White Space Database Research Articles

Joint sub-Nyquist wideband spectrum sensing and reliable data transmission for cognitive radio networks over white space

The emerging cognitive radio technology resolves the spectrum scarcity problem by exploiting the unutilised licenced spectrum on an opportunistic basis. Meanwhile, future cognitive devices require advanced sensing techniques for rapid and active identification of spectrum holes over a wideband. Incorporation of prior information from the geolocation database enhances the sensing performance, reduces the computation complexity and maximizes the spectrum utilisation by white space devices. However, unlike the TV white space database, other wideband spectrum databases are not yet available. Therefore for dynamic and fragile cognitive networks, the geolocation database cannot assist the spectrum sensing process, which necessitated database-independent real-time spectrum sensing. Constant interference from primary users is yet another major challenge with cognitive radio networks which makes reliable communication extremely difficult for secondary users. Forward error correction codes ensure the reliability of transmitted data, among which low-density parity check codes are the most appropriate. Lengthy low-density parity check codes, however, have certain drawbacks specifically high encoding and decoding complexity. Parallel concatenated Gallager code addresses these issues. This paper presents a reliable data transmission scheme for secondary users using the proposed non-zero syndrome parallel concatenated Gallager codes with interleaver for cognitive radio networks performing real-time spectrum sensing over white space. The joint sensing scheme along with prior knowledge from the geolocation database improves the spectrum sensing performance with reduced complexity and is more suitable for low-power cognitive devices. Further, simulation results affirm that proposed PCGC outperform a dedicated LDPC in terms of coding gain and bit-error rate.

TV White Space Database and Augmented Sensing Algorithmic Research

Although the space resources are rather scarce, the research shows that the spectrum efficiency of the current spectrums is very low in China. This article presents an available method to construct TV white space database and an efficient augmented sensing algorithm based on the database. The goal is to sense the spectral distribution at a given location. To verify the proposed method is feasible, we only take a fixed area into account. In this paper, we selected some of the cellular-base-stations in an urban area to construct the database, and we can get the spectral distribution of an arbitrary location in the city. The results show that our database can give a quick response once a request comes, and it can display the accurate spectrum distribution of the area.

Optimizing privacy-preserving DSA for mobile clients

The exponential growth of connected wireless devices has led to a depletion of the available wireless spectrum. To this end, dynamic spectrum access (DSA) has been proposed as a viable framework for maximizing the usability of the wireless spectrum by allowing some portions of it to be accessed and used in a dynamic manner. Contrary to the legacy fixed spectrum access policy, DSA enables license-exempt users to access licensed bands during their respective owner’s idle times. Specifically, in the database-driven DSA model, mobile users issue location-based queries to a white-space database and request idle channels in their area. To preserve location privacy, existing solutions suggest the use of private information retrieval (PIR) protocols when querying the database. Nevertheless, these methods are not communication efficient and fail to take into account user mobility. In this paper, we address these shortcomings and propose an efficient privacy-preserving protocol based on the Hilbert space filling curve. We provide optimizations for mobile users that require privacy on-the-fly and users that have full a priori knowledge of their trajectory. Results from our experimentation on two real life datasets show that, compared to the current state-of-the-art protocol, our methods reduce the query processing cost at the mobile clients by a factor of 2 to 8.

Performance of a TV white space database with different terrain resolutions and propagation models

Cognitive Radio has now become a realistic option for the solution of the spectrum scarcity problem in wireless communication. TV channels (the primary user) can be protected from secondary-user interference by accurate prediction of TV White Spaces (TVWS) by using appropriate propagation modelling. In this paper we address two related aspects of channel occupancy prediction for cognitive radio. Firstly we investigate the best combination of empirical propagation model and spatial resolution of terrain data for predicting TVWS by examining the performance of three propagation models (Extended-Hata, Davidson-Hata and Egli) in the TV band 470 to 790 MHz along with terrain data resolutions of 1000, 100 and 30 m, when compared with a comprehensive set of propagation measurements taken in randomly-selected locations around Hull, UK. Secondly we describe how such models can be integrated into a database-driven tool for cognitive radio channel selection within the TVWS environment.

You Can Jam But You Cannot Hide: Defending Against Jamming Attacks for Geo-Location Database Driven Spectrum Sharing

The emerging paradigm for dynamic spectrum sharing is based on allowing secondary users (SUs) to exploit white space frequency that is not occupied by primary users. White space database provides an opportunity for SUs to obtain spectrum availability information by submitting a location-based query. However, this new paradigm can also be exploited by the attackers to significantly enhance their jamming capability due to the available channel information from spectrum queries, which is expected to increasingly block SUs. The challenge is that the unique characteristics (e.g., lack of the wide range frequencies or continuous broadband) make existing anti-jamming techniques (e.g., direct-sequence spread spectrum and frequency hopping spread spectrum) difficult to be applied. In this paper, we present a novel Jammer Inference-based Jamming Defense (jDefender) framework. The main idea of jDefender is inferring the likelihood of a user being a jammer based on the observed jamming events and then utilizing the inferred attack likelihood to enhance the effectiveness of a series of the proposed anti-jamming strategies. Specifically, we first propose the Channel Allocation-based Jammer Inference scheme to infer the likelihood of an SU being a jammer based on the channels occupied by SUs even under the collusion attack performed by multiple jammers. The strength of the anti-jamming strategies (e.g., puzzle difficulties, available spectrum resources) will be correlated with the possibility of an SU being a jammer to achieve the tradeoff between system performance and jamming tolerance. We then implement the proposed scheme on Universal Software Radio Peripheral and PC. Extensive evaluations are performed to validate the effectiveness of the attacks and countermeasures.

Pricing Model for TV White Spaces Channels With Different Priorities

A new type of TV white space (TVWS) channel called the high priority channel (HPC) has been proposed by the regulator of Singapore. The HPCs are TVWS channels that will always be available to unlicensed white space devices (WSDs) although a white space database (WSDB) provider may impose fees to WSDs for using HPCs. The HPC is of interest to WSDB providers since it creates a new business opportunity for them. In this letter, we investigate the optimal fee for using HPCs such that the WSDB provider achieves the maximum revenue. The solution of the optimal fee is provided in this letter. From this study, it is observed that WSDB provider should not always increase the fee when the total number of WSDs increases as our results show that sometimes lowering the fee to attract more WSDs to use HPCs actually increases the revenue.

Price and Inventory Competition in Oligopoly TV White Space Markets

In this paper, we investigate an oligopoly-competitive TV white space (TVWS) market, where multiple secondary network operators compete to serve a common pool of secondary end users by using TVWS purchased from a white space database. We first study the competitive interactions among secondary operators. Specifically, we formulate the interactions as a noncooperative price-inventory competition game, where operators determine the spectrum inventory (purchased from the database) and the service price (charged to end users) simultaneously. We prove the existence and uniqueness of the Nash equilibrium using the supermodular game theory. Then, we study the impact of the database manager's wholesale pricing strategy on the market equilibrium. Specifically, we analytically show how the wholesale prices affect the operators' equilibrium inventory and pricing decisions. Based on this analysis, we further propose two different spectrum wholesale pricing strategies that maximize the database manager's profit and the total network profit, respectively. Our simulations evaluate the performance difference between these two wholesale pricing strategies.

Business modeling for TV white space networks

Database-assisted TV white space network is a promising paradigm of dynamic spectrum sharing, and can effectively improve spectrum utilization and alleviate spectrum scarcity via centralized control of TV white space databases residing in the cloud. In this article, we discuss business modeling for a database-assisted TV white space network, which is very important for wide commercialization of this promising technology. Motivated by several recent business practices, we propose and study two types of different business models: spectrum market and information market. In the spectrum market model, spectrum licensees, through spectrum brokers acted by databases, lease the underutilized (licensed) TV channels to unlicensed wireless devices for secondary utilization. In the information market model, databases sell the advanced information regarding (unlicensed) TV channels to unlicensed wireless devices in order to enhance the secondary spectrum utilization performance. We outline the corresponding trading mechanism details for both market models, and evaluate the feasibility and performance of both models through theoretical and numerical studies. Numerical results indicate that both the database operator’s profit and the total network profit can be significantly improved under properly designed trading mechanisms.

화이트 스페이스 활용을 위한 무선환경 인지 기술 및 활성화 방안

주파수 공유대역에서 가용 주파수 자원을 인지하여 효과적으로 공유하고 활용하기 위해서 데이터베이스 접속을 통한 무선환경 인지 기술과 광대역 스펙트럼 센싱을 통한 무선환경 인지 기술 개발이 필요하다. 본 논문에서는 IETF (Internet Engineering Task Force) PAWS (Protocol to Access White Space database) 표준 프로토콜 기반으로 개발한 TVWS (TV White Space) 데이터베이스 접속 프로토콜 구현 기술을 제시하고, TVWS에 적합한 MWC (Modulated Wideband Converter) 구조를 이용한 광대역 압축 스펙트럼 센싱 기술을 제안한다. 제안된 TVWS 데이터베이스 접속 프로토콜 구현 기술은 TVBD (TV Band Device)와 TVWS 데이터베이스에 탑재되어 실환경 테스트를 통해 안정적으로 동작함을 보인다. 본 연구에서 제안된 광대역 압축 스펙트럼 센싱 방식은 잡음 분산 추정 오차에 무관하게 일정 수준의 오경보 확률을 유지할 뿐만 아니라 95% 이상의 높은 검출 성능을 보인다. 또한, 본 논문에서는 미국 FCC와 유럽 ETSI에서 최근 마련한 TVWS 데이터베이스 정책을 분석하고, IETF에서 현재 마련 중인 화이트 스페이스 데이터베이스 접속 프로토콜에 관해 기술한다. Cognitive radio (CR) technology based on geo-location database access approach and/or wideband spectrum sensing approach is absolutely vital in order to recognize available frequency bands in white spaces (WSs), and efficiently utilize shared spectrums. This paper presents a new structure for the TVWS database access protocol implementation based on Internet Engineering Task Force (IETF) Protocol to Access WS database (PAWS). A wideband compressive spectrum sensing (WCSS) scheme using a modulated wideband converter is also proposed for the TVWS utilization. The developed database access protocol technology which is adopted in both the TV band device (TVBD) and the TVWS database operates well in the TV frequency bands. The proposed WCSS shows a stable performance in false alarm probability irrespective of noise variance estimation error as well as provides signal detection probabilities greater than 95%. This paper also investigates Federal Communications Commision (FCC) regulatory requirements of TVWS database as well as European Telecommunications Standards Institute (ETSI) policy related to TVWS database. A standardized protocol to achieve interoperability among multiple TVBDs and TVWS databases, which is currently prepared in the IETF, is discussed.

Low Complexity Uplink Schedulers for Energy-Efficient Cognitive Radio Networks

We formulate and solve energy-efficient uplink scheduling problem, and propose two low-complexity schedulers for a cognitive radio (CR) network with a white space database access. The proposed schedulers - one applying power adaptation- evaluate each frequency and CR pair considering spectrum switching, transmission, and idling times. As CRs are expected to operate in a wide spectrum, channel switching has to be considered in CRNs since it increases energy consumption and leaves less time for transmission. Simulations demonstrate that our proposals attain significantly higher energy efficiency without sacrificing throughput under sufficient spectrum resources while achieving similar performance for low spectrum resources.