Traffic Characteristics Based Dynamic Radio Resource Management in Heterogeneous Wireless Networks

The traffic with tidal phenomenon in Heterogeneous Wireless Networks(HWNs)has radically increased the complexity of radio resource management and its performance analysis.In this paper,a Simplified Dynamic Hierarchy Resource Management(SDHRM)algorithm exploiting the resources dynamically and intelligently is proposed with the consideration of tidal traffic.In network-level resource allocation,the proposed algorithm first adopts wavelet neural network to forecast the traffic of each sub-area and then allocates the resources to those sub-areas to maximise the network utility.In connection-level network selection,based on the above resource allocation and the pre-defined QoS requirement,three typical network selection policies are provided to assign traffic flow to the most appropriate network.Furthermore,based on multidimensional Markov model,we analyse the performance of SDHRM in HWNs with heavy tailed traffic.Numerical results show that our theoretical values coincide with the simulation results and the SDHRM can improve the resource utilization.

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.

An autonomic joint radio resource management algorithm in end-to-end reconfigurable system

This paper presents the multi-step Q-learning(MQL)algorithm as an autonomic approach to thejoint radio resource management(JRRM)among heterogeneous radio access technologies(RATs)in theB3G environment.Through the'trial-and-error'on-line learning process,the JRRM controller can con-verge to the optimized admission control policy.The JRRM controller learns to give the best allocation foreach session in terms of both the access RAT and the service bandwidth.Simulation results show that theproposed algorithm realizes the autonomy of JRRM and achieves well trade-off between the spectrum utilityand the blocking probability comparing to the load-balancing algorithm and the utility-maximizing algo-rithm.Besides,the proposed algorithm has better online performances and convergence speed than theone-step Q-learning(QL)algorithm.Therefore,the user statisfaction degree could be improved also.

AN EFFICIENT RADIO RESOURCE MANAGEMENT STRATEGY FOR ADAPTIVE OFDM CELLULAR SYSTEMS

This paper presents an efficient Radio Resource Management (RRM) strategy for adaptive Orthogo-nal Frequency Division Multiplexing (OFDM) cellular systems. In the proposed strategy, only those users who have the same distance from their base stations can reuse a same subcarrier. This can guarantee the received Carrier-to-Interference ratio (C/I) of each subcarrier to be acceptable as required by system planning. Then by employing different modulation scheme on each subcarrier according to its received C/I, system spectral effi-ciency can be gracefully increased. Analytical and simulation results show that the spectral efficiency is im-proved by 40% without sacrificing the Bit Error Rate (BER) performance and call blocking probability and sys-tem capacity of the proposed strategy is better than conventional systems.

INVESTIGATION OF UPLINK RADIO RESOURCE MANAGEMENT SCHEMES FOR MULTI-SERVICES IN TDD-CDMA SYSTEMS EMPLOYING SMART ANTENNAS

In this paper, a theoretical analysis of Time Division Duplex-Code Division Multiple Access (TDD-CDMA) uplink capacity constraint is presented when employing the smart antenna techniques. The evaluation formulations of capacity and load for multi-services are proposed. In order to maximize the throughput, the objective of optimization is proposed, and an advanced uplink resource management algo-rithm is developed. The proposed algorithm based on the least interference admission control scheme focuses on the maximum throughput for the circuit switched multi-services. The simulation results show that the pro-posed strategy has a significant improvement in throughput when the optimum admission control threshold is set.

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.

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.

Investigation of Adaptive Multi-Rate Link Adaptation of 3G System

In term of the features of 3G system, a novel AMR link adaptation strategy for 3G system is proposed. The impacts of AMR codec modes and power control on traffic quality of service are taken into account in the strategy at the same time. By synthetically comparing the signal-to-interference ratio value with the switching threshold and comparing the transmission power with its threshold, radio resource management can always keep each link on its proper codec mode with the corresponding optimal power level to achieve both robust speech quality and link capacity enhancement. Based on the WCDMA FDD uplink link-level simulation platform, AMR link adaptation platform is constructed. Simulation results show that the algorithm can track the fast change of channel conditions and select the most robust codec mode, thus the synthetic speech quality of AMR is better than that of signal mode during a wide range of channel conditions. The result will provide a reference strategy for AMR link adaptation of 3G system.

A Frameless Network Architecture for the Way Forward of C-RAN

The key technologies involved in the evolution of the Cloud-based Radio Access Network(C-RAN) are discussed in this paper. Taking the Frameless Network Architecture(FNA) as a starting point, a cell-lessbased network topology for a multi-tier Heterogeneous Network(Het Net) and ultra-dense network is proposed. The FNA network topology modeling is researched with centralized processing and distributed antenna deployments. The Antenna Element(AE) is released as a new dimensional radio resource that is included in the centralized Radio Resource Management(RRM) processes. This contributes to the on-demand user-centric serving-set associations with cell-edge effect elimination. The Control Plane(CP) and User Plane(UP) separation and adaptation are introduced for energy efficiency improvements. The centralized RRM and different optimization goals are discussed for fully exploring the merits from the centralized computing of C-RAN. Considering the complexity, near-optimal approaches for specific users' Quality-of-Service(Qo S) requirements are addressed. Finally, based on the research highlighted above, the way forward of C-RAN evolution is discussed.

Cooperative wireless networks for better green services

In order to guarantee the overall return on investment (ROI), improve user experience and quality of service (QoS), save energy, reduce electra magnetic interference (EMI) and radiation pollution, and enable the sustainable deployment of new profitable applications and services in heterogeneous wireless networks coexistence reality, this paper proposes a cross-network cooperation mechanism to effectively share network resources and infrastructures, and then adaptively control and match multi-network energy distribution characteristics according to actual user/service requirements in different geographic areas. Some idle or lightly-loaded base stations (BS or BSs) will be temporally turned off for saving energy and reducing EMI. Initial simulation results show that the proposed approach can significantly improve the overall energy efficiency and QoS performance across multiple cooperative wireless networks.

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.

SPATIAL COMPATIBLE USER GROUPING ALGORITHM FOR MULTIUSER MIMO SYSTEMS

A spatial compatible user grouping algorithm is proposed to reduce CoChannel Interference (CCI) in Space Division Multiple Access (SDMA) multiuser Multiple Input Multiple Output (MIMO) systems. We evaluate the interferences among users by use of distances between row spaces spanned by users’ channel matrixes, then control frequency sharing according to the compatible user grouping algorithm. Results show that the row space distance algorithm outperforms others because it can fully utilize the information from users’ channel matrixes, especially the matrix structure information. The results also prove that the algorithm based on channel matrix structure analysis is a better candidate for spatial compatibility approximation.

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 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.

A flexible scheduling algorithm for the 5th-generation networks

At present,the 5th-Generation(5G)wireless mobile communication standard has been released.5G networks efficiently support enhanced mobile broadband traffic,ultra-reliable low-latency communication traffic,and massive machine-type communication.However,a major challenge for 5G networks is to achieve effective Radio Resource Management(RRM)strategies and scheduling algorithms to meet quality of service requirements.The Proportional Fair(PF)algorithm is widely used in the existing 5G scheduling technology.In the PF algorithm,RRM assigns a priority to each user which is served by gNodeB.The existing metrics of priority mainly focus on the flow rate.The purpose of this study is to explore how to improve the throughput of 5G networks and propose new scheduling schemes.In this study,the package delay of the data flow is included in the metrics of priority.The Vienna 5G System-Level(SL)simulator is a MATLAB-based SL simulation platform which is used to facilitate the research and development of 5G and beyond mobile communications.This paper presents a new scheduling algorithm based on the analysis of different scheduling schemes for radio resources using the Vienna 5G SL simulator.