MODELING RADIO RESOURCE MANAGEMENT IN COGNITIVE RADIO SYSTEM BASED ON OFDMA USING COLORED PETRI NET

Cognitive Radio(CR) system based on Orthogonal Frequency Division Multiple Access(OFDMA),such as Wireless Regional Area Networks(WRAN) and Worldwide Interoperability for Microwave Access(WiMAX),often attempt to improve performance via dynamic radio resource management,which is characterized as concurrent processing of different traffic and nondeterministic system capacity.It is essential to design and evaluate such complex system using proper modeling and analysis tools.In the previous work,most of the communication systems were modeled as Markov Chain(MC) and Stochastic Petri Nets(SPN),which have the explicit limitation in evaluating adaptive OFDMA CR system with wide area traffic.In this paper,we develop an executable top-down hier-archical Colored Petri Net(CPN) model for adaptive OFDMA CR system,and analyze its performance using CPN tools.The results demonstrate that the CPN can model different radio resource manage-ment algorithms in CR Systems,and the CPN tools require less computational effort than Markov model using Matlab,with its flexibility and adaptability to the traffics which arrival interval and processing time are not exponentially distributed.

Utility-based and fairness-aware radio resource allocation in OFDMA cellular relay networks with traffic prioritization

The combination of orthogonal frequency division multiple access(OFDMA) with relaying techniques provides plentiful opportunities for high-performance and cost-effective networks.It requires intelligent radio resource management schemes to harness these opportunities.This paper investigates the utility-based resource allocation problem in a real-time and non-real-time traffics mixed OFDMA cellular relay network to exploit the potentiality of relay.In order to apply utility theory to obtain an efficient tradeoff between throughput and fairness as well as satisfy the delay requirements of real-time traffics,a joint routing and scheduling scheme is proposed to resolve the resource allocation problem.Additionally,a low-complexity iterative algorithm is introduced to realize the scheme.The numerical results indicate that besides meeting the delay requirements of real-time traffic,the scheme can achieve the tradeoff between throughput and fairness effectively.

ZTE 's WCDMA Radio Resource Management Strategy

WCDMA Radio Resource Management (RRM) controls the allocation and usage of all radio resources. The purpose of RRM is to have optimal coverage and capacity while ensuring the QoS. RRM directly affects the system performance. As the soul of system control, it includes power control, handoff control, load control, admission control, code allocation, etc. This paper introduces the RRM strategy of ZTE's WCDMA equipment.

Adaptive radio resource allocation for multiple traffic OFDMA broadband wireless access system

In this article, an adaptive radio resource ＂allocation algorithm applied to multiple traffic orthogonal frequency division multiple access （OFDMA） system is proposed, which distributes subcarriers and bits among users according to their different quality of service requirements and traffic type. By classifying and priorifizing the users based on their traffic characteristic and ensuring resource for higher priority users, the new scheme decreases tremendously the outage probability of the users requiring a real-time transmission without impact on the spectrum efficiency of system, as well as the outage probability of data users is not increased compared with the radio resource allocation methods published.

Joint Downlink Scheduling and Radio Resource Allocation for User-Individual QoS in Adaptive OFDMA Wireless Communication Systems

This paper proposes and analyzes a downlink multi-carrier proportional fair scheduler and an adaptive radio resource allocation algorithm combining the scheduler. This scheduler and algorithm are suitable for orthogonal frequency division multiple access wireless communication systems supporting multiple quality of service classes. Our results demonstrate that the scheduler and algorithm provide user-explicit fairness with user-individual quality of service guarantees, but the joint schheme achieves a higher sum-rate capacity with flexible parameter settings compared with the multi-carrier proportional fair scheduler.

Radio Resource Allocation for Bidirectional Offloading in Space-Air-Ground Integrated Vehicular Network

Aerial platforms and edge servers have been recognized as two promising building blocks to improve the quality of service(QoS)in space-air-ground integrated vehicular networks(SAGIN).Communication intensive tasks can be offloaded to aerial platforms via broadcasting,while computation intensive tasks can be offloaded to ground edge servers.However,the key issues including how to allocate radio resources and how to determine the task offloading strategy for the two types of tasks,are yet to be solved.In this paper,the joint optimization of radio resource allocation and bidirectional offloading configuration is investigated.To deal with the non-convex nature of the original problem,we decouple it into a two-step optimization problem.In the first step,we optimize the bidirectional offloading configuration in the case of the radio resource allocation known in advance,which is proved to be a convex optimization problem.In the second step,we optimize the radio resource allocation through a brute-force search method.We use queuing theories to analyze the average delay of the two tasks with respect to the broadcasting capacity and task arrival rate.The offloading strategies with closed-form expressions of communication intensive tasks are proposed.We then propose a heuristic algorithm which is shown to perform better than interior point algorithm in simulations.The numerical results also demonstrate that the aerial platforms and edge servers can significantly reduce the average delay of the tasks under different network conditions.

Genetic algorithm for autonomic joint radio resource management in end-to-end reconfigurable systems

This article presents the genetic algorithm （GA） as an autonomic approach for the joint radio resource management （JRRM） amongst heterogeneous radio access technologies （RATs） in the end-to-end reconfigurable systems. The joint session admission control （JOSAC） and the bandwidth allocation are combined as a specific decision made by the operations of the genetic algorithm with certain advisable modifications. The proposed algorithm is triggered on the following two conditions When a session is initiated, it is triggered for the session to camp on the most appropriate RAT and select the most suitable bandwidth for the desired service. When a session terminates, it is also used to adjust the distribution of the ongoing sessions through the handovers. This will increase the adjustment frequency of the JRRM controller for the best system performance. Simulation results indicate that the proposed autonomic JRRM scheme not only effectively reduces the handover times, but also achieves well trade-off between the spectrum utility and the blocking probability.

An Overview of Data-Importance Aware Radio Resource Management for Edge Machine Learning

The 5G network connecting billions of Internet of things(IoT)devices will make it possible to harvest an enormous amount of real-time mobile data.Furthermore,the 5G virtualization architecture will enable cloud computing at the(network)edge.The availability of both rich data and computation power at the edge has motivated Internet companies to deploy artificial intelligence(AI)there,creating the hot area of edge-AI.Edge learning,the theme of this project,concerns training edge-AI models,which endow on IoT devices intelligence for responding to real-time events.However,the transmission of high-dimensional data from many edge devices to servers can result in excessive communication latency,creating a bottleneck for edge learning.Traditional wireless techniques deigned for only radio access are ineffective in tackling the challenge.Attempts to overcome the communication bottleneck has led to the development of a new class of techniques for intelligent radio resource management(RRM),called data-importance aware RRM.Their designs feature the interplay of active machine learning and wireless communication.Specifically,the metrics that measure data importance in active learning(e.g.,classification uncertainty and data diversity)are applied to RRM for efficient acquisition of distributed data in wireless networks to train AI models at servers.This article aims at providing an introduction to the emerging area of importance-aware RRM.To this end,we will introduce the design principles,survey recent advancements in the area,discuss some design examples,and suggest some promising research opportunities.

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.

An efficient resource optimization scheme for D2D communication

With the rapid development of wireless technologies,wireless access networks have entered their Fifth-Generation(5G)system phase.The heterogeneous and complex nature of a 5G system,with its numerous technological scenarios,poses significant challenges to wireless resource management,making radio resource optimization an important aspect of Device-to-Device(D2D)communication in such systems.Cellular D2D communication can improve spectrum efficiency,increase system capacity,and reduce base station communication burdens by sharing authorized cell resources;however,can also cause serious interference.Therefore,research focusing on reducing this interference by optimizing the configuration of shared cellular resources has also grown in importance.This paper proposes a novel algorithm to address the problems of co-channel interference and energy efficiency optimization in a long-term evolution network.The proposed algorithm uses the fuzzy clustering method,which employs minimum outage probability to divide D2D users into several groups in order to improve system throughput and reduce interference between users.An efficient power control algorithm based on game theory is also proposed to optimize user transmission power within each group and thereby improve user energy efficiency.Simulation results show that these proposed algorithms can effectively improve system throughput,reduce co-channel interference,and enhance energy efficiency.

多小区OFDMA网络中用于有效无线资源分配的ICI管理技术(英文)

Two Inter-cell Interference (ICI) management algorithms: Primary Interference Balancing (PIB) algorithm and Interfering Bits Loading Avoidance (IBLA) algorithm are proposed for canceling the ICI effects which the existing efficient radio resource allocation algorithms do not consider. The efficient radio resource allocation algorithm, i.e., Pre-assignment and Reassignment (PR) algorithm, obtains the lowest complexity and achieves good throughput performance in single cell OFDMA system. However, in multi-cell multi-sector OFDMA networks, PR algorithm is not applicable because it does not take ICI into consideration. The proposed PIB algorithm balances the number of loading bits for the desired User Equipment (UE) and the major interfering UE, as well as optimizes the SINR performance; meanwhile, IBLA avoids loading certain number of interfering bits which would make SINR unqualified. Simulations confirm the ICI management effectiveness and feasibility of both the proposals.

Power allocation for MIMO-OFDM systems with multi-user decoupling and scheduling

A power allocation scheme for multi-user multiple-input multiple-output orthogonal frequency division multiplexing （MI- MO-OFDM） systems with channel state information （CSI） on transmitter and receiver is pressed. Multi-user lower allocation can be decoupled into single user lower allocation throughout null space mapping of multi-user channel and lower allocation can be performed throughout spatial-spectral water-filling for per user.To deal with more users in system and fading correlation,scheduling is oerformed to maintain the gain of power allocation.The proposed scheme can substantially improve system＇s spectral efficiency with low complexity.Simulation results validate the accuracy of theoretic analyses.

The Adaptive Random Access Carrier Allocation Scheme in NB-IoT Networks

The rapid progress of the deployment of IoT services pushes the evolution of wireless communication techniques. Because the number of IoT devices is much more than that of the human-held devices for traditional services. It introduces the random access issue in radio networks. In order to support massive IoT devices to transmit data in NB-IoT, the release 14 of 3 GPP provides the preambles in non-anchor carrier for random access. However, if more non-anchor carriers are provided for random access, the resource of uplink shared channel will be compressed. The use of non-anchor carrier for random access preambles shall be carefully allocated for effective resource utilization. In this paper, we propose the adaptive non-anchor allocation algorithm by referring to the collision report flag (CRF) from the user equipment. The proposed CRF algorithm considers the congestion status of uplink to adjust the number of non-anchor carriers in flexible way for better random access experience of huge random access attempts condition. The simulation results show that the proposed algorithm achieves high success access ratio and effective non-anchor carrier utilization when comparing to that of the fixed allocation schemes. The proposed scheme can save 5 - 10 numbers of non-anchor carriers for the number of UEs varies from 15,000 to 37,500 when comparing to the fixed 15 non-anchor carriers scheme under the similar successful access ratio.

Extended Virtual Boundary and Its Application in Dynamic Spectrum Allocation

This paper presents an efficient dynamic spectrum allocation （DSA） scheme in a flexible spectrum licensing environment where multiple networks coexist and interfere with each other. In particular, an extension of virtual boundary concept in DSA is proposed, which is spectrally efficient than the previous virtual boundary concept applied to donor systems only. Here, the same technique is applied to both donor and rental systems so as to further reduce the occurrences where the insertion of guard bands is obligatory and as a result provides better spectral efficiency. The proposed extension improves the spectrum utilization without any compromise on interference and fairness issues.

Multi-radio access based bandwidth allocation strategy for video communication in heterogeneous wireless networks

In order to make full use of the radio resource of heterogeneous wireless networks（HWNs） and promote the quality of service（Qo S） of multi-homing users for video communication, a bandwidth allocation algorithm based on multi-radio access is proposed in this paper. The proposed algorithm adopts an improved distributed common radio resource management（DCRRM） model which can reduce the signaling overhead sufficiently. This scheme can be divided into two phases. In the first phase, candidate network set of each user is obtained according to the received signal strength（RSS）. And the simple additive weighted（SAW） method is employed to determine the active network set. In the second phase, the utility optimization problem is formulated by linear combining of the video communication satisfaction model, cost model and energy efficiency model. And finding the optimal bandwidth allocation scheme with Lagrange multiplier method and Karush-Kuhn-Tucker（KKT） conditions. Simulation results show that the proposed algorithm promotes the network load performances and guarantees that users obtain the best joint utility under current situation.

Dynamic subcarrier and power allocation based on cooperative game theory in symmetric cooperative OFDMA networks

In order to improve the efficiency and fairness of radio resource utilization,a scheme of dynamic cooperative subcarrier and power allocation based on Nash bargaining solution（NBS-DCSPA） is proposed in the uplink of a three-node symmetric cooperative orthogonal frequency division multiple access（OFDMA） system.In the proposed NBS-DCSPA scheme,resource allocation problem is formulated as a two-person subcarrier and power allocation bargaining game（SPABG） to maximize the system utility,under the constraints of each user＇s maximal power and minimal rate,while considering the fairness between the two users.Firstly,the equivalent direct channel gain of the relay link is introduced to decide the transmission mode of each subcarrier.Then,all subcarriers can be dynamically allocated to the two users in terms of their selected transmission mode.After that,the adaptive power allocation scheme combined with dynamic subcarrier allocation is optimized according to NBS.Finally,computer simulation is conducted to show the efficiency and fairness performance of the proposed NBS-DCSPA scheme.

Max-utility subcarrier allocation for heterogeneous services in wireless OFDM system

In future wireless network, one user will require multiple homogeneous or heterogeneous services simultaneously. Then, the scheduling algorithm is not only responsible for assigning a resource block to different users but also sharing the assigned resource block among multiple services for one user. Most of the traditional scheduling algorithms are designed to serve one service per user, and cannot be applied directly to this scenario because of the fairness criterion. This article focuses on adaptive resource allocation for multiple services per user at the downlink of orthogonal frequency division multiplexing （OFDM） based system. This article addresses this integrative resource scheduling problem based on utility function. First, the optimal algorithm for dynamic subcarrier allocation and share is deduced for homogeneous best-effort service system. Then the algorithm is extended to heterogeneous services system by classifying the delay sensitive service according to the head-of-line packet delay. The design goal is to maximize aggregate utility function to exploit multiuser diversity gain to the greatest extent even as guaranteeing quality of service （QoS） for delay sensitive service.

Dynamic traffic split scheme in an integrated LTE and HSDPA networks

In the future, the wireless communication networks can be visualized as the integration of different radio access technologies （RATs）, which are referred to as heterogeneous wireless networks （HWNs）. In this paper, the traffic split scheme in the HWNs integrating the long term evolution （LTE） and the high speed downlink packet access （HSDPA） networks is investigated. Assuming that the networks can support multi-homing access and the user can be served by both networks simultaneously, the traffic split problem is described as an optimization problem with the aim of maximizing the throughput. By solving the problem, the dynamic traffic split scheme is proposed. The split ratios in the scheme should be proportional to the transmission rates in theory, which are hard to be described in the closed forms. Then the adaptive algorithm is proposed to obtain the split ratios. Simulation results show that the scheme with the adaptive algorithm provides better performance than the scheme without it over the additive white Gaussian noise （AWGN） fading channel and Rayleigh fading channel.

Spatial Compatible User Evaluation Algorithm for Space Division Multiplexing Broadcast Channels

Cochannel interference introduced by frequency reuse under space division multiple access can be reduced by controlling the frequency sharing according to the users＇ spatial separability. The system avoids placing highly correlated users in space into the same spatial multiplexing group. This paper describes a user spatial compatibility evaluation criterion based on channel matrix structure analysis. The interferences are evaluated using the distances between subspaces spanned by the users＇ channel matrixes. The analysis considers row space and column space. Simulation results show that the row space distance criterion significantly outperforms other criteria because it fully utilizes the information from the users＇ channel matrixes. As the dimensions of the users＇ channel matrixes increase, the matrix structure analysis-based criteria become even more efficient.