Spectrum Allocation Mechanism Research Articles

An improved spectrum sharing strategy evaluation over wireless network framework to perform error free communications

The possible application of wireless sensor networks is hampered and the widespread use of this novel method is slowed, according to recent surveys conducted within the field of automation in industry, which identified that accuracy pertains indicate currently among the primary obstacles to the dissemination of wireless networking for recognizing and regulating applications. In order to overcome these constraints, it is necessary to raise public understanding of the reasons for dependability issues and the potential approaches to resolving them. Low-power communications of sensor nodes are, in reality, quite susceptible to adverse channel conditions and can readily be affected by transmissions of other co-located devices, making them seem unreliable. In this dissertation, I explore several strategies that may be used to either eliminate interference altogether or reduce its negative consequences. In this paper, we study the creation and modeling of a brand-new spectrum allocation mechanism for wireless sensor networks. Cognitive radio technology can detect spectrum holes in the environment, learn from its surroundings using artificial intelligence, adjust the system’s operating parameters in real-time, and use the secondary spectrum to increase efficiency. In this study, we present a reinforcement learning-based strategy for choosing the power of transmission and frequency that can help individual sensors learn from their prior decisions and those of their peers. Our suggested approach is multiple agents decentralized and adaptable to both the data needs from source to sink and the amount of energy that sensing devices in the network have left over. In comparison to different resource allocation algorithms, the results reveal a dramatic increase in the lifespan of the network.

Blocking Rate Analysis in Heterogeneous Multicell Cognitive-Radio 5G Networks

Cognitive radio (CR) technology is being recognized as one of the main enabling technologies for supporting massive high-speed connectivity in multicell fifth-generation (5G) networks by allowing dynamic spectrum access policies according to predetermined etiquette. Under this paradigm, the available spectrum is opportunistically allocated to the different cells. A key metric that is heavily employed in designing efficient CR-based multicell spectrum-allocation mechanisms is the blocking rate. An efficient spectrum-allocation mechanism aims to adaptively allocate channels to the different cells such that the overall blocking rate is minimized. In this article, we use the theory of continuous-time Markov chains to derive a closed-form expression for the blocking rate in multicell CR-based 5G networks. In our derivations, we build two detailed mathematical models describing the frequency-spectrum usage of both primary and secondary users. We combine the two models in a hierarchical fashion. As opposed to related models in the literature which suffer high complexity, the proposed hierarchical structure yields simplicity and tractability. Furthermore, while existing research works overlook spectrum heterogeneity, the proposed model addresses this important factor. Simulation results demonstrate high accuracy in evaluating the blocking rate across the different cells in the network.

On three shades of partial protection in elastic optical networks

Gone have been the days when the allocation of spectrum resources for a demand is over-provisioned due to worst-case based designs and the optical transmission technologies are based on the fixed spectral grid, modulation format and/or line-rate schemes. Elastic optical networks technologies featuring adaptive spectrum allocation mechanisms have been becoming the architecture and technology of choice for future core networks to meet explosive traffic growths in a cost and energy-efficient manner. Partial protection strategies based on the observation that in failure events, a service can tolerate a certain amount of degradation and therefore by reducing the protection traffic in the network, better spectrum utilization could be attained. Such concept has been widely studied in the traditional wavelength division multiplexing (WDM) context and yet has been somehow faded due to the fact that fixed transmission technologies provide limited room for spectral improvements. This paper aims to renew the interest in partial protection and re-adapt it to the context of elastic optical networks. The evolutionary perspective we lay out in this paper identifies a new route for achieving greater spectral efficiency in a pragmatic way by simply differentiating the protection services for each demand rather than the uniform treatment for all demands. As such, we present a new research problem entitled, routing, modulation level, spectrum and protection service assignment which is essentially an extension of the well-established one, that is, routing, modulation level, and spectrum assignment as the (partial) protection service for each demand is taken into account and optimized. Three variants of that problem reflecting shades of applying partial protection are covered in details. Specifically, the first one considers the intuitive case as the amount of protection traffic for each demand is provided as the input to the network planning process while the second one is dedicated to the special case of enforcing the same level of partial protection for all demands. More interesting case emerges in the third variant where given the service level agreement for the total protected network traffic, we provide the optimal solution that determines the protection service for each individual demand so as to minimize the spectral occupancy. Extensive numerical simulations have been conducted in the realistic COST239 network topology and it has been revealed that a remarkable spectral saving could be achieved thanks to introducing partial protection services. Moreover, our results have demonstrated that the demand-wise approach far outperforms the one-size-fits-all one and the difference could be up to 25% in our studied cases.

Leveraging AI‐enabled 6G‐driven IoT for sustainable smart cities

SummaryMany scholastic researches have begun around the globe about the competitive technological interventions like 5G communication networks and its challenges. The incipient technology of 6G networks has emerged to facilitate ultrareliable and low‐latency applications for sustainable smart cities which are infeasible with the existing 4G/5G standards. Therefore, the advanced technologies like machine learning (ML), block chain, and Internet of Things (IoT) utilizing 6G network are leveraged to develop cost‐efficient mechanisms to address the issues of excess communication overhead in the present state of the art. Initially, the authors discussed the key vision of 6G communication technologies, its core technologies (such as visible light communication [VLC] and THz), and the existing issues with the existing network generations (such as 5G and 4G). A detailed analysis of benefits, challenges, and applications of blockchain‐enabled IoT devices with application verticals like Smart city, smart factory plus, automation, and XR that form the key highlights for 6G wireless communication network is also presented. In addition, the key applications and latest research of artificial intelligence (AI) in 6G are discussed facilitating the dynamic spectrum allocation mechanism and mobile edge computing. Lastly, an in‐depth study of the existing open issues and challenges in green 6G communication network technology, as well as review of solutions and potential research recommendations are also presented.

AN ENHANCED RESOURCE ALLOCATION SCHEME FOR LONG TERM EVOLUTION ADVANCED NETWORK

The emerging Long-Term Evolution Advanced (LTE-A) is an extended version of Long-Term Evolution (LTE) fourth-generation (4G) wireless broadband technologies that supports high speed transmission of multimedia applications, like video streaming, multimedia online game, Voice over IP (VoIP), browsing over the web etc. The Third Generation Partnership Project (3GPP) does not define a standard packet scheduling strategy in LTE-A. Therefore, it is expected for researchers and network service providers to design efficient schemes. This paper proposed an Enhanced Resource Allocation Scheme (E-RAS) that improves the packet scheduling strategy of LTE-A by addressing issues related to delay and fairness of users with both high and low channel conditions, for both Real Time (RT) and Non-Real Time (NRT) flows. The aim was achieved by using a fair spectrum allocation mechanism that consider the priority of RT flows of cell-centre users, without neglecting the throughput requirements of edge-centre users. Moreover, the proposed algorithm introduces an efficient traffic load balancing mechanism to efficiently regulate traffic load in LTE-A network. To evaluate the proposed scheme, simulation was conducted using the MATLAB programming with LTE-A system level simulator. The result obtained shows that the proposed scheme achieves better delay for RT and NRT traffics by 7% and 11% respectively as against the Resource Allocation Scheme to Optimize the Throughput (RASOT) scheme.

Research on wireless spectrum allocation and utility evaluation of cross-domain multi-slot radio

The existing spectrum use authorization adopts the large-period and large-area allocation mode, and users exclusively use the right to use the spectrum, resulting in the idle spectrum of multiple time slots and regions and a low utilization rate. This paper proposes a cross-domain, multi-slot Wireless Spectrum Allocation Mechanism (CMWSA) from a fine-grained spatiotemporal perspective. The bilateral spectrum auction model includes the buyer’s location, the start and end time, and the interference radius in the auction information, and the multi-spectrum buyer virtual grouping algorithm is designed. By classifying the spectrum and constructing the interference matrix, a cross-domain, multi-slot, spatiotemporal reuse Wireless Spectrum auction mechanism is proposed to improve the utilization of the idle spectrum and increase users’ satisfaction. Simulation results show that CMWSA can improve the spectrum utilization rate of secondary users, meet the diverse needs of secondary users, and improve the spectrum reuse rate.

Multi-Winner Spectrum Allocation in Cognitive Radio Networks: A Single-Sided Auction Theoretic Modelling Approach with Sequential Bidding

Cognitive radio (CR) has evolved as a novel technology for overcoming the spectrum-scarcity problem in wireless communication networks. With its opportunistic behaviour for improving the spectrum-usage efficiency, CR enables the desired secondary users (SUs) to dynamically utilize the idle spectrum owned by primary users. On sensing the spectrum to identify the idle frequency bands, proper spectrum-allocation mechanisms need to be designed to provide an effectual use of the radio resource. In this paper, we propose a single-sided sealed-bid sequential-bidding-based auction framework that extends the channel-reuse property in a spectrum-allocation mechanism to efficiently redistribute the unused channels. Existing auction designs primarily aim at maximizing the auctioneer’s revenue, due to which certain CR constraints remain excluded in their models. We address two such constraints, viz. the dynamics in spectrum opportunities and varying availability time of vacant channels, and formulate an allocation problem that maximizes the utilization of the radio spectrum. The auctioneer strategises winner determination based on bids collected from SUs and sequentially leases the unused channels, while restricting the channel assignment to a single-channel-multi-user allocation. To model the spectrum-sharing mechanism, we initially developed a group-formation algorithm that enables the members of a group to access a common channel. Furthermore, the spectrum-allocation and pricing algorithms are operated under constrained circumstances, which guarantees truthfulness in the model. An analysis of the simulation results and comparison with existing auction models revealed the effectiveness of the proposed approach in assigning the unexploited spectrum.

Collaborative Flow Control in the DARPA Spectrum Collaboration Challenge

Wireless network technologies are becoming more and more popular. Because of this, important parts of the wireless spectrum become overloaded. Static spectrum allocation, which has been the norm for decades, is not suitable anymore. To maintain the high demand for spectrum and the continuous development of new wireless technologies, there is a need for an intelligent, dynamic spectrum allocation mechanism, where different network technologies collaboratively optimize the spectrum usage. New wireless network paradigms, such as Neutral Host Networks (NHNs) and private 5G, require a smart, spectrum-footprint-aware flow control algorithm to overcome the spectrum scarcity in collaborative way. This article presents a strategy, vision and flow control mechanism to implement collaboration in a Quality of Service (QoS)-driven way. The solution in this article is based on policies which may activate depending on its current and neighbor’s network states. Through a flow ordering and selection strategy, these policies optimize the spectrum footprint, based on the performance and QoS-requirements of the own and surrounding networks. The proposed algorithm is tested extensively and validated on a large scale during the DARPA Spectrum Collaboration Challenge (SC2) competition. The results of the SC2 final event and intermediate scrimmages showed that the proposed approach increased the score, indicating increased inter-network collaboration was achieved.

QoS-aware protection in elastic optical networks with distance-adaptive and reconfigurable modulation formats

• Proposal on QoS-aware protection combined with reconfigurable modulation formats. • A novel network design formulation for QoS-aware protection. • Protection based on traffic differentiation brings significant spectral saving. Elastic optical networks have recently emerged as one of the most promising technologies for creating next-generation optical core networks thanks to the adaptive spectrum allocation mechanism. In order to achieve higher spectrum efficiency and exploit elastic optical networking technology, in this paper, we introduce a novel perspective on re-designing dedicated path protection for elastic optical networks. First, inspired by the observation that, in distance-diverse network topologies, the transmission margin between the working and protection route could be wide enough and therefore, the most feasibly spectrum-efficient modulation format could be assigned according to the specific condition of each route rather than applying a single modulation format that is able to cope with the worse condition of the route as currently adopted in traditional designs. Such more granular in transmission adaption is powered by the fast reconfiguration of state-of-the-art elastic transponders and this paves new opportunities in leveraging the spectrum efficiency. Second, the characteristics of traffic traveling in fiber links could be furthermore exploited to tailor the protection services to the actual requirement instead of enforcing the same level of protection for the entire traffic. Specifically, premium traffic today accounts for only 25 % and the remained traffic is best-effort and in taking advantage of this insight, dedicated path protection could be re-designed to ensure just-enough bandwidth provision for premium traffic in case of failures while possibly accepting best-effort traffic discard. In exploiting both the reconfiguration capability and traffic differentiation, a new quality-of-service aware protection framework for the design of elastic optical networks with the capability of distance-adaptive and reconfigurable modulation format assignment is provided. We introduce the node architecture supporting our proposal and provide an optimal design formulation in the form of integer linear programming model to maximize the spectral utilization efficiency. We have also applied extensively experimental simulations to evaluate the performance of our proposed solution in comparison with that of appropriate conventional approaches on a realistic network topology, i.e. COST239. The obtained numerical results prove that our developed solution significantly outperforms the conventional ones, in terms of spectrum efficiency, and it has been revealed that permitting reconfiguration of transmission parameters in switching from working routes to protection ones could result up to 20 % spectral saving in most favorable conditions. Furthermore, incorporating the protection service differentiation could substantially boost spectrum efficiency. For the present ratio of premium traffic– roughly 25 % , our proposal reveals that a spectral saving of up to more than 80 % could be attained and on the whole, the developed solution tends to be more profitable with the medium and high-load traffic conditions.

A Truthful Online Incentive Mechanism for Nondeterministic Spectrum Allocation

Dynamic spectrum access (DSA) is a promising platform to solve the problem of spectrum shortage for which the most challenging issue is spectrum allocation under uncertain availability information, which is referred as a nondeterministic spectrum allocation problem. The nature of such a problem is due to inaccurate spectrum sensing results, which are induced by that power or energy based sensing can be greatly impacted by thermal and environmental noise. For spectrum allocation, auction-based mechanisms have been extensively studied because of channel allocation efficiency, and its potential to achieve bidding truthfulness for secondary uses (SUs). However, most existing spectrum auction mechanisms focus on realizing the truthfulness under certain spectrum availability information. In this paper, we propose FORTUNE, the first truthful online auction mechanism for nondeterministic spectrum allocation by considering uncertain spectrum availability and dynamic spectrum requests. Specifically, we take limited information to compute expected income and losses when interference between primary users (PUs) and SUs occurs, and present a virtual request method for changing of spectrum’s actual state. Thorough theoretical analysis proves the truthfulness of FORTUNE. Furthermore, given a sample set with 5%-30% noise in spectrum sensing, FORTUNE achieves not only truthfulness, but also up to 50% higher channel utilization than existing spectrum auction mechanisms.

Heterogeneous network spectrum allocation scheme based on three-phase bargaining game

The fifth generation (5G) networks are envisioned to support the exploding mobile data traffic demands while improving quality of service (QoS) provision. The heterogeneous network (HetNet) platform provides one possible solution for dealing with this traffic explosion problem. However, several technical issues and challenges are associated with the deployment of HetNets. In this paper, we aim to design a new spectrum allocation scheme to effectively use the limited HetNet spectrum resource. By employing the main ideas of relative utilitarian, equality averse and inequality averse bargaining solutions, our approach unfolds into three stages of spectrum allocation process while balancing the efficiency and fairness. Based on the main features of each bargaining solution, we hierarchically apply these three solutions to spectrum assignment among BSs, spectrum allocation among SBSs, and spectrum sharing among applications, respectively. According to the advantages of cooperative bargaining approach, the proposed scheme takes various benefits in a rational way. The numerical simulations demonstrate the effectiveness and potential gain of our proposed three-phase spectrum allocation mechanism over the existing protocols.

Spectrum Allocation Strategies Based on QoS in Cognitive Vehicle Networks

The vehicular ad hoc network (VANET) is an important part of modern intelligent transportation systems (ITS), and its emergence has provided support for improving traffic safety and driving experience. The problem of spectrum scarcity has become evident due to the increasing demand for various VANET services. Using cognitive radio (CR) technology in VANET to solve the problem of spectrum scarcity has become a research focus in recent years. The existing spectrum allocation mechanism cannot effectively solve problems, such as high delay, uncertain quality of service (QoS), and low throughput. In this study, we investigate the spectrum allocation strategies in CR for VANET(CR-VANET). For different network optimization indicators under different load networks, we divide CR-VANET into two scenarios: high-load CR-VANET (HCR-VANET) and low-load CR-VANET (LCR-VANET). In LCR-VANET, we establish a model for maximizing throughput with two constraints and propose a channel allocation scheme based on a greedy algorithm (CASGA) to maximize the network throughput. In HCR-VANET, application services are divided into safe application services(SAS) and unsafe application services. To improve the acceptance probability of SAS, we also propose an SMDP-based channel allocation scheme (SMDP-CAS) to maximize the acceptance probability of SAS. Simulation results prove that CASGA and SMDP-CAS greatly improve the throughput of the network and the acceptance probability of SAS.

Periodic multimedia spectrum sensing method based on high-order anti-jamming mechanism in cognitive wireless networks

The cognitive radio network provides high bandwidth for mobile users to reconstruct wireless architecture and dynamic spectrum access technology. The spectrum allocation is the key to cognitive radio spectrum resources for the relative scarcity of radio spectrum resources. The spectrum allocation algorithm must have faster convergence speed to adapt to the time-varying characteristics of cognitive radio networks. In this paper, a spectrum sensing method is proposed based on high-order anti-jamming mechanism for cognitive radio spectrum allocation. Firstly, the combination of cognitive anti-jamming spectrum sensing, channel estimation, learning comprehension, time-hopping frequency hopping, spectrum access control and other technologies can improve the anti-jamming ability. Secondly, cognitive radio can effectively improve the utilization of spectrum resources according to the different benefits of different users on different channels, achieve the best matching between cognitive users and channels and flexible spectrum allocation. Finally, the effectiveness of the proposed algorithm is verified by simulation experiments.

<inline-formula> <tex-math notation="LaTeX">$PROST$ </tex-math> </inline-formula>: Privacy-Preserving and Truthful Online Double Auction for Spectrum Allocation

Spectrum auction is an effective way to redistribute scarce spectrum resources. However, most spectrum auction designs only target at economic robustness, while neglecting the inherent privacy leakage problem. Existing secure spectrum auction mechanisms fail to provide adequate security, and they all neglect the online fashion of spectrum request arrival. In this paper, for the first time, we propose a Privacy-pReserving and truthful Online double auction mechanism for Spectrum allocaTion in wireless networks, PROST . Compared with the state-of-the-art solutions, PROST provides a comprehensive and strong protection for users’ sensitive information, especially for location privacy and time dynamics. PROST is constructed based on our carefully designed security building blocks, which support various arithmetics over encrypted real numbers, and they are also well applicable in other spectrum auctions. Besides, we improve on the existing online spectrum auction mechanisms by designing a novel privacy-preserving buyer grouping protocol for spectrum reuse. We not only theoretically prove that PROST can realize an all-round security against semi-honest adversaries but also extensively evaluate its performance. Experimental results validate that PROST achieves nice spectrum allocation efficiency with light computation and communication costs.

Knowledge-Based Autonomous Service Provisioning in Multi-Domain Elastic Optical Networks

Optimization of end-to-end service provisioning across multi-domain EONs is critically important due to the restricted intra-domain visibility and the agile spectrum allocation mechanism of EONs. Previously demonstrated schemes apply fixed service provisioning policies (e.g., heuristic routing and spectrum assignment and threshold- based anomaly detection) and fail to fully address the inherent principle and dynamic conditions of multi-domain EONs. This article brings in data analytics and presents a knowledge-based autonomous service provisioning framework for multi-domain EONs. The proposed framework employs a new broker plane working with domain managers while supporting the autonomy of each management domain. This can be seen as a hierarchical multi-domain network control and management architecture in support of enhanced resource efficiency and network scalability where each hierarchy employs an observe-analyze-act cycle. Specifically, the broker and domain managers can observe the network state through comprehensive network monitoring (monitoring of optical paths' performance, resource utilization, and traffic dynamics), analyze the network behavior and form the knowledge repository of network rules using machine learning techniques, and act intelligently according to the obtained knowledge. We assess the proposed framework by evaluating two key knowledge-based service provisioning use cases: proactive inter-domain traffic-prediction- based autonomous traffic engineering and quality-of-transmission-aware inter-domain lightpath provisioning. Numerical results demonstrate remarkable benefits of the proposed framework over conventional solutions.

Financial Implications of Femtocell Deployment

Increased usage in wireless communication has been observed in the last decades and it is expected to rise even more. Traditional spectrum allocation mechanism together with increasing demand for data transfers caused spectrum to become more congested. As a consequence, high pressure for its more effective usage emerges. Modern concept of heterogeneous networks with cognitive femtocells represents one of the promising solutions. Associated technical issues of heterogeneous networks have been discussed in many papers. However, economic aspects of femtocell deployment in network are still insufficiently analysed. This paper is devoted to economic aspects of operators’ behaviour in the macro-femto network but we also focus on technical issue of overall spectrum usage. For this purpose, the agent-based model of two-tier network was proposed. Results of simulation confirm significant influence of number of deployed femtocells and their location in the network on operators’ pricing strategies and their whole economic performance.

Spectrum allocation strategy for heterogeneous wireless service based on bidding game

The spectrum scarcity crisis has resulted in a shortage of resources for many emerging wireless services, and research on dynamic spectrum management has been used to solve this problem. Game theory can allocate resources to users in an economic way through market competition. In this paper, we propose a bidding game-based spectrum allocation mechanism in cognitive radio network. In our framework, primary networks provide heterogeneous wireless service and different numbers of channels, while secondary users have diverse bandwidth demands for transmission. Considering the features of traffic and QoS demands, we design a weighted interference graph-based grouping algorithm to divide users into several groups and construct the non-interference user-set in the first step. In the second step, we propose the dynamic bidding game-based spectrum allocation strategy; we analyze both buyer’s and seller’s revenue and determine the best allocation strategy. We also prove that our mechanism can achieve balanced pricing schema in competition. Theoretical and simulation results show that our strategy provides a feasible solution to improve spectrum utilization, can maximize overall utility and guarantee users’ individual rationality.

On-demand ecology-inspired spectrum allocation mechanism for heterogeneous cognitive radio networks

As increasing number of cognitive radio network (CRN) standards are developed in TV White Spaces band with incompatible communication patterns, heterogeneous CRNs coexistence problem could not be avoided. However, most solutions on this problem have not considered CRNs’ actual data transmission demands and weighted fairness simultaneously. Therefore, we would like to introduce a novel On-demand ecological Species Competition based HEterogeneous networks coexistence MEchanism (O-SCHEME) in this paper. Inspired by ecology species competition model, O-SCHEME utilizes an ecology based spectrum allocation mechanism for guaranteeing heterogeneous CRNs’ spectrum shares weighted fairness. And by employing CRNs’ communication spectrum requirement constraints, actual data transmission needs could be satisfied without wasted communication resources. Through both theoretical and simulation analyses, we demonstrate that O-SCHEME can achieve stable and fair spectrum allocations among coexisting networks with high communication efficiency.

The effects of spectrum allocation mechanisms on market outcomes: Auctions vs beauty contests

This paper compares the evolution of seven key market outcomes in 47 countries after the allocation of mobile phone spectrum by auctions and beauty contests held from 2000 to 2008. Traditional auction theory predicts the merits of auction versus “beauty contests”. However, recent theoretical research shows that auctions impose selection and debt effects on the after-market competition that could harm consumers. We employ two semi-parametric estimators to determine the treatment effects and find that 3G mobile phone penetration rates among auctioning countries are 1.04–8.95% lower. Findings suggest that auctions, when used to raise public revenues, not only transfer profits to government but also sacrifice consumer surplus.

Dynamic downlink resource allocation and access strategy for femtocell networks

AbstractFemtocells are small, low‐power cellular base stations with high potential for coverage extension and offloading voice and wireless data. In this paper, we study the problem of joint access control and spectrum resource allocation in a 2‐tier femtocell network with 1 macro base station and multiple Femto access points (FAPs). The objective is to maximize the overall network capacity, while guaranteeing the quality of service requirement of all user equipments. We develop an access scheme for macro user equipments and a spectrum allocation mechanism for the FAPs. Spectrum allocation is used as an incentive mechanism to encourage FAPs to serve more macro user equipments. We also derive an upper bound of the network‐wide capacity through a reformulation of the problem. The proposed algorithms are validated, and the upper bound is shown to be quite accurate in the simulation study.