dynamic spectrum access scheme is proposed to improve the transmission performance of the CIoV in the licensed spectrum,and avoid causing harmful interference to the PU.The frame structure of the CIoV is separated into sensing period and access period,whereby the CIoV can optimize the transmission parameters in the access period according to the spectrum decisions in the sensing period.Considering both detection probability and false alarm probability,a Q-learning based spectrum access algorithm is proposed for the CIoV to intelligently select the optimal channel,bandwidth and transmit power under the dynamic spectrum states and various spectrum sensing performance.The simulations have shown that compared with the traditional non-learning spectrum access algorithm,the proposed Q-learning algorithm can effectively improve the spectral efficiency and throughput of the CIoV as well as decrease the interference power to the PU.

Orthogonal Codes-Based Dynamic Spectrum Access in Cognitive Radio Networks

Dynamic spectrum access(DSA) in cognitive radio(CR) networks became a challenging research area recently. In CR technology, the DSA between primary users(PUs) and secondary users(SUs) simultaneously can be achieved without degrading the performance of the PUs by SUs interference. This can be achieved by donating incentive power to the PUs in order to compensate the interference caused by the SUs. Consequently, PUs allow SUs to share the spectrum. In this paper, orthogonal codes-based dynamic spectrum access(OC-DSA) technique is proposed. OC-DSA technique employs orthogonality between PUs and SUs transmitted data symbols in addition to the incentive power donation. Compared to other techniques, the proposed technique uses a simple encoder at the SU network for the same PU network infrastructure. By applying orthogonal codes, the interference caused by SUs is canceled and hence the donated power to incentivize the PUs is reduced. Also, the SU packet rate is increased significantly. The simulation results show that the proposed technique provides effective improvements over other existing techniques in the signal strength and the bit error rate performance of both the PU network and the SU network at the receiver side. Moreover, the proposed technique requires less donated power to incentivize the PU and has higher packet rate.

Dynamic Spectrum Access Based on Prior Knowledge Enabled Reinforcement Learning with Double Actions in Complex Electromagnetic Environment

The spectrum access problem of cognitive users in the fast-changing dynamic interference spectrum environment is addressed in this paper.The prior knowledge for the dynamic spectrum access is modeled and a reliability quantification scheme is presented to guide the use of the prior knowledge in the learning process.Furthermore,a spectrum access scheme based on the prior knowledge enabled RL(PKRL)is designed,which effectively improved the learning efficiency and provided a solution for users to better adapt to the fast-changing and high-density electromagnetic environment.Compared with the existing methods,the proposed algorithm can adjust the access channel online according to historical information and improve the efficiency of the algorithm to obtain the optimal access policy.Simulation results show that,the convergence speed of the learning is improved by about 66%with the invariant average throughput.

Energy Aware Spectrum Access in Cognitive Radio Networks with Imperfect Channel Sensing

Due to the problem of spectrum underutilization and energy inefficiency in wireless communications,the research on energy efficient Cognitive Radio Networks (CRNs) has received significant attention in both industry and academia.In this paper,we consider the problem of optimal spectrum selection and transmission parameters design with the objective of minimizing energy consumption in CRNs.Since the system state cannot be directly observed due to miss detections and estimation errors,we formulate the optimal spectrum access problem as a Partially Observable Markov Decision Process (POMDP).In particular,the proposed scheme selects the optimal spectrum,modulation and coding scheme,transmission power,and link layer frame size in each time slot according to the belief state,which captures all the history information of past actions and observations.The optimal policy can be acquired by solving POMDP problem with linear programming based algorithm.Simulation results show that significant energy savings can be achieved by the proposed scheme.

A Frequency－Diversity Spread－Spectrum Multiple Access System with Random Signature Sequences

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Throughput Analysis of Dynamic Spectrum Anti-Jamming Multiple-Access in HF Communication Systems

A multiple-access networking scheme based on the new dynamic spectrum anti-jamming system is proposed in this paper. The network consists of a center node and multiple user nodes. The center node detects spectrum holes in the operation band periodically according to the user performance target. Detected spectrum holes are allocated to users who request communication. Throughput of this networking scheme is analyzed over a high-frequency(HF) interference channel. The effect of error correction coding and spectrum hole information transmission error is discussed. Throughput of this scheme and conventional frequency-hopping multiple-access(FHMA) scheme are compared. Results show that user performance increase leads to throughput decrease, which can be offset by error correction coding. If spectrum hole information transmission is in error, the throughput is not affected much as long as the bit error rate is below 10-2. Furthermore, throughput of this scheme is obviously superior to the throughput of FHMA scheme.

Database-Assisted Dynamic Spectrum Access with QoS Guarantees:A Double-Phase Auction Approach

Since FCC's opening for white space(WS) utilization,database-assisted dynamic spectrum access(DSA) has become the de facto solution for the realization of dynamic spectrum sharing(DSS),due to its simplicity and compatibility with commercial off-the-shelf(COTS) devices.It is envisioned that such technology will strongly support the prosperous wireless multimedia networking(WMN) applications with satisfying QoS guarantees in the future.However,how to counter the time-frequency variant property when exploiting the WS spectrum for the provision of these services to secondary users(SUs) still remains a great challenge.In such context,a dynamic secondary access scheme for database-assisted spectrum sharing networks is proposed in this paper.In the beginning,the spectrum requirements of SUs for diverse services are modeled by considering the minimum required service data-rate and spectrum access duration.Afterwards,the spectrum demand evaluation and bidding policy are formulated based on the service classes of SUs.Furthermore,a doublephase(DP) spectrum allocation scheme,which consists of the initial resource allocation phase and resource allocation adjustment phase,is carefully designed for DSA.Finally,extensive simulations are conducted and the results demonstrate that our scheme can increase the spectrum trading revenue and adapt to varying service requirements.

User-Based Discrete-Time Queuing Analysis for Opportunistic Spectrum Access in Cognitive Radio Networks

In cognitive radio networks, the spectrum utilization can be improved by cognitive users opportunistically using the idle channels licensed to the primary users. However, the new arrived cognitive users may not be able to use the channel immediately since the channel usage state is random. This will impose additional time delay for the cognitive users. Excessive waiting delay can make cognitive users miss the spectrum access chances. In this paper, a discrete-time Markov queuing model from a macro point of view is provided. Through the matrix-geometric solution theory, the average sojourn time for cognitive users in the steady state before accessing the spectrum is obtained. Given the tolerant delay of cognitive users, the macro-based throughput is derived and an access control mechanism is proposed. The numerical results show the effects of service completion probability on average sojourn time and throughput. It is confirmed that the throughput can be obviously improved by using the proposed access control mechanism. Finally, the performance evaluations based on users are compared to that based on data packets.

Combinatory Spread－Spectrum Multiple－Access Based on Residue Number System：System and Performance

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MULTI-CHANNEL TRANSMISSION STRATEGY FOR DYNAMIC SPECTRUM ACCESS

Cognitive radio is a promising technology that deals with the scarcity of radio spectrum. In this paper, we propose a new multi-channel transmission strategy for dynamic spectrum access in cognitive radio network. Starting with the model of spectrum activities, we present the multi-channel transmission strategy which has primary user's protection mechanism to improve the spectrum efficiency and study its performance under perfect and imperfect sensing. Numerical example results reveal that the performance of the proposed strategy has the superiority with respect to capacity performance of cognitive users and the protection of primary users.

Dynamic Spectrum Access Scheme of Variable Service Rate and Optimal Buffer-Based in Cognitive Radio

Dynamic spectrum access (DSA) scheme in Cognitive Radio (CR) can solve the current problem of scarce spectrum resource effectively, in which the unlicensed users (i.e. Second Users, SUs) can access the licensed spectrum in opportunistic ways without interference to the licensed users (i.e. Primary Users, PUs). However, SUs have to vacate the spectrum because of PUs coming, in this case the spectrum switch occurs, and it leads to the increasing of SUs’ delay. In this paper, we proposed a Variable Service Rate (VSR) scheme with the switch buffer as to real-time traffic (such as VoIP, Video), in order to decrease the average switch delay of SUs and improve the other performance. Different from previous studies, the main characteristics of our studying of VSR in this paper as follows: 1) Our study is on the condition of real-time traffic and we establish three-dimension Markov model;2) Using the internal optimization strategy, including switching buffer, optimizing buffer and variable service rate;3) As to the real-time traffic, on the condition of meeting the Quality of Service(QoS) on dropping probability, the average switch delay is decreased as well as improving the other performance. By extensive simulation and numerical analysis, the performance of real-time traffic is improved greatly on the condition of ensuring its dropping probability. The result fully demonstrates the feasibility and effectiveness of the variable service rate scheme.

Media Access with Spatial Reuse for Cooperative Spectrum Sensing

The increasing interest for wireless communication services and scarcity of radio spectrum resources have created the need for a more flexible and efficient usage of the radio frequency bands. Cognitive Radio (CR) emerges as an important trend for a solution to this problem. Spectrum sensing is a crucial function in a CR system. Cooperative spectrum sensing can overcome fading and shadowing effects, and hence increase the reliability of primary user detection. In this paper we consider a system model of a dedicated detect-andforward wireless sensor network (DetF WSN) for cooperative spectrum sensing with k-out-of-n decision fusion in the presence of reporting channels errors. Using this model we consider the design of a spatial reuse media access control (MAC) protocol based on TDMA/OFDMA to resolve conflicts and conserve resources for intra-WSN communication. The influence of the MAC protocol on spectrum sensing performance of the WSN is a key consideration. Two design approaches, using greedy and adaptive simulated annealing (ASA) algorithms, are considered in detail. Performance results assuming a grid network in a Rician fading environment are presented for the two design approaches.

Dynamic Spectrum Access Protocol for the Digital Dividend

It is not more and more, easy to satisfy the important and growing spectrum demands in the context of the static conventional policy spectrum allocation. Therefore, to find a suitable solution to this problem, we are to days observing the apparition of flexible dynamic spectrum allocation methods. These methods that ought to improve more significantly the spectrum use have gained much interest. In fact, the digital dividend due to the change-over from the analog television to the digital terrestrial television must be efficiently used. So the Dynamic Spectrum Access (DSA) can potentially play a key role in shaping the future digital dividend use. In the DSA, two kinds of users or networks coexist on different channels. The first one, known as the primary user, accesses to a channel with high priority;and the second one, known as secondary user has a low priority. This paper presents a dynamic spectrum access protocol based on an auction framework. Our protocol is an interesting tool that allows the networks to bid and obtain on the available spectrum, the rights to be primary and secondary users according their valuations and traffic needs. Based on certain offers, our protocol selects primary and secondary users for each idle channel in order to realize the maximum economic for the regulator or social benefits. We deal with the case in which the offers of the networks are independent one another even if they will share the same channels. We design an algorithm in accordance with our dynamic spectrum access protocol. The algorithm is used here to find an optimal solution to the access allocation problem, specifically to digital dividend. Finally, the results in the numeric section, regarding the three suggested scenarios, show that the proposed dynamic spectrum access protocol is viable. The algorithm is able to eliminate all non-compliant bidders for the available spectrum sharing. We notice that the revenue or social benefits of the regulator is maximized when we have on each channel, one primary user and the maximum number of secondary users.

Traffic sensitive spectrum access scheme for cognitive radio networks

A traffic sensitive spectrum access scheme is proposed to satisfy the traffic load requirement of secondary users(SUs).In the proposed design,SU only accesses available channels which can meet the traffic demand.To achieve this,the expected transmission time(ETT) of the SU is calculated first based on the delivery ratio.Then,the channel idle time is estimated based on the activity of primary users(PUs).Therefore,available channels with estimated idle time longer than ETT could be chosen.With high probability,the SU can finish transmission on these channels without disruption,thereby satisfying the traffic load demand of the SU.Finally,our method is extended to the multi-channel scenario where each SU can access multiple channels simultaneously.Performance analysis shows that our method satisfies the requirement of SUs while effectively improving the throughput.

一种多用户频谱分配优化模型建立与求解

为解决多区域多用户在通信过程中的频谱最优分配与激励问题,本文首先在考虑多个通信运营商及多个小区用户的情况下,通过区块链理论对不同小区不同用户的频谱分配问题进行分析建模,并建立频谱最优分配优化模型;其次,针对优化模型的约束条件,通过引入拉格朗日及二分法理论对其进行求解,进而得出不同小区用户人数与频谱分配之间的数学关系;最后,通过仿真证明了容纳小区人数与频谱持有量近似地呈线性关系,且基站功率越大,近似直线的斜率越大。当基站的持有频谱量较少时,提高功率对可容纳人数的增加影响较小,随着频谱量的增加,提高基站功率,可容纳人数随之近似线性增加。

面向数据传输稳定性的无人机群频谱接入方法

针对频繁变化的无线通信环境中无人机群频谱资源使用问题,在保障无人机数据传输稳定的前提下,以降低无人机间用频冲突率、提升信道利用率和系统吞吐量为目标,设计了基于多用户非耦合排队频谱接入方法。该方法中无人机之间不需要信息交互和中心控制节点,仅需根据自身数据传输需求、互扰功率和历史信道使用状态信息来构建学习效益函数,生成频谱使用策略。仿真结果表明,所提方法在确保无人机数据传输稳定和兼顾无人机用频公平性的前提下,能有效降低无人机间用频冲突,提升无人机群吞吐量。