Combination of a geolocation database access with infrastructure sensing in TV bands

This paper describes the implementation and the technical specifications of a geolocation database assisted by a spectrum-monitoring outdoor network. The geolocation database is populated according to Electronic Communications Committee (ECC) report 186 methodology. The application programming interface (API) between the sensor network and the geolocation database implements an effective and secure connection to successfully gather sensing data and sends it to the geolocation database for post-processing. On the other hand, the testbed allows authorized TV white space devices to gain access to the services of the geolocation database, according to a draft implementation of Internet Engineering Task Force (IETF) Protocol to Access White Space (PAWS) Two experimental methodologies are available with the testbed: one focused on coexistence studies with commercial wireless microphones, when the testbed is used for sensing only, and another for demonstration purposes, when the testbed is also used to emulate wireless microphone signals. Overall, this hybrid approach is a promising solution for the effective use of TV white spaces and for the coexistence with digital TV broadcast signals, or dynamic incumbent systems, such as unregistered wireless microphones

WhiteHaul: an efficient spectrum aggregation system for low-cost and high capacity backhaul over white spaces

We address the challenge of backhaul connectivity for rural and developing regions, which is essential for universal fixed/mobile Internet access. To this end, we propose to exploit the TV white space (TVWS) spectrum for its attractive properties: low cost, abundance in under-served regions and favorable propagation characteristics. Specifically, we propose a system called WhiteHaul for the efficient aggregation of the TVWS spectrum tailored for the backhaul use case. At the core of WhiteHaul are two key innovations: (i) a TVWS conversion substrate that can efficiently handle multiple non-contiguous chunks of TVWS spectrum using multiple low cost 802.11n/ac cards but with a single antenna; (ii) novel use of MPTCP as a link-level tunnel abstraction and its use for efficiently aggregating multiple chunks of the TVWS spectrum via a novel uncoupled, cross-layer congestion control algorithm. Through extensive evaluations using a prototype implementation of WhiteHaul, we show that: (a) WhiteHaul can aggregate almost the whole of TV band with 3 interfaces and achieve nearly 600Mbps TCP throughput; (b) the WhiteHaul MPTCP congestion control algorithm provides an order of magnitude improvement over state of the art algorithms for typical TVWS backhaul links. We also present additional measurement and simulation based results to evaluate other aspects of the WhiteHaul design

Reinforcement Learning-Based Television White Space Database

Television white spaces (TVWSs) refer to the unused part of the spectrum under the very high frequency (VHF) and ultra-high frequency (UHF) bands. TVWS are frequencies under licenced primary users (PUs) that are not being used and are available for secondary users (SUs). There are several ways of implementing TVWS in communications, one of which is the use of TVWS database (TVWSDB). The primary purpose of TVWSDB is to protect PUs from interference with SUs. There are several geolocation databases available for this purpose. However, it is unclear if those databases have the prediction feature that gives TVWSDB the capability of decreasing the number of inquiries from SUs. With this in mind, the authors present a reinforcement learning-based TVWSDB. Reinforcement learning (RL) is a machine learning technique that focuses on what has been done based on mapping situations to actions to obtain the highest reward. The learning process was conducted by trying out the actions to gain the reward instead of being told what to do. The actions may directly affect the rewards and future rewards. Based on the results, this algorithm effectively searched the most optimal channel for the SUs in query with the minimum search duration. This paper presents the advantage of using a machine learning approach in TVWSDB with an accurate and faster-searching capability for the available TVWS channels intended for SUs

A Hierarchical Spectrum Access Scheme for TV White Space Coexistence in Hetergeneous Networks

Among current techniques for dynamic access to television (TV) white space (TVWS), geolocation database-based access provides a promising performance in protecting the TV-band incumbents from interference that cannot be efficiently achieved in other license-exempt models. However, in heterogeneous wireless networks, most portable devices do not have such access and may cause interference to TV incumbents. We propose a hierarchical model for spectrum sharing in TVWS that includes a wide range of fixed and portable devices. In the first tier, the TV broadcaster can lease the spectrum bands to local fixed users based on a soft license agreement. The fixed users are allowed to share access to this spectrum with some mobile users in their proximity in exchange for cooperative relaying. We consider a practical scenario, where only partial channel state information (CSI) is available at the users\u27 transmitters, and we propose a robust algorithm against such uncertainties in CSI values. We also propose a reputation-based relay selection mechanism to identify selfish portable users. The proposed spectrum sharing framework can provide a practical model for TVWS-coexistence that prevents undesired interference to the incumbents while restricting interference among the unlicensed devices. The simulation results show the enhancement of fixed users\u27 rate compared with alternative relay selection methods

TVWS policies to enable efficient spectrum sharing

The transition from analogue to the Digital Terrestrial Television (DTV) in Europe is planned to be completed by the end of the year 2012. The DTV spectrum allocation is such that there are a number of TV channels which cannot be used for additional high power broadcast transmitters due to mutual interference and hence are left unused within a given geographical location, i.e. the TV channels are geographically interleaved. The use of geographically interleaved spectrum provides for the so-called TV white spaces (TVWS) an opportunity for deploying new wireless services. The main objective of this paper is to present the spectrum policies that are suitable for TVWS at European level, identified within the COGEU project. The COGEU project aims the efficient exploitation of the geographical interleaved spectrum (TVWS). COGEU is an ICT collaborative project supported by the European Commission within the 7th Framework Programme. Nine partners from seven EU countries representing academia, research institutes and industry are involved in the project. The COGEU project is a composite of technical, business, and regulatory/policy domains, with the objective of taking advantage of the TV digital switchover by developing cognitive radio systems that leverage the favorable propagation characteristics of the UHF broadcast spectrum through the introduction and promotion of real-time secondary spectrum trading and the creation of new spectrum commons regimes. COGEU will also define new methodologies for compliance testing and certification of TVWS equipment to ensure non-interference coexistence with the DVB-T European standard. The innovation brought by COGEU is the combination of cognitive access to TV white spaces with secondary spectrum trading mechanisms.telecommunications,spectrum management,secondary spectrum market,regulation,TV white spaces,cognitive radio

LOCALIZATION AND TRACKING OF 4G COGNITIVE RADIO

The 4G network provides a significant improvement in performance, but service providers are still faced with the annual increase in usage of cell phones and wireless devices. Spectrum efficiency is the most prominent issue in handling the high number of users. The cognitive radio is capable of changing its transmission and/or reception parameters according to the demands of the network. In the 4G network, the cognitive radio is seen as a solution to spectrum efficiency. With the high number of users, it also means that there is a need to effectively localize and track the 4G cognitive radio (4G-CR) signal for various purposes such as urban environment warfare, national security, surveillance, intelligence, and emergency rescue. The localization errors from previous proposed methods of time-difference-of-arrival (TDOA) measurements were analyzed in this thesis. The localization errors obtained are close to the differential-distance errors derived from the TDOA measurement algorithms. In addition, the localization of 4G-CR requires an adaptive tracking method, which is also discussed in this thesis.Civilian, ST Electronics, SingaporeApproved for public release; distribution is unlimited

PSO AND SVD BASED ENHANCED SIGNAL DETECTION FOR COGNITIVE RADIO SYSTEM

Spectrum sensing is an essential problem in cognitive radio communication system. This paper presents covariance based spectrum sensing on the test bed if cognitive radio system. A series of tests show that the detection performance of Covariance Based spectrum sensing technique is not liable to be affected by the noise uncertainty in practical application and meets the need of the system primly. Furthermore, the performances of detection are also verified with different kinds of source signals. Simulations are carried out on MATLAB2010a and system performance is measured based on probability of detection vs. SNR, Probability of false alarm, sensing time and modulation techniques respectively