Centralized Dynamic Spectrum Allocation in Cognitive Radio Networks Based on Fuzzy Logic and Q-Learning

A novel centralized approach for Dynamic Spectrum Allocation (DSA) in the Cognitive Radio (CR) network is presented in this paper. Instead of giving the solution in terms of formulas modeling network environment such as linear programming or convex optimization, the new approach obtains the capability of iteratively on-line learning environment performance by using Reinforcement Learning (RL) algorithm after observing the variability and uncertainty of the heterogeneous wireless networks. Appropriate decision-making access actions can then be obtained by employing Fuzzy Inference System (FIS) which ensures the strategy being able to explore the possible status and exploit the experiences sufficiently. The new approach considers multi-objective such as spectrum efficiency and fairness between CR Access Points (AP) effectively. By interacting with the environment and accumulating comprehensive advantages, it can achieve the largest long-term reward expected on the desired objectives and implement the best action. Moreover, the present algorithm is relatively simple and does not require complex calculations. Simulation results show that the proposed approach can get better performance with respect to fixed frequency planning scheme or general dynamic spectrum allocation policy.

Spatio-Temporal Population Density and Spatial Dynamic Spectrum Allocation

A realistic population density distribution scenario in conjunction with the spatial dynamic spectrum allocation （DSA） is taken into account to mitigate the spectrum wastage in terms of extra guard bands. For the insertion of the extra guard bands, an efficient strategy based on self-assessment is applied to each victim cell individually and independently. Consequently, it is no more required to spread the extra guard band over the whole DSA region. Simulation results StlOW an improvement of 3% -4% in percentage of satisfied users for Universal Mobile Telecommunications System （UMTS） network and 4%-5% for Digital Video Broadcasting Terrestrial （DVB-T） network.

Dynamic spectrum allocations in multi-cells and intra-cell of cognitive network to enhance system performance

In this study, we propose new dynamic spectrum allocations in multi-cells and intra-cell of cognitive network to enhance system performance in terms of decreasing probability of interruption and spectrum handoff of communication services in a cognitive system. The inter-cells of the spectrum allocation mechanism is designed to share the risk of vacating spectrum caused by licensed incumbents re-occupying the spectrum and minimize probability of service interruption in the cognitive network. This mechanism also can guarantee fairness among multi-cells. The intra-cell of the proposed spectrum allocation is based on a service data hierarchical model and establishes a mapping mechanism between layered data and the spectrum. It can reduce probability of spectrum handoff. Finally, simulation results are given and show that the new mechanism can reduce service interruption ratio and the probability of spectrum handoff caused by licensed incumbents with re-occupying the spectrum.

Genetic approach for Cell-by-Cell dynamic spectrum allocation in the heterogeneous scenario

In this paper,a genetic algorithm (GA) is investigated to deal with cell-by-cell dynamic spectrumallocation (DSA) in the heterogeneous scenario with temporal and spatial traffic demand changes,whichis also known as a difficult combinatorial optimization problem.A new two-dimensional chromosome encodingscheme is defined according to characteristics of the heterogeneous scenario,which prevents forminginvalid solutions during the genetic operation and enables much faster convergence.A novel randomcoloring gene generation function is presented which is the basic operation for initialization and mutationin the genetic algorithm.Simulative comparison demonstrates that the proposed GA-based cell-by-cellDSA outperforms the conventional contiguous DSA scheme both in terms of spectral efficiency gain andquality of service (QoS) satisfaction.

Extended Virtual Boundary and Its Application in Dynamic Spectrum Allocation

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

Database-Assisted Dynamic Spectrum Access with QoS Guarantees:A Double-Phase Auction Approach

Since FCC's opening for white space(WS) utilization,database-assisted dynamic spectrum access(DSA) has become the de facto solution for the realization of dynamic spectrum sharing(DSS),due to its simplicity and compatibility with commercial off-the-shelf(COTS) devices.It is envisioned that such technology will strongly support the prosperous wireless multimedia networking(WMN) applications with satisfying QoS guarantees in the future.However,how to counter the time-frequency variant property when exploiting the WS spectrum for the provision of these services to secondary users(SUs) still remains a great challenge.In such context,a dynamic secondary access scheme for database-assisted spectrum sharing networks is proposed in this paper.In the beginning,the spectrum requirements of SUs for diverse services are modeled by considering the minimum required service data-rate and spectrum access duration.Afterwards,the spectrum demand evaluation and bidding policy are formulated based on the service classes of SUs.Furthermore,a doublephase(DP) spectrum allocation scheme,which consists of the initial resource allocation phase and resource allocation adjustment phase,is carefully designed for DSA.Finally,extensive simulations are conducted and the results demonstrate that our scheme can increase the spectrum trading revenue and adapt to varying service requirements.

A parallel algorithm for statistical-fairness-based spectrum allocation of cognitive radios

A parallel algorithm for statistical-fairness-based spectrum allocation of cognitive radios is proposedin this paper. The key idea of the algorithm is to pursue the maximum total spectrum utilization of thesystem by adopting a parallel technique in every spectrum allocation, and to ensure the statistical fairnessrule by deploying a particular scheme during a series of allocations. The simulation results show that theproposed algorithm not only achieves a fairer and more efficient allocation of spectrum resources, but alsohas much shorter allocation duration than the color sensitive graph coloring (CSGC) algorithm.