Dynamic Spectrum Allocation Scheme Research Articles

IMPROVED QoE IN 5G BASE STATION USING PSO BASED DSA

In the 5G era, base stations can offer multiple services in various scenarios, enhancing spectrum efficiency by utilizing idle frequency bands for low-demand services while ensuring high-priority services are prioritized. This creates a distributed architecture for spectrum allocation. The proposed dynamic spectrum allocation scheme for base stations, optimizes spectrum rearrangement based on service priority, energy consumption, and renting cost. We employ the Particle Swarm Optimization (PSO) algorithm, inspired by bird flocking or fish schooling behavior, to solve the problem. Moreover, provide detailed information on our approach, demonstrating the effectiveness of PSO in optimizing spectrum allocation. By using PSO, we find the optimal solution considering service priority, energy consumption, and renting cost, supported by mathematical proofs of PSO algorithm performance. MATLAB is used as the simulation tool to carry out these techniques. Simulation experiments validate the approach, showing the stability and efficacy of PSO-based algorithm, which aligns with the theoretical analysis. . Key Words: Spectrum efficiency; 5G; dynamic spectrum allocation; service priority; PSO.

A Deep-Q Learning Scheme for Secure Spectrum Allocation and Resource Management in 6G Environment

In this paper, we propose a dynamic spectrum allocation (DSA) scheme DeepBlocks at the backdrop of sixth-generation (6G) communication networks that address the challenges of fixed spectrum allocations (FSA). The scheme exploits the advantages of deep-Q-network (DQN) and minimizes the search state explosion through a reward-penalty framework. A dynamic allocation of unallocated resource blocks (RBs) to mobile units (MUs) is carried out and once the allocation of RBs is complete, we integrate blockchain (BC) to record the transactional ledgers. The resource usage of MUs is recorded through smart contracts (SCs). We model the proposed scheme as a convex optimization problem, and subproblems are decomposed into a Pareto-optimal solution via Techebyecheff decomposition. In the simulation, we compare our scheme against FSA, and fifth-generation (5G) based DSA schemes like reinforcement learning (RL), deep neural networks (DNN)-based, and duelling DQN based schemes. The comparative analysis of 6G-DQN is modeled in terms of reward formulation, scalability of 6G-DQN-assisted DSA, and profit scenarios of BC-based allocation through intelligent channel control. The scheme proposes significant findings, with the best fit learning rate of 0.0001, and takes 500 episodes to converge to 60 total resource blocks. The servicing latency of the scheme is 272.4 ms, compared to 2010 ms in the duelling DQN approach. In spectrum allocation, an improvement of 26.32% is observed against non-DQN approaches, and 13.57% in the fairness parameter for spectrum allocation due to BC inclusion. The findings present the scheme efficacy for DSA over the aforementioned conventional approaches.

Pricing Policy for a Dynamic Spectrum Allocation Scheme with Batch Requests and Impatient Packets in Cognitive Radio Networks

Pricing Policy for a Dynamic Spectrum Allocation Scheme with Batch Requests and Impatient Packets in Cognitive Radio Networks

Finder-MCTS: A Cognitive Spectrum Allocation Based on Traveling State Priority and Scenario Simulation in IoV

With the increasing number of intelligent connected vehicles, the problem of scarcity of communication resources has become increasingly obvious. It is a practical issue with important significance to explore a real-time and reliable dynamic spectrum allocation scheme for the vehicle users, while improving the utilization of the available spectrum. However, previous studies have problems such as local optimum, complex parameter setting, learning speed, and poor convergence. Thus, in this paper, we propose a cognitive spectrum allocation method based on traveling state priority and scenario simulation in IoV, named Finder-MCTS. The proposed method integrates offline learning with online search. This method mainly consists of two stages. Initially, Finder-MCTS gives the allocation priority of different vehicle users based on the vehicle’s local driving status and global communication status. Furthermore, Finder-MCTS can search for the approximate optimal allocation solutions quickly online according to the priority and the scenario simulation, while with the offline deep neural network-based environmental state predictor. In the experiment, we use SUMO to simulate the real traffic flows. Numerical results show that our proposed Finder-MCTS has 36.47%, 18.24%, and 9.00% improvement on average than other popular methods in convergence time, link capacity, and channel utilization, respectively. In addition, we verified the effectiveness and advantages of Finder-MCTS compared with two MCTS algorithms’ variations.

Improving Spectrum Management for Satellite Communication Systems With Hunger Marketing

Efficient spectrum management is an important issue in satellite communications due to the pervasive growth in wireless communications and the ever-increasing demand by bandwidth-hungry mobile applications. While various kinds of static and dynamic spectrum allocation schemes have been studied by satellite researchers, the issue of unpredictable user behavior, hence demand for bandwidth, remains one of the key challenges faced by the research community. In this letter, we introduce the hunger marketing strategy in satellite spectrum management in order to address the unpredictable user demands. When adopting hunger marketing, the system always maintain a certain level of spectrum supply shortage, thus stimulating the desire of users to plan and commit their bandwidth requirements in advance, hence making their behavior more predictable and benefiting satellite systems. Besides, in circumstances of multibeam satellite systems, when allocating bands to new satellite users, the issue of increase in inter-cell interference is also considered in this letter. Thus, a two-stage dynamic game model based on hunger marketing is proposed which aims to achieve an optimal balance between spectrum utilization and inter-cell interference. Numerical results are presented to show the effectiveness of the proposed method.

On Dynamic Spectrum Allocation in Geo-Location Spectrum Sharing Systems

Spectrum sharing is a key technology to relieve the ever-increasing spectrum demand and realize the full potential of radio spectrum. In this paper, we study spectrum sharing between higher priority users and lower priority users under geo-location based spectrum sharing systems. We consider a dynamic spectrum allocation scheme that allocates spectrum to a higher priority user based on its spectrum need that can be determined by its traffic load. The lower priority users utilize the unallocated spectrum. In addition to studying the performance of higher priority users with this dynamic spectrum allocation scheme, we also investigate the impact of this scheme on spectrum availability and stability of lower priority users. We develop a mathematical model to analyze the performance. The simulation results indicate that spectrum sharing is efficient, and the spectrum is abundant and relatively stable to lower priority users, even when the system is moderately loaded with higher priority users.

UFMC-Based Interference Management for Heterogeneous Small-Cell Networks

In this paper, we apply the advanced waveform universal filtered multi-carrier (UFMC) to a heterogeneous small-cell network, where both the inner-cell interference and the inter-cell interference are considered. By employing UFMC, a dynamic spectrum allocation scheme and a precoding scheme are proposed to mitigate the interference. The proposed UFMC based interference management schemes are analyzed in detail, and the achievable data rate of the proposed scheme is derived. Simulation results show that the proposed UFMC based schemes can efficiently mitigate the interference, and reduce the effect of frequency offsets.

A dynamic resource allocation scheme based on cognition in LTE system

In this paper, we propose a dynamic spectrum allocation scheme based on cognition in the LTE system. The new scheme is to address the poor communication service problem caused by co-channel interference between the cell-edge users in the LTE system. The scheme leverages the cognitive characteristic in the LTE system to enable the base station to dynamically obtain the idle resource status information of the adjacent cells and integrates the idle resource information of the target cell, and then employs the ant colony optimisation technique to allocate the resource blocks to users. Experimental results show that the proposed scheme allows the cell-edge users to dynamically utilise the idle resource blocks of adjacent cells, which enhances resource blocks utilisation and system throughput while ensuring fairness among users, thus may improve the quality of user service at the cell-edge.

A dynamic resource allocation scheme based on cognition in LTE system

In this paper, we propose a dynamic spectrum allocation scheme based on cognition in the LTE system. The new scheme is to address the poor communication service problem caused by co-channel interference between the cell-edge users in the LTE system. The scheme leverages the cognitive characteristic in the LTE system to enable the base station to dynamically obtain the idle resource status information of the adjacent cells and integrates the idle resource information of the target cell, and then employs the ant colony optimisation technique to allocate the resource blocks to users. Experimental results show that the proposed scheme allows the cell-edge users to dynamically utilise the idle resource blocks of adjacent cells, which enhances resource blocks utilisation and system throughput while ensuring fairness among users, thus may improve the quality of user service at the cell-edge.

Prediction-Based Spectrum Management in Cognitive Radio Networks

Cognitive radio networks (CRNs) have been widely studied to improve spectrum utilization through a dynamic spectrum allocation scheme. However, many challenges remain and one big issue is how to provide an efficient spectrum management in a mobile environment. In this paper, we propose a new prediction-based spectrum management strategy to tackle this challenge. Both spectrum prediction and users’ mobility prediction are fully considered in the proposed strategy. Combining the prediction information and cooperative sensing, a CR base station can obtain the sensing information for future location of each secondary user, so as to prearrange high-quality channels for secondary users ahead of time. In addition, we propose a new channel selection scheme when multiple channels are available simultaneously. Besides traditional decision factors, the new channel selection algorithm takes the channel's future availability obtained from spectrum prediction into account. By properly integrating the spectrum prediction, user mobility prediction, and channel selection, the new spectrum management strategy is capable of allocating the spectrum resource more efficiently. Extensive simulations are conducted and results verify that the proposed spectrum management strategy significantly improves the system performance in terms of reducing handoff times and improving user satisfactory, connection reliability, and channel utilization.

A Spectrum Allocation Scheme Between Smart Grid Communication and Neighbor Communication Networks

One key requirement of a smart grid communication network (SGCN) is to provide wireless-enabled devices with a frequency spectrum for data transmission. This spectrum can be partially supplied from existing neighboring communication networks (NCNs) via spectrum ordering. The scope of this paper is to propose a coexistence scheme, in which NCNs declare their own price per frequency channel and allow an SGCN to make decisions on the number of channels to be ordered. Due to dynamic NCN conditions and, accordingly, time-varying channel pricing, the spectrum ordering by an SGCN over a time horizon is formulated as a stochastic optimization problem. Having decoupled the problem over time, a dynamic spectrum allocation scheme is proposed. As a result of this scheme, the required data transmission rate of an SGCN is provided statistically. Numerical results demonstrate the effectiveness of the proposed scheme from the viewpoint of the grid operational cost.

Dynamic Spectrum Allocation Scheme for Heterogeneous Network

Recently, femtocells (HeNBs) are deployed in heterogeneous network (HetNets) attributable to the addition of coverage, capacity and impeccable spectrum efficiency in private buildings/office complexes surroundings. This unplanned placement of HeNBs creates co-channel interference (CCI) in orthogonal frequency division multiple access (OFDMA). As a result service, disruption occurred at the macrocell user and femtocell user. Therefore, with always expanding interest for frequency spectrum, there is have to make available more resource allocation in order to permit more quantities of unlicensed clients to transmit their signals in the authorized groups. Cognitive-based approaches may increase the spectrum efficiency by sharing resources opportunistically from unlicensed/licensed network. However, spectrum management processes quite difficult, and a lot of chance to occur interference at the cell-edge users. Therefore, a dynamic spectrum allocation scheme is proposed for OFDMA based HetNets. The proposed scheme efficiently reduces the interferences through subchannel detection. To accomplish the CCI mitigation, the proposed scheme is functioning using the energy exposure with group creation algorithm for subchannel detection. Finally, the detected subchannel is allocated through applying power allocation algorithm. The simulation results represent that proposed scheme is able to maximize the spectrum detection and enhanced the spectral efficiency. The improved spectral efficiency recuperates the CCI situation at underlay HetNets.

Game Theory based Dynamic Spectrum Allocation for Secondary Users in the Cell Edge of Cognitive Radio Networks

Cognitive Radio (CR) has very promising potential to improve spectrum utilization by allowing unlicensed Secondary Users (SUs) to access the spectrum dynamically without disturbing licensed Primary Users (PUs). Mitigating interference is a fundamental problem in CR scenarios. This is particularly problematic for deploying CR in cellular networks, when users are located at the cell edge, as the inter-cell interference mitigation and frequency reuse are critical requirements for both PUs and SUs. Further cellular networks require higher cell edge performance, then SUs will meet more challenges than PUs. To solve the performance decrease for SUs at the cell edge, a novel Dynamic Spectrum Allocation (DSA) scheme based on Game Theory is proposed in this paper. Full frequency reuse can be realized as well as inter-cell interference mitigated according to SUs’ sensing, measurement and interaction in this scheme. A joint power/channel allocation algorithm is proposed to improve both cell-edge user experience and network performance through distributed pricing calculation and exchange based on game theory. Analytical proof is presented and simulation results show that the proposed scheme achieves high efficiency of spectrum usage and improvement of cell edge SUs’ performance.

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.

Coalitional Double Auction for Spatial Spectrum Allocation in Cognitive Radio Networks

Recently, many dynamic spectrum allocation schemes based on economics are proposed to improve spectrum utilization in cognitive radio networks (CRNs). However, existing mechanisms do not take into account the economic efficiency and the spatial reusability simultaneously, which leaves room to further enhance the spectrum efficiency. In this paper, we introduce the coalition double auction for efficient spectrum allocation in CRNs, where secondary users (SUs) are partitioned into several coalitions and the spectrum reusability can be executed within each coalition. The partition formation process is not only related to the interference condition between SUs, but also the expected economic goals. Therefore, we propose a fully-economic spatial spectrum allocation mechanism by incorporating the coalition formation approach with auction theory. With the proposed scheme, the primary operator acts as an auctioneer, who performs multiple virtual auctions to form a stable partition of SUs and conducts a final auction to decide the winning SUs. Moreover, we propose a possible operation rules for the primary operator to iteratively change the partition, and prove that the virtual auctions could converge in finite time. Comprehensive theoretical analysis and simulation results are presented to show that our scheme can satisfy the crucial economic robustness properties of double auction, and outperform existing mechanisms.

Dynamic routing, modulation level and spectrum allocation (RMLSA) in FWDM with modulation format conversion

This paper proposes a dynamic routing, modulation level and spectrum allocation (RMLSA) scheme in the flexible optical wavelength-division multiplexing (FWDM) networks with modulation format conversion ability. The scheme considers the modulation format conversion at the intermediate nodes and addresses the fragmentation problem by avoiding appearance of them. The influence of routing to the emergence of the fragmentation is quantified, which is referenced to decide which one route of k-paths to use. Simulation results demonstrate efficient reductions in blocking rates and improvements in failure recovery rates for the scheme in the network.

弹性光网络中基于效用的公平性感知动态频谱分配方案

弹性光网络中基于效用的公平性感知动态频谱分配方案

Coverage probability driven dynamic spectrum allocation in heterogeneous wireless networks

In this paper, we design a dynamic spectrum allocation (DSA) scheme for heterogeneous cellular wireless networks with special interest on guaranteeing the cell coverage probability. To this end, considering users spatial distribution, we propose a new interference control (IC) model, which guarantees SINR (signal to interference plus noise ratio) requirements of different services and ensures the coverage performance of base stations (BSs). Under such an IC model, we formulate the DSA scheme as a combinatorial optimization problem. Since the problem is computationally intractable, we design an algorithm for its solution based on graph coloring. Simulation results indicate that the proposed DSA scheme can increase the total spectrum utility while effectively controlling the interference among BSs and meeting SINR requirements of users.

Dynamic spectrum allocation for cell range extension in tiered Macro-Pico heterogeneous networks

Heterogeneous networks are employed in the next generation communication systems to enhance the area spectral efficiency (ASE), where cell range extension (CRE) is a promising technique to improve the cell edge performance and utilize the low power node (LPN) resources more effectively. In this paper we propose a dynamic spectrum allocation scheme for Macro-Pico scenario to mitigate both the co-tier and cross-tier interferences. The available system spectrum is divided into different parts by four steps, i.e. user set partition, service request collection, cross-tier occupation and CRE occupation decision, while the service request of each user is taken into consideration. During the process implementation, the reference signal receiving power (RSRP) threshold is derived by mathematical means to judge cell edge macro users when a predefined ratio is given. Simulation results show that the proposed scheme reaches almost the same cell edge performance with the best existing option, meanwhile provides higher overall system throughput and better spectral efficiency. Therefore, much better balance is achieved.

Advanced Technologies in Wireless Internet and Communications Networks (Editorial for WICON 2011 Special Issue)

Over the last two decades, wireless internet and communications networks have experienced an explosive growth in both the diversity of the techniques and its range of applications. Besides the traditional mobile communications services, current mobile communications networks can also provide internet access services. In order to provide higher data transmission rate, the 4th generation mobile communications systems, i.e., IMT-Advanced, have been developed and many advanced technologies, such as MIMO and OFDM, have been applied. The constantly developing wireless communications technologies also have enabled the extensive deployment of distributed wireless networks, such as the Ad Hoc networks. This kind of networks has applications in many important areas, such as military, healthcare, environment monitoring, and manufacturing. Due to the absence of central controllers, the distributed networks face many challenges. In recently years, radio spectrum has becoming exhausted because of the growing demands for wireless broadband communications. However, the traditional static spectrum allocation policy has prevented the spectrum utilization efficiency from further increasing. In order to overcome the spectrum shortage problem, cognitive wireless network, in which cognitive radio technique is applied, have drawn a great of research attentions. In the future wireless internet and communications networks, many advanced technologies, such as MIMO, OFDM, cognitive radio, distributed resource allocation/management, distributed admission control, etc., will be applied to satisfy the increasing demands for broadband wireless services. Our objectives for this special issue of ACM/Springer Mobile Networks & Applications are to collate and disseminate the most relevant achievements of research work on wireless network architectures, wireless access technologies, distributed admission control, advanced resource allocation/management, QoS guarantees, etc. In response to this call for papers, we have received a total of xx high-quality submissions, and 6 papers have been selected for publication after a rigorous review process. The first paper “Optimal Resource Allocation for Spectrum Sensing Based Cognitive Radio Networks with Statistical QoS Guarantees” by Y. Wang, P, Ren, Q. Du, and C. Zhang proposes an optimal resource allocation scheme for statistical QoS provisioning in spectrum sensing based cognitive radio networks subject to the average transmit and interference power constraints. The second paper “The Master–slave Stochastic Knapsack Modeling for Fully Dynamic Allocation” by S. Zhang, F. Yang, M. Zhao, and W. Zhou models the fully dynamic spectrum allocation scheme as a master–slave stochastic knapsack process, analyzes the equilibrium state transition, and derives the probability of blocking and forced termination for the secondary user. The third paper “A Method for Classifying Packets into Networks Flows Based on GHSOM” by H. Shi, T. Hamagami, H. Xu, P. Yu, and Y. Wu develops an intelligent network flow identifying method based on the neural network algorithm and suggests a new normalization for changing the raw network traffic to learn input vectors. The forth paper “Performance Improvement of the Precise Paging in CoLAC for 2G/3G Convergence Core Networks with Path Diversity” by Y. Su and X. Feng evaluates the system performance metrics in terms of handover success rate and P. Ren (*) Xi’an Jiaotong University, Xi’an, China e-mail: pyren@mail.xjtu.edu.cn