Multi-Stage Pricing Game for Collusion-Resistant Dynamic Spectrum Allocation

QoS-aware distributed spectrum sharing for heterogeneous wireless cognitive networks

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.

Allowing Secondary Users (SUs) to access the licensed spectrum without causing harmful interference to the Primary Users (PUs) is crucial in enabling the Cognitive Radio (CR) technology. In order to increase the utilization of the spectrum bands, we propose a Dynamic Spectrum Allocation (DSA) algorithm that integrates both interweave and underlay spectrum access schemes. The proposed algorithm will jointly take into account the geographical locations of the nodes, the correlated shadow fading, the interference between the primary and the secondary networks, the interference between SUs that are transmitting on the same channel, and the communications activity of the users. Moreover, a suboptimal heuristic DSA algorithm that jointly takes into consideration all of the aforementioned issues, while requiring low computational- and time-costs, is developed. Simulation results show that the proposed algorithm provides a good success rate and outperforms classical spectrum allocation algorithms.

Flexible optical networks appear as the most prevalent candidates for next-generation core transport networks. The transition from a fixed to a flexible frequency grid calls for novel spectrum allocation techniques. This work focuses on the notion of dynamic cooperative spectrum sharing and addresses the issue of dynamic cooperative spectrum allocation for flexible optical networks. In orderto cope with the dynamicity of the traffic demands, spectrum expansion/contraction (SEC) policies attempt to accommodate incoming requests by means of expanding/contracting the allocations of connections. When spectrum expansion is limited by neighboring connections, appropriate spectrum defragmentation (SD) policies undertake the task of reallocating connections in order to free up the spectrum. In this work, a novel cooperative SEC policy is examined, which takes into consideration the spectrum allocation of neighboring connections. Additionally, a class of cooperative SD policies is proposed, based on the capabilities of current technology. Simulation results from two reference core networks quantify the benefits that can be reaped in terms of blocking rate. Trade-offs with respect to the achieved reduction in blocking rate and the number of reallocated connections during the SD procedure are examined.

In this paper, a novel spectrum allocation approach for cognitive radio networks (CRNs) is proposed. Based on a measure of inference performance as well as on a measure of quality-of-service, the association between secondary users (SUs) in the network and frequency bands licensed to primary users (PUs) is investigated. The problem is formulated as a matching game between SUs and PUs. In this game, SUs employ hypothesis testing to detect PUs' signals and, eventually, rank them based on the logarithm of the a posteriori probability ratio. A valuation that captures the ranking metric and rate over the PU-owned frequency bands is proposed to PUs in the form of credit or rewards by SUs. Using this proposal, a PU evaluates a utility function that it uses to build its association preferences. A distributed algorithm that allows both SUs and PUs to interact and self-organize into a stable and optimal matching is presented. Simulation results show that the proposed algorithm can improve: i) the sum of SUs' rates by up to 20% and 60% relative to the deferred acceptance algorithm and random channel allocation approach respectively, and ii) the sum of PUs' payoffs by up to 25% compared to the deferred acceptance algorithm. The results also show an improved convergence time.

Dynamic spectrum allocation can improve spectrum efficiency by exploiting the traffic loads variations of multiple wireless network systems, when they share neighboring band. In this study, we use a centralized approach in which a spectrum manager periodically re-allocates spectrum among two networks in a single cell. We propose a two levels model (a spectrum level model and a call level model) to characterize the dynamic spectrum allocation. We have further validated the approximated numerical results by simulations. Numerical and simulation results show that the performances of networks with the dynamic spectrum allocation are better than those with fixed allocation and complete its performance analysis via approximation and iterative approach. Hence, we conclude that our model and scheme can improve Quality of Service (QoS) of wireless networks when spectrum is limited.

Wireless Sensor Networks (WSNs) use the unlicensed Industrial, Scientific, and Medical (ISM) band for transmissions. However, with the increasing usage of these networks for diverse applications, the currently available ISM band does not suffice for their transmissions and a new challenge appears before the WSNs' research community. One of the candidate approaches to tackle this spectrum insufficiency problem is to incorporate the opportunistic spectrum access capability of Cognitive Radio (CR) into the existing WSN, thus giving birth to Cognitive Radio Sensor Network (CRSN). Efficient spectrum utilization is another approach to overcome this challenging problem. Another challenge associated to WSN operation is the dependability of sensor nodes on battery supplied power where the batteries in general are not replaceable. Therefore, advanced and intelligent radio resource management schemes are very essential to perform dynamic and efficient spectrum allocation among multiple sensor nodes and to optimize the power consumption of each individual node in the network. Radio resource management enables the sensor nodes to efficiently utilize the available spectrum and power, which in turn ensures QoS transmissions, maximizes the network lifetime, and reduces the inter-node and inter-network interferences. In this chapter, the authors present a comprehensive overview of the recent advances in radio resource management for CRSN. Radio resource management in CRSN has been reviewed in various scenarios (i.e., centralized, cluster-based, and distributed). The related issues and challenges are discussed, and future research directions are highlighted.

In order to improve spectrum utilization, dynamic spectrum allocation DSA schemes with interference management have been widely investigated, and a special interest is in the current heterogeneous wireless network HWN environment. In the previous work, the approach that guarantees quality of service for the cell-boundary user is extensively used in the DSA scheme. However, such approach gives a pessimistic result. In this paper, we design a DSA scheme for the HWN system, which adopts relatively accurate interference constraints. First, considering that users may randomly locate over the cell, we propose interference constraints across the cell coverage, in which the interference experienced at a point is controlled below the level suffered when using fixed spectrum allocation in only a single network, and the proportion of the cell area where interference is controlled reaches the required area coverage probability. Then under the interference constraints, we formulate the downlink DSA scheme as a combinatorial optimization problem. As the problem is NP-hard, to reduce the computational complexity, we propose two greedy heuristic algorithms for its solution. Simulation results show that the DSA scheme could improve the total spectrum utility for operators and increase the satisfaction rate of spectrum demands for base stations. Copyright © 2013 John Wiley & Sons, Ltd.

This paper presents and evaluates the performance of a temporal dynamic spectrum allocation (DSA) scheme based on the CDMA networks as an alternative to the fixed spectrum allocation (FSA) methods. The paper considers the spectrum allocation between two code division multiple access (CDMA) systems with different time-varying traffic pattern. The traffic pattern is based on the real CDMA traffic data from Daegu urban area in Korea. A proposed algorithm is investigated by the simulation based on CDMA call processing and shows that can produce significant gains for the radio access network (RAN) in DSA.

In this paper, we propose a grouping-based dynamic routing, core, and spectrum allocation (RCSA) method for preventing spectrum fragmentation and inter-core crosstalk in elastic optical path networks based on multi-core fiber environments. Multi-core fibers enable us to considerably enhance the transmission capacity of optical links; however, this induces inter-core crosstalk, which degrades the quality of optical signals. We should thus avoid using the same frequency bands in adjacent cores in order to ensure high-quality communications. However, this simple strategy leads to inefficient use of frequency-spectrum resources, resulting in spectrum fragmentation and a high blocking probability for lightpath establishment. The proposed method allows one to overcome this difficulty by grouping lightpath-setup requests according to their required number of frequency slots. By assigning lightpath-setup requests belonging to the same group to cores according to their priority, the proposed method aims to suppress inter-core crosstalk. Furthermore, the proposed method is designed to mitigate spectrum fragmentation by determining the prioritized frequency bandwidth for lightpath-setup requests according to their required number of frequency slots. We show that the proposed method reduces the blocking of lightpath establishment while suppressing inter-core crosstalk through simulation experiments.

This paper considers distance adaptive dynamic routing and spectrum assignment (RSA) for elastic optical networks with shared backup path protection (SBPP). Efficient heuristic algorithms based on spectrum window planes are proposed for implementing distance and modulation format adaptive RSA so as to maximize spare capacity sharing among multiple protection lightpaths. A differentiated sharable frequency slot cost was also defined for the first time to more efficiently share protection resource. Network performance is evaluated in terms of bandwidth blocking probability (BBP) through simulations. The proposed SBPP technique is effective in reducing BBP and improving spectral efficiency compared to conventional SBPP schemes and 1+1 path protection. The impact of transponder tunability on bandwidth blocking performance is also evaluated to show that a limited tuning range is sufficient to achieve a BBP performance close to that with full tunability.

Presently a new technology which is highly preferred is wireless ADHOC networks. The traffic of the wireless ADHOC networks day by day is growing up due to this the scarcity problem arises in the available spectrum. The channel resources are allocated in Cognitive Radio Network (CRN) with a Dynamic Access methods of available sensed radio environment. The Dynamic Spectrum Allocation (DSA) is a suitable technique which solves the issue of spectrum scarcity in the CRNs. This DSA will coordinate with the channel access for schedule sensing , release connection etc. when two networks are active at the same moment. Here this research paper provides an analysis of reliable channels exclusively used for CRNs with respect to distribution of license-exempt bands and also determining the potential and limitations of every methods.

A two-tier heterogeneous network, comprised of a macrocell underlaid with flexible and uncoordinated femtocell network, provides an economically viable way to improve indoor coverage, users' QoS and the capacity of the whole cellular network. However, mutual interference between macrocell and femtocell limits capacity and leads to the problem of coexistence. This paper proposes a game theoretical and decentralized spectrum negotiation framework to solve the above-mentioned problem. Macrocell and femtocell users have to reach a mutual satisfactory agreement on the partition of spectrum by making alternating offers to each other. By modeling the bargaining process as multi-stage dynamic game, we are able to obtain the equilibrium outcome. Theoretical and numerical analysis on negotiation results show that macrocell and femtocell can achieve a fair, efficient, and incentive compatible spectrum allocation via the proposed bilateral negotiation interactions.

Mobile communication plays an important role in the future of communication systems. To meet personalized and intelligent requirements, mobile communication has evolved from single wireless cellular network to heterogeneous mobile communication network, including wireless cellular network, wireless local network, and wireless personal network. In the heterogeneous communication system, to entirely fulfill the spectrum resource complementary advantages of such a heterogeneous wireless network, the spectrum resource trade algorithm has attracted tremendous research efforts. In this paper, the advantages and disadvantages of dynamic spectrum allocation and load balancing are discussed and spectrum auction takes the place of spectrum allocation to maximize the operation revenue. The authors design a joint spectrum auction and load balancing algorithm (SALB) based on heterogeneous network environment to develop a more flexible and efficient spectrum management. The simulation result shows that SALB increases the operation profit significantly.

The metro section of telecom networks is currently pressured by a strong increase of traffic required by end users. Especially mobile end users are adopting new media-rich services that require high bandwidth. These users are characterized by a geographical mobility this mobility induces significant changes in the traffic pattern at metro level. So future metro networks are expected not only to provide very large capacities but also to support sudden (dynamic) changes of the traffic pattern. An optical metro network based on the concept of flexible spectrum grid can address such requirements in terms of bandwidth and flexibility. In this paper we show the benefits of employing a flexible grid in metro ring networks compared to a fixed-grid WDM case, under dynamic (changing) traffic. The adoption of flexible grid enables an effective spectrum utilization resulting in network blocking a few orders of magnitude lower with respect to fixed grid case.