TV White Space Research Articles

Regulations and Standards for TV White Space

Regulations and Standards for TV White Space

Performance measurements of communication access technologies and improved cognitive radio model for smart grid communication

AbstractTraditional power grids have unidirectional power flow and often information transfer, this limits their capacity for scalability, efficiency, and renewable energy integration. Smart grids (SGs) are being developed as more intelligent power grids with bidirectional power flow and information interchange. A reliable communication network is required in order to realize some important SG features, such as renewable energy integration, distributed energy resources, scalability, self‐healing and efficient holistic monitoring, and control capability. However, this communication network needs to comply with critical requirements. Cognitive radio (CR) has been projected as a possible solution to common problems in conventional wireless systems such as spectrum scarcity and interference. The CR accesses a greater range of spectra via dynamic spectrum access capability. This paper focuses on the evaluation of communication access technologies performance measurements and improved CR model for SG communications. This paper employs the National Institute of Standard framework for SG interoperability, the low power wide area network (LPWAN), multihoming, and a CR device such as TV white space band devices (TVBDs). The results from simulation analysis show that the performance of TVBDs outperforms the legacy Wi‐Fi in terms of latency; also, LPWA devices, such as LTE Cat1/LTE‐M devices, outperform the legacy cellular, such as CDMA 1x‐EVDO, in terms of latency and throughput. In addition, the improved CR model, which involves a proposed channel fragmentation strategy–based Alamouti scheme, outperforms legacy CR in terms of blocking probability and throughput in the harsh SG environment.

TV White Space Spectrum Analysis Based on Machine Learning

Exploration of TV white space (TVWS) is a promising solution to mitigate the spectrum shortage and provide opportunities for new applications. In this paper, we present a detailed analysis of spectrum utilisation over TVWS at different locations in London. Both short-term and long-term outdoor measurement campaigns are conducted over large scales to better understand the spectrum features and variations across multiple locations and time periods. Different from most fixed-location-only measurements, we also drive along the main streets of London with a portable moving node to measure the on-route spectrum density along with the corresponding geographical information, which allows us to study the features and variations of spectrum use through a continuous space. To better analyse the dynamic spectrum utilisation, a machine learning based analysis algorithm is developed over the real-world measurements. This approach allows us to characterise the similarity and variability in spectrum usage within and among different channels, locations, and time instances, which is critical for the secondary system deployment to efficiently exploit the white space.

An Efficient Resource Allocation Scheme for Applications in LR-WPANs Based on a Stable Matching With Externalities Approach

This paper deals with an efficient resource allocation algorithm for Wide-Area Low Rate Wireless Personal Area Networks (LR-WPANs), based on the IEEE 802.15.4 m standard. The proposed scheme aims at lowering the spectrum congestion problems and optimizing performance in terms of data packets dropping probability for all the active clusters of end-devices. The algorithm realizes a many-to-one mapping between the sets of LR-WPANs and available access bands (i.e., TV white space bands). It is based on a matching game with externalities and involves two-side preferences, i.e., clusters over bands and bands over clusters, respectively. The procedure provides high resource reuse, adaptation to changes of system conditions, and improvements on quality of service. Furthermore, a post-matching procedure is also discussed to ensure stability of the provided many-to-one matching. Finally, the good behavior of the matching approach is validated by providing performance comparisons with alternative schemes based on the random assignment, the Brelaz graph coloring algorithm applied in a modified form, and potential game strategy.

Operating white space devices in the DTV service area

Abstract White space devices (WSDs) that operate in the underutilized TV bands (TV white space) must not interfere with the incumbent digital TV (DTV) reception. We identify the conditions for harmonious coexistence between WSD and three different DTV services: Advanced Television Systems Committee, Integrated Services Digital Broadcasting - Terrestrial, and Digital Video Broadcasting - Terrestrial. We find that a WSD can operate within all three regions provided that (1) its radiated power is smaller than 13 dBm, (2) it keeps a minimum distance of 50 m from a DTV receiver, (3) it operates in the adjacent channels except the closest one.

A Pricing-Based Rate Allocation Game in TVWS Backhaul and Access Link for Rural Broadband

The traditional cellular technology is not profitable to serve the sparsely populated and clustered remote rural areas because of huge network set-up cost and lesser return from low density of rural population. To provide broadband service in those remote rural areas, in this paper, we consider a TV white space (TVWS)-based hierarchical network architecture where sparsely located clustered rural pieces of user equipment (UEs) are connected to far-off central base station (CBS) via intermediate TVWS nodes, known as the pieces of customer premises equipment (CPEs) through TVWS link. The CBS has direct broadband connectivity to the Internet through optical fiber backhaul. In such a network architecture, we adopt a two-stage market model among UEs, CPEs, CBS, and propose a pricing-based Stackelberg game to distribute the total available data rate at CBS among CPEs and then to the UE. Extensive simulations have been carried out to study the data-rate distribution, and the behavior of utilities of CPE, CBS, and UE with variation of different parameters for a particular network scenario. The study of the outcome suggests that using this simple price exchange mechanism, it is possible, based on each UE's willingness-to-pay and the total available data rate, to distribute data rate optimally among the UEs where each of the network entities behaves selfishly.

Joint bandwidth and power allocation for multiple services in TV white space

As the bandwidth resource in TV white space (TVWS) is permitted to be used for the secondary users, multiple secondary networks coexisting in the same geographical area can provide multiple services without interfering with the primary service, such as the TV broadcasting. To satisfy the minimum rate requirements and maximise the sum rate of the multiple services, the problem of resource allocation can be modelled as a mixed integer non-linear programming (MINLP). According to this model, the joint bandwidth and power allocation (JBPA) method is proposed to solve the resource allocation for multiple services. The JBPA method is sub-optimal, which can approximate the performance of the optimal two-step exhaustive search (TSES) method very well, especially when the number of services is larger than the number of idle channels. Compared with TSES, the JBPA method decreases the complexity from exponential level to polynomial level. Besides, compared with one channel occupied by single service, the JBPA can serve more services and provide stable performance when the number of services varies dynamically. Compared with the algorithm random bandwidth allocation, the JBPA can approximate the optimal performance provided by TSES better with the time complexity of the same order.

Using an IoT Platform for Trustworthy D2D Communications in a Real Indoor Environment

The constantly increasing need for data exchange among various types of devices, mobile and fixed, is one of the main characteristics of technological developments in the last few years. Within this context, the possibility to deliver content to more devices into the same domestic environment is very interesting for both consumers and service providers. The main hurdle for device to device (D2D) communications is the available bandwidth and, implicitly, the used radio technology and frequency range. From this point of view, so called TV white spaces (TVWSs) are an ideal candidate for short range communications, but have the problem of interference management with the licensed services already operating there. This problem can be alleviated by using cooperative, distributed spectrum sensing techniques. This paper proposes an innovative approach for D2D communications in a real indoor environment, based on a social Internet of Things (SIoT) architecture able to involve all participating objects in a twofold procedure, gathering both spectrum sensing and quality of service data, and weighting the received information using a novel trustworthiness algorithm. The algorithm, together with the entire SIoT architecture, has been implemented and extensively tested in a real indoor environment.

Shades of White: Impacts of Population Dynamics and TV Viewership on Available TV Spectrum

Current regulations leave a few television (TV) white spaces in populated urban areas where spectrum shortage is mostly experienced. As TV set feedback becomes essential in the next generation terrestrial TV standard, an opportunistic TV spectrum sharing based on TV receiver activity information and transmit power control is proposed to exploit the underutilized active TV channels. Based on investigation of the spatial–spectral–temporal characteristics of TV receiver activities, analytical models are developed to capture the spatio-temporal distributions of available spectrum and corresponding capacity. The influence of multiple factors, such as feedback delay, spectrum handover overhead, ranking order, and distribution of TV channel popularity are discussed and modeled. The proposed power control mechanism is verified through experiments at representative campus and residential environments. Empirical data-based simulations and geographic analyses are conducted to evaluate the developed models and further profile the spectrum opportunities within a cell, across New York city (NYC) and other 273 cities in the United States. In NYC, the proposed solution provides a $3.8$ – $11.7$ -fold increase of average spectrum availability, and $2.5$ – $6.6$ -fold increase of capacity from current regulations. By investigating the feasibility and prospects of this approach, this paper intends to motivate further discussions in policy, business, and privacy aspects to reach its significant potential.

Joint power and channel allocation scheme for IEEE 802.11af based smart grid communication network

To reap the full potentials of Smart grid (SG), a reliable, resourceful, efficient and cost-effective communication network is inevitable. The crucial need to transmit a significant amount of smart grid application data in an efficient spectral manner makes cognitive radio (CR) technology most suitable for SG environment. Identically, TV white space (TVWS) is the most expectant candidate for CR based smart grid communication network (CRSGCN). In this paper, we are investigating the problem of joint power and channel allocation (JPCA), which is among the most important and widely explored area in cognitive radio domain. We first model a typical scenario in a neighborhood area network (NAN) communication using IEEE 802.11af via open loop regulatory framework for TVWS. A mathematical model is formulated to jointly address power and channel allocation considering practical constraints for two real-world scenarios of fairness-based and priority-based allocation. Next, an efficient power allocation (PA) scheme is presented, meeting quality-of-service (QoS) requirements, followed by channel allocation (CA) scheme based on cuckoo search algorithm (CSA). The performance of the proposed solutions is analyzed using exhaustive simulations to optimize power consumption, fairness and user rewards. The presented results in the form of graph and numerical comparisons indicate the effectiveness of our allocation algorithm to achieve the desired objectives.

Computation Offloading and Resource Allocation in Vehicular Networks Based on Dual-Side Cost Minimization

The proliferation of smart vehicular terminals (VTs) and their resource hungry applications impose serious challenges to the processing capabilities of VTs and the delivery of vehicular services. Mobile Edge Computing (MEC) offers a promising paradigm to solve this problem by offloading VT applications to proximal MEC servers, while TV white space (TVWS) bands can be used to supplement the bandwidth for computation offloading. In this paper, we consider a cognitive vehicular network that uses the TVWS band, and formulate a dual-side optimization problem, to minimize the cost of VTs and that of the MEC server at the same time. Specifically, the dual-side cost minimization is achieved by jointly optimizing the offloading decision and local CPU frequency on the VT side, and the radio resource allocation and server provisioning on the server side, while guaranteeing network stability. Based on Lyapunov optimization, we design an algorithm called DDORV to tackle the joint optimization problem, where only current system states, such as channel states and traffic arrivals, are needed. The closed-form solution to the VT-side problem is obtained easily by derivation and comparing two values. For MEC server side optimization, we first obtain server provisioning independently, and then devise a continuous relaxation and Lagrangian dual decomposition based iterative algorithm for joint radio resource and power allocation. Simulation results demonstrate that DDORV converges fast, can balance the cost-delay tradeoff flexibly, and can obtain more performance gains in cost reduction as compared with existing schemes.

A Comprehensive Survey on Spectrum Sensing in Cognitive Radio Networks: Recent Advances, New Challenges, and Future Research Directions.

Cognitive radio technology has the potential to address the shortage of available radio spectrum by enabling dynamic spectrum access. Since its introduction, researchers have been working on enabling this innovative technology in managing the radio spectrum. As a result, this research field has been progressing at a rapid pace and significant advances have been made. To help researchers stay abreast of these advances, surveys and tutorial papers are strongly needed. Therefore, in this paper, we aimed to provide an in-depth survey on the most recent advances in spectrum sensing, covering its development from its inception to its current state and beyond. In addition, we highlight the efficiency and limitations of both narrowband and wideband spectrum sensing techniques as well as the challenges involved in their implementation. TV white spaces are also discussed in this paper as the first real application of cognitive radio. Last but by no means least, we discuss future research directions. This survey paper was designed in a way to help new researchers in the field to become familiar with the concepts of spectrum sensing, compressive sensing, and machine learning, all of which are the enabling technologies of the future networks, yet to help researchers further improve the efficiently of spectrum sensing.

Vehicular Communications Over TV White Spaces in the Presence of Secondary Users

The lack of available spectrum for wireless communications is a threat to the successful deployment of applications designed for intelligent transportation systems (ITSs). The ITS services should be available to a high number of road users and have a fast response time. The interworking between radio access networks is one way to increase spectrum availability. In particular, the joint operation of the dedicated short-range communication (DSRC) technology and TV white spaces (TVWS) has been proposed to increase the dissemination distance for safety messages in vehicular networking. However, previous works have often assumed that the only restriction on the opportunistic access of TVWS is the presence of a TV transmitter (i.e., the primary user). Other secondary users, such as the popular White-Fi networks to be deployed in TV bands, are omitted from the analysis of opportunistic channel access over TVWS. This is despite several proposals in the literature that use secondary networks for purposes other than vehicular networking over TVWS. In this paper, we analyze the opportunistic use of TVWS when other fixed users, such as White-Fi networks, are present. We estimate channel access opportunities and introduce a new metric, the channel availability for opportunistic vehicular access (CAFOVA), which relates the channel occupancy of the White-Fi network, the speed of the vehicle, and the channel verification distance. The results show that there are opportunities for vehicular access even when a White-Fi network occupies the TVWS. Vehicles may use these opportunities for transmission, instead of spending time looking for a new available TVWS and establishing a new link with another vehicle. Therefore, even when a White-Fi network occupies the same TVWS, it may be possible to exploit dynamic spectrum access to extend the available spectrum for vehicular communications.

A Survey of Resource Allocation in TV White Space Networks

A Survey of Resource Allocation in TV White Space Networks

Cognitive radio-based solutions for spectrum scarcity in Palestine

In this paper, we study the feasibility of implementing cognitive radio (CR) secondary network either on the primary Palestinian second generation (2G) global system for mobile communication (GSM) network or on the ultra-high frequency (UHF) television (TV) band. Particularly, we propose solutions for spectrum scarcity based on the three CR paradigms, namely: interweave CR, underlay CR, and overlay CR. In the first solution, an interweave CR system is suggested to efficiently utilise the so-called TV white spaces in the UHF TV band allocated for Palestine. In the second solution, an underlay CR system based on code division multiple access (CDMA) is introduced to underlay the primary GSM system. In the third solution, an overlay CR system is proposed based on orthogonal frequency division multiplexing (OFDM) to share the same spectrum band with the primary GSM system. It is confirmed that the proposed solutions can solve the spectrum scarcity and limit the interference levels, and consequently improve system capacity.

A Cyber-Enabled Mission-Critical System for Post-Flood Response: Exploiting TV White Space as Network Backhaul Links

A crucial problem in post-flood recovery actions is the ability to rapidly establish communication and collaboration among rescuers to conduct timely and effective search and rescue (SAR) mission given disrupted telecommunication infrastructure to support the service. Aimed at providing such proximity service (ProSe) for mission-critical data exchange in the post-flood environment, the majority of existing solutions rely heavily upon ad-hoc networking approaches, which suffer from restricted communication range and the limited scope of interaction. As an effort to broaden the ProSe coverage and expand integrated global-local information exchange in the post-flood SAR activities, this paper proposes a novel network architecture in the form of a cyber-enabled mission-critical system (CEMCS) for acquiring and communicating post-flood emergency data by exploiting TV white space spectrum as network backhaul links. The primary method of developing the proposed system builds upon a layered architecture of wireless local, regional and wide-area communications, and incorporates collaborative network components among these layers. The desirable functionalities of CEMCS are showcased through formulation and the development of an efficient global search strategy exploiting a wide range of collaboration among network agents. The simulation results demonstrate the capability of CEMCS to provide ProSe in the post-flood scenarios as reflected by reliable network performance (e.g., packet delivery ratio nearing 80%–90%) and the optimality of efficient search algorithm.

Optimizing City-Wide White-Fi Networks in TV White Spaces

White-Fi refers to WiFi deployed in the TV white spaces. Unlike its ISM band counterparts, White-Fi must obey requirements that protect TV reception. As a result, optimization of citywide White-Fi networks faces the challenges of heterogeneous channel availability and link quality, over location. The former is because, at any location, channels in use by TV networks are not available for use by White-Fi. The latter is because the link quality achievable at a White-Fi receiver is determined by not only its link gain to its transmitter but also by its link gains to TV transmitters and its transmitter’s link gains to TV receivers. In this paper, we model the medium access control throughput of a White-Fi network. We propose heuristic algorithms to optimize the throughput, given the described heterogeneity. The algorithms assign power, access probability, and channels to nodes in the network, under the constraint that reception at TV receivers is not compromised. We evaluate the efficacy of our approach over example city-wide White-Fi networks deployed over Denver and Columbus (respectively, low and high channel availability) in the USA, and compare with assignments cognizant of heterogeneity to a lesser degree, for example, akin to FCC regulations.

Enhanced 5G Cognitive Radio Networks Based on Spectrum Sharing and Spectrum Aggregation

In this paper, new enhanced cognitive radio networks (E-CRNs) based on spectrum sharing (SS) and spectrum aggregation (SA) are proposed for fifth generation (5G) wireless networks. The E-CRNs jointly exploit the licensed spectrum shared with the primary user (PU) networks and the unlicensed spectrum aggregated from the industrial, scientific, and medical bands. The PU networks include TV systems in TV white space and different incumbent systems in the long term evolution time division duplexing bands. The harmful interference from the E-CRNs to the PU networks are delicately controlled. Furthermore, the coexistence between the E-CRNs and other unlicensed systems, such as WiFi, is studied. The E-CRNs framework including dynamic spectrum management (DSM) is designed for the key parameters of licensed SS and unlicensed SA. The essential tradeoff between sharing efficiency and aggregation efficiency for the E-CRNs is discussed. Based on this tradeoff, a spectrum lean-management scheme is proposed to fulfill the DSM. Moreover, a water-filling algorithm is designed to dynamically access the available spectrum. Numerical results demonstrate that the proposed E-CRNs can significantly improve the system performance in terms of data rate, outage probability, and spectrum efficiency. In particular, the E-CRNs framework provides a spectrum usage prototype for 5G wireless communication networks.

Unleashing the Power of Multi-Server PIR for Enabling Private Access to Spectrum Databases

The emergence of IoT is driving rapid growth in the use of wireless devices around the world. In addition, 5G, through its support for large numbers of devices, is expected to unleash the full potential of IoT globally. The growing number of wireless devices and the massive traffic stemming from the emergence of these technologies will result in a dramatic increase in the demand for spectrum resources. Dynamic spectrum sharing, enabled through cognitive radio network technology, emerges as a key solution for coping with these rising spectrum demands. One important approach that is currently being adopted as a potential solution for promoting dynamic spectrum sharing is the deployment and reliance on white space geo-location spectrum databases for locating spectrum availability in the TV white space. Despite the great benefits these databases offer in terms of their ability to help locate spectrum opportunities for secondary usage, they suffer from location privacy issues, as users need to reveal their location in the process of querying these databases for spectrum availability. Knowing that their whereabouts may be exposed, users can be discouraged from querying the databases, thereby hindering the adoption and deployment of this technology in future generation networks. In this article, we focus on the location privacy problem in database-driven dynamic spectrum access. Specifically, we present and compare key approaches that aim to protect the location information of secondary users in database-driven spectrum sharing and discuss some key research challenges that remain unaddressed.

Channel accessing and handoff mechanisms in TV white spaces based on channel sensing and database information

Opportunistic channel accessing and handoff mechanisms are crucial for the successful implementation of cognitive radio networks that depend on vacant channel frequencies of TV white spaces and other primary users. In this work, two such mechanisms that enable quick accessing of vacant channels and cause less interference to primary users are proposed. In these methods, combination of database information and local sensing of channels is used, to know about available vacant channels. If the primary user of incumbent channel returns, the secondary user moves to another vacant channel that is found to be free after scanning. Information from database can be used to speed up the process by limiting the scanning to few probable channels, instead of searching for all. The results show that these methods offer quick handoff of secondary users and cause less interference to primary users.