TV White Space Networks Research Articles

Improved spectrum allocation scheme for TV white space networks using a hybrid of firefly, genetic, and ant colony optimization algorithms

This study proposes a novel hybrid Firefly Algorithm, Genetic Algorithm, and Ant Colony Optimization Algorithm (FAGAACO) for spectrum allocation in TV White Space (TVWS) networks. The Genetic Algorithm (GA) was used in the design to provide cross-over chromosomes to both the Firefly Algorithm (FA) and the Ant Colony Optimization Algorithm (ACO), thereby improving the exploration abilities of FA and ACO and preventing FA and ACO from becoming trapped in local optimum. The proposed algorithm was implemented using MATLAB R2018a. Simulation results show that in comparison with a hybrid of the Firefly Algorithm and Genetic Algorithm (FAGA), the proposed algorithm achieved 13.03% higher throughput, 1.3% improved objective function value and 5.03% higher runtime due to the good accuracy of the proposed algorithm. Based on these improvements, the proposed algorithm is therefore an efficient spectrum allocation technique in TVWS networks.

Novel Resource Allocation Algorithm for TV White Space Networks Using a Hybrid of Firefly Algorithm, Genetic Algorithm, and Ant Colony Optimization Algorithm

Novel Resource Allocation Algorithm for TV White Space Networks Using a Hybrid of Firefly Algorithm, Genetic Algorithm, and Ant Colony Optimization Algorithm

TV White Space Network Power Allocation Using Hybrid Grey Wolf Optimizer with Firefly Algorithm and Particle Swarm Optimization

TV white spaces (TVWS) can be utilized by Secondary Users (SUs) equipped with cognitive radio functionality on the condition that they do not cause harmful interference to Primary Users (PUs). Optimization of power allocation is necessary when there is a high density of secondary users in a network in order to reduce the level of interference among SUs and to protect PUs against harmful interference. Grey Wolf Optimizer (GWO) is relatively recent population based metaheuristic algorithm that has shown superior performance compared to other population based metaheuristic algorithms. Recent trend has been to hybridize population based metaheuristic algorithms in order to avoid the problem of getting trapped in a local optimum. This paper presents the design and analysis of performance of a hybrid grey wolf optimizer and Firefly Algorithm (FA) with Particle Swarm Optimization operators for optimization of power allocation in TVWS network power allocation as a continuous optimization problem. Matlab was used for simulation. The hybrid of GWO, FA and PSO (HFAGWOPSO) reduces sum power by 81.42% compared to GWO and improves sum throughput by 16.41% when compared to GWO. Simulation results also show that the algorithm has better convergence rate.

Comparison of Hybrid Firefly Algorithms for Binary and Continuous Optimization Problems in a TV White Space Network

TV white spaces (TVWS) can be used by Secondary Users (SUs) through Dynamic Spectrum Access (DSA) as long as they do not cause harmful interference to Primary Users (PUs). Due to spectrum scarcity, there is increasing demand for DSA. When there is a high density of SUs in a TVWS network such as cellular access to TVWS, problem of interference among SUs will arise. Possibility of harmful interference to PUs may also arise. Power and spectrum allocation optimization is therefore necessary to reduce the level of interference among SUs and to protect PUs against harmful interference. In this paper different hybrid firefly algorithms with particle swarm optimization and genetic algorithm for optimization of spectrum allocation in a TVWS network as a discrete optimization problem and that of power allocation as a continuous optimization problem are compared. Simulation was done using Matlab. Simulation results show that hybrid firefly algorithm with genetic algorithm outperforms other hybrid firefly algorithms for spectrum allocation. On the other hand, hybrid firefly algorithm with genetic algorithm and particle swarm optimization outperforms all other algorithms for power allocation as continuous optimization problem

Interference Mitigation of Heterogeneous Cognitive Radio Network using Spatial Diversity

The heterogeneous cognitive radio networks are playing the most important role in the future generation wireless networks in order to address the problem of spectrum scarcity and to satisfy the demand of multiple coexistence networks. . In a country like India the deployment of CRN is possible on television network with the help of TV White Spaces (TVWS) as its capacity is quite high due to digital transmission of TV channel. The use of multiple wireless standards such as IEEE 802.11a, IEEE 802.22, IEEE 802.19.1 and many more wireless networks operating in the same frequency band of TVWS creates the coexistence scenario which involves the heterogeneous networks. The interference mitigation is the most important issue in such heterogeneous networks. In literature, the issue of interference mitigation is addressed mainly at the medium access layer; however, very limited work is presented at physical layer. In this paper, an interference mitigation problem of heterogeneous cognitive radio network at physical layer is addressed. The spatial diversity based techniques are proposed to mitigate the interference in heterogeneous CRN. The coexistence of different wireless networks in secondary CRN is considered for analysis. The characterization of aggregate interference is carried out for different interference scenarios. The proposed system outperform for heterogeneous CRN network over TVWS network.

Comparison of Hybrid Firefly Algorithms for Power Allocation in a TV White Space Network

Comparison of Hybrid Firefly Algorithms for Power Allocation in a TV White Space Network

A Survey of Resource Allocation in TV White Space Networks

A Survey of Resource Allocation in TV White Space Networks

Busy tone based coexistence algorithm for WRAN and WLAN systems in TV white space

TV White Space (TVWS) refers to frequency band reserved only for licensed terrestrial TV broadcasting and is opened to unlicensed use under regulatory conditions. While regulations protect licensed systems from interference, interference among unlicensed systems is left mainly to manufacturers. Consequently, there is a need to develop new coexistence approaches between TVWS networks. Busy tone broadcasting is a coexistence method, which can be used by TVWS networks to announce the selected frequency band is occupied. In this paper, a busy tone based coexistence algorithm is proposed for IEEE 802.11af and IEEE 802.22 networks and analyzed by considering different client distributions experiencing log-normal shadowing, where the exact interfering packet rate and successful packet transmission rate expressions are obtained and validated by simulations for different scenarios. The results show that with the proposed coexistence approach, a WLAN can reliably detect the busy tone signal to change its frequency band and can reduce interference to WRAN. Even if there is no available frequency band for the WLAN, the WRAN still maintains its enhanced successful packet transmission performance. The deployment of the proposed algorithm is important for successful coexistence between cognitive wireless networks, where interference is not regulated, such as in TVWS bands.

TV White Space and LTE Network Optimization Toward Energy Efficiency in Suburban and Rural Scenarios

The radio spectrum is a limited resource. Demand for wireless communication services is increasing exponentially, stressing the availability of radio spectrum to accommodate new services. TV white space (TVWS) technologies allow a dynamic usage of the spectrum. These technologies provide wireless connectivity, in the channels of the very high frequency and ultra high frequency television broadcasting bands. In this paper, we investigate and compare the coverage range, network capacity, and network energy efficiency for TVWS technologies and LTE. We consider Ghent, Belgium, and Boyeros, Havana, Cuba, to evaluate a realistic outdoor suburban and rural area, respectively. The comparison shows that TVWS networks have an energy efficiency 9–12 times higher than LTE networks.

Improved Resource Allocation for TV White Space Network Based on Modified Firefly Algorithm

There is continued increased demand for dynamic spectrum access of TV White Spaces (TVWS) due to growing need for wireless broadband. Some of the use cases such as cellular (2G/3G/4G/5G) access to TVWS may have a high density of users that want to make use of TVWS. When there is a high density of secondary users (SUs) in a TVWS network, there is possibility of high interference among SUs that exceeds the desired threshold and also harmful interference to primary users (PUs). Optimization of resource allocation (power and spectrum allocation) is therefore necessary so as to protect PUs against harmful interference and to reduce the level of interference among SUs. Existing resource allocation optimization algorithms for a TVWS network ignore adjacent channel interference, interference among SUs or apply greedy algorithms which result in sub-optimal resource allocation. In this paper we propose an improved resource allocation algorithm based on continuous-binary firefly algorithm. Simulation is done using Matlab. Simulation results show that the proposed algorithm improves the SU sum throughput and SU signal to interference noise(SINR) ratio in the secondary network.

Energy Efficiency Consideration for Indoor Femtocell Networks in TV White Spaces

The federal communications commission (FCC) took the unprecedented step to approve the usage of TV white spaces, i.e., locally vacant TV channels, in 2012. This TV spectrum will present new opportunities for wireless access technologies and applications, e.g., femtocell networks. The utilization of TV white spaces in femtocell networks also comes with some technical challenges. One of the most fundamental is that how much capacity and energy efficiency can be achieved in TV white spaces network. Prior works only focused on capacity consideration for cellular network in outdoor scenario leaving important femtocell network in indoor scenario largely open for investigation. In this paper, we explore the capacity and energy efficiency for femtocell network by developing a TV white spaces reuse and power allocation scheme. The problem is formulated into an optimization problem with the objective to maximize the energy efficiency achieved by a femtocell network, while keeping the interference to the primary receiver and macro receiver at an acceptable level. We demonstrate the existence of a unique globally optimal transmit power vector for all the femtocells, and propose a gradient absent algorithm to obtain it. Simulation results show that the femtocell can have a considerable capacity and energy efficiency improvement by using the TV channels.

Dynamic Adaptive Video Streaming on Heterogeneous TVWS and Wi-Fi Networks

Nowadays, people usually connect to the Internet through a multitude of different devices. Video streaming takes the lion’s share of the bandwidth, and represents the real challenge for the service providers and for the research community. At the same time, most of the connections come from indoor, where Wi-Fi already experiences congestion and coverage holes, directly translating into a poor experience for the user. A possible relief comes from the TV white space (TVWS) networks, which can enhance the communication range thanks to sub-GHz frequencies and favorable propagation characteristics, but offer slower datarates compared with other 802.11 protocols. In this paper, we show the benefits that TVWS networks can bring to the end user, and we present CABA, a connection aware balancing algorithm able to exploit multiple radio connections in the favor of a better user experience. Our experimental results indicate that the TVWS network can effectively provide a wider communication range, but a load balancing middleware between the available connections on the device must be used to achieve better performance. We conclude this paper by presenting real data coming from field trials in which we streamed an MPEG dynamic adaptive streaming over HTTP video over TVWS and Wi-Fi. Practical quantitative results on the achievable quality of experience for the end user are then reported. Our results show that balancing the load between Wi-Fi and TVWS can provide a higher playback quality (up to 15% of average quality index) in scenarios in which the Wi-Fi is received at a low strength.

An Integrated Spectrum and Information Market for Green Cognitive Communications

A database-assisted TV white space network can achieve the goal of green cognitive communication by effectively reducing the energy consumption in cognitive communications. The success of such a novel network relies on a proper business model that provides substantial incentives for all parties involved. In this paper, we propose an integrated spectrum and information market for a database-assisted TV white space network, where a geolocation database acts as an online platform providing services to both a spectrum market and an information market. We model the interactions among the database operator, the spectrum licensee, and the unlicensed users as a three-stage sequential decision process. Specifically, Stage I characterizes the negotiation between the database and the spectrum licensee, in terms of the commission for the licensee to use the spectrum market platform, Stage II models the pricing decisions of the database and the spectrum licensee, and Stage III characterizes the subscription behaviors of the unlicensed users. Analyzing such a three-stage model is very challenging due to the co-existence of positive and negative network externalities in the information market. We explicitly characterize the impact of network externalities on the equilibrium behaviors of all parties involved. We also analytically show that the spectrum licensee can never get a market share larger than half in the integrated market. Our numerical results further show that the proposed integrated market can outperform the pure information market in terms of network profit up to 87%.

Optimal Strategy Design for Enabling the Coexistence of Heterogeneous Networks in TV White Space

Very recently, regulatory bodies worldwide have approved dynamic access of unlicensed networks to the TV white space (TVWS) spectrum. Hence, in the near future, multiple heterogeneous and independently operated unlicensed networks will coexist within the same geographical area over shared TVWS. Although heterogeneity and coexistence are not unique to TVWS scenarios, their distinctive characteristics pose new and challenging issues. In this paper, the problem of the coexistence interference among multiple heterogeneous and independently operated secondary networks (SNs) in the absence of secondary cooperation is addressed. Specifically, the optimal coexistence strategy, which adaptively and autonomously selects the channel maximizing the expected throughput in the presence of coexistence interference, is designed. More in detail, at first, an analytical framework is developed to model the channel selection process for an arbitrary SN as a decision process. Then, the problem of the optimal channel selection, i.e., the channel maximizing the expected throughput, is proved to be computationally prohibitive (NP-hard). Finally, under the reasonable assumption of identically distributed interference on the available channels, the optimal channel selection problem is proved not to be NP-hard, and a computationally efficient (polynomial-time) algorithm for finding the optimal strategy is designed. Numerical simulations validate the theoretical analysis.

WhiteFi Infostation: Engineering Vehicular Media Streaming With Geolocation Database

The TV white spaces (TVWS) enabled infostation has received significant attention due to its wide area coverage for cost-effective and media-rich content dissemination. In this paper, we engineer WhiteFi infostation, which is dedicated for Internet-based vehicular media streaming by leveraging geolocation database. After demonstrating the empirical observations of unique TVWS features and analyzing the real-world TVWS data collected from geolocation database, we first propose an optimal TVWS network planning to deploy WhiteFi infostation with the objective of maximizing network-wide throughput. The proposed TVWS network planning jointly considers the multi-radio configuration and the channel-power tradeoff, which can be realized by decentralized Markov approximation. Furthermore, we introduce a location-aware contention-free multi-polling access scheduling scheme for vehicular media streaming, which considered both the realistic vehicular applications and dynamics of wireless channel conditions. Through extensive simulations with real-world empirical TVWS data and urban vehicular traces, we demonstrate that our WhiteFi infostation solution can well support both the delay-sensitive and delay-tolerant vehicular media streaming services.

Modernizing African Townships using TV White Space Networks: A Case study of Mankweng Township in South Africa

The role of cheap and easy access to various telecommunication facilities is crucial for further community development. Such an observation is of particular importance for the developing countries all over the world since reliable and open access to communication systems can fasten the reduction of the development gap. In this work we analyse the benefits that can be obtained by application of TV White Space network, i.e. the network that operates in vacated TV band in a cognitive manner. The whole analysis is conducted based on specific use-case, i.e. the test network deployed in the Mankweng Township

On the Probabilistic Deployment of Smart Grid Networks in TV White Space.

To accommodate the rapidly increasing demand for wireless broadband communications in Smart Grid (SG) networks, research efforts are currently ongoing to enable the SG networks to utilize the TV spectrum according to the Cognitive Radio paradigm. To this aim, in this letter, we develop an analytical framework for the optimal deployment of multiple closely-located SG Neighborhood Area Networks (NANs) concurrently using the same TV spectrum. The objective is to derive the optimal values for both the number of NANs and their coverage. More specifically, regarding the number of NANs, we derive the optimal closed-form expression, i.e., the closed-form expression that assures the deployment of the maximum number of NANs in the considered region satisfying a given collision constraint on the transmissions of the NANs. Regarding the NAN coverage, we derive the optimal closed-form expression, i.e., the closed-form expression of the NAN transmission range that assures the maximum coverage of each NAN in the considered region satisfying the given collision constraint. All the theoretical results are derived by adopting a stochastic approach. Finally, numerical results validate the theoretical analysis.

Trust-Aware Consensus-Inspired Distributed Cooperative Spectrum Sensing for Cognitive Radio Ad Hoc Networks

Cooperation among cognitive radios for spectrum sensing is deemed essential for environments with deep shadows. In this paper, we study cooperative spectrum sensing for cognitive radio ad hoc networks where there is no fusion center to aggregate the information from various secondary users. We propose a novel consensus-inspired cooperative sensing scheme based on linear iterations that is fully distributed and low-cost. In addition, the tradeoffs on the number of consensus iterations are explored for scenarios with different shadow fading characteristics. Furthermore, we model insistent spectrum sensing data falsification (ISSDF) attack aimed at consensus-based iterative schemes and show its destructive effect on the cooperation performance which accordingly results in reduced spectrum efficiency and increased interference with primary users. We propose a trust management scheme to mitigate these attacks and evaluate the performance improvement through extensive Monte Carlo simulations for large-scale cognitive radio ad hoc networks in TV white space. Our proposed trust management reduces the harm of a set of collusive ISSDF attackers up to two orders of magnitude in terms of missed-detection and false alarm error rates. Moreover, in a hostile environment, integration of trust management into cooperative schemes considerably relaxes the sensitivity requirements on the cognitive radio devices.

Protection of Incumbent Services and Its Impact on Coverage of TV Band Device Networks in TV White Space

This paper presents a set of candidate regulatory requirements for TV band devices (TVBDs) in the Rep. of Korea. To guarantee the protection of incumbent services, especially digital TV (DTV) and wireless microphones, in TV frequency bands, we suggest minimum separation distances of TVBDs from the noise-limited contour according to incumbent users and TVBD types. This paper also deals with multiple sets of separation distances of a co-channel TVBD network from a DTV protected contour on the basis of the radio propagation characteristics of different geographic areas to make good use of TV white space (TVWS) and safely protect the DTV service. We present a low-power transmission mode of TVBDs and the relevant separation distances for small-cell deployment. The service coverage reduction ratio of a TVBD network is investigated in the presence of DTV interference in four geographic areas. The TVWS field verification results, conducted on the island of Jeju (Rep. of Korea), show that incumbent services operate well without harmful interference from neighboring TVBDs with the proposed separation distances.

Distributed Spectrum Management in TV White Space Networks

We investigate the distributed spectrum management problem in opportunistic TV white space (TVWS) systems using a game theoretical approach that accounts for adjacent-channel interference and spatial reuse. TV band devices (TVBDs) compete to access idle TV channels and select channel “blocks” that optimize an objective function. This function provides a tradeoff between the achieved rate and a cost factor that depends on the interference between TVBDs. We consider practical cases where contiguous or noncontiguous channels can be accessed by TVBDs, imposing realistic constraints on the maximum frequency span between the aggregated/bonded channels. We show that under general conditions, the proposed TVWS management games admit a potential function. Accordingly, a “best response” strategy allows us to determine the spectrum assignment of all players. This algorithm is shown to converge in a few iterations to a Nash equilibrium. Furthermore, we propose an effective algorithm based on Imitation dynamics, where a TVBD probabilistically imitates successful selection strategies of other TVBDs in order to improve its objective function. Numerical results show that our game theoretical framework provides a very effective tradeoff (close to optimal, centralized spectrum allocations) between efficient TV spectrum use and reduction of interference between TVBDs.