In this article, we assess the viability of underlay sensor networks in frequencies used by an incumbent digital TV broadcasting system, that is, in the so-called TV grayspaces (TVGS). Grayspace operations are particularly interesting when other unlicensed bands are overcrowded, for example, due to high-volume WiFi operations. We simulate the operational characteristics of the recent IEEE 802.15.4m standard for low-rate wireless personal area networks to evaluate the performance degradation of an incumbent Digital Video Broadcasting - Terrestrial (DVB-T) system if a secondary network of low-power low-rate devices are co-deployed in the same frequency bands. Our results show that short sensor messages will not disrupt the DVB-T service due to the existing error-correction capabilities. Furthermore, if sufficient separation distances to primary transmitters are maintained, transmit powers are sufficient to achieve reasonable connectivity levels of the secondary network. In order to obtain realistic figures on the predicted feasibility of grayspace sensor networks, we study the deployment constraints of a hypothetical secondary network co-located with the TV broadcasting network of Germany. Our analysis shows that if we aim to support a minimum sensor-sensor distance, no universal coverage can be maintained in this country. While our quantitative results are specific to Germany, we deem them indicative for the expected results also in other potential deployments. We found that while a secondary wireless sensor network in TVGS is technically possible, the necessary constraints on operational parameters and service levels for TVGS co-existence will significantly limit its practical viability.

Crosstalk between physically co-located lines is a pressing issue in VDSL2 access networks. In order to enhance the crosstalk mitigation capabilities of the latest extension to VDSL2, vectoring G.993.5, full control over all lines within the same cable binder is required. However, this is not always possible in practical deployments due to regulatory, structural, or late technology adoption constraints. In these cases a technique to minimize interference from non-controlled lines, known as binder management, aims at rearranging the line configuration within each binder. In this work, we quantify the advantages of binder management in a partially controlled setup. We initially establish a model of a commonly used 50-pair cable binder and provide its far-end crosstalk (FEXT) characterization. We then carry out an extensive simulation study for various degrees of control over the lines and realistic line length distributions to yield tangible metrics on vectoring performance for downstream transmission. Our results show that binder management is of limited use in partially controlled systems. Consequently, we provide an additional comparison study to help DSL providers to evaluate the remaining gains of upgrading to VDSL2-vectoring in such scenarios for different levels of dominance in the cable binder.

Software-defined networking provides new tools and offers more opportunities to actively manage large-scale network setups during runtime. However, controlling such installations in a unified and adaptive manner is inherently complex due to the remarkable diversity of management tools. In this paper we propose ULLA-X, a novel middleware that unifies network monitoring and on-demand reconfiguration through a universal network programming language. We introduce ULLA-X architecture and usage concept, which aims at bridging sophisticated network planning with practical network maintenance tools, resembling an “autonomic nervous system” for communication networks. Through its modular design, ULLA-X can be easily integrated into current network setups. While this paper is focused on introducing the ULLA-X concept and framework, we also present initial results from a prototype implementation for National Instruments wireless networked devices.

Recent rulings by US and UK regulators allowing access to unused portions of TV spectrum have elicited high hopes for the practical value of these TV whitespaces (TVWS) for secondary exploitation. However, this optimism has been largely fueled by rather simple early studies, which do not consider all the system aspects in sufficient detail; the few early experimental works reported are proprietary and consider only a small number of nodes, whereas the existing more sophisticated theoretical studies focus on singular aspects of secondary spectrum access in isolation from the overall system interactions. In this paper we study quantitatively the deployment of secondary networks in TVWS by considering two archetypal candidate systems: LTE-like cellular and Wi-Fi-like networks. We develop a systematic framework for the performance evaluation of secondary networks, which we then use to obtain realistic estimates of the performance of our example systems. The secondary network performance assessment methodology demonstrated in this paper can be directly applied for other regions and systems. Our work explicitly takes into account limitations arising from aggregate interference, user density, and specific secondary transceiver characteristics. We argue that a systematic analysis, jointly considering all of these aspects, is key for obtaining realistic and robust results on the estimated value of whitespace spectrum. Our detailed system-level approach reveals a much more conservative picture of the realistic benefit of TVWS deployments than what has been commonly assumed thus far. We find that cellular TVWS networks have limited capabilities, but that a macro-cellular-only network may be a viable option for traffic offloading. Our results also show that Wi-Fi-like secondary deployments in TVWS, although increasing coverage range, lead to increased congestion, which limits the system capacity.

In this paper we analyze the potential use of underutilized TV frequencies to enable high-speed hotspots and data offloading in trains. We propose a system where the hotspots connect via TV frequencies to base stations that are located at the train stations. Using data from the railway network of Germany and detailed spectrum availability information we carry out a performance analysis for various realistic scenarios and configurations of a secondary system that relies on LTE technologies. Our analysis shows that sustainable data rates beyond 20 Mbps per train can be achieved in all considered scenarios, and that a proposed modified spectrum policy for authorized shared access of the secondary system will yield near-universal coverage. The results show that it would be possible to provide cost-efficient broadband connectivity for a national high-speed train network by using unused TV frequencies.

A better understanding of the spatial structure of existing opportunistic wireless network deployments will offer new insights for future deployments, e.g. dense femtocell networks. In this paper we present a performance analysis for three different localization algorithms that support such efforts by finding the location of IEEE 802.11 Wi-Fi access points (APs) from distributed signal strength measurements. These algorithms extend prior works on omnidirectional single-point measurements and includes angular information into the estimation process. Using a custom-made measurement setup, we have collected data for typical indoor and outdoor scenarios which are likely to be encountered in large measurement campaigns. We quantify and reason on the localization error for each scenario and algorithm, and propose a weight spread estimate for determining the robustness of the localization approaches. Through variations in the used sample data set we further discuss relevant observations on the stability of the different algorithmic estimation approaches. Our results show that overall propagation-centric algorithms perform best, but that algorithms that build a stochastic model of angular signal strength distribution are more robust if only few measurements are available.

With an increasing demand for monitoring energy consumption at granularity levels down to single household appliances, it is necessary to develop new means to collect sensor measurements in a robust and cost-efficient manner. The smart grid paradigm foresees using wireless links for data transfer, albeit no dedicated spectrum bands have been designated for this purpose. In this paper we study the feasibility of opportunistic spectrum access for smart grids, and focus on underlay spectrum sharing over occupied TV channels. These frequency bands, which are commonly denoted as TV gray spaces, provide superior propagation characteristics, but are locally used by high-power (mostly DTV) broadcasting transmitters. For selected reference geometries of intra-meter and meter-to-operator communications, we study the smart meter performance (in terms of achievable throughput and transmission range), and the necessary power limits. We compare our results from a small-scale measurement campaigns against existing wireless technologies for low-power communications in other adjacent bands. Our results show that wall shielding and fading in indoor to outdoor propagation channels sufficiently protects the primary system from the interference introduced by gray space meter-to-meter communications, but that the required transmit powers to send operations data from indoor meters to outdoor collection point severely limit the applicability of TV gray spaces for such network topologies.

An understanding of the underlying spatial structure of user-deployed wireless networks is invaluable for the design and optimization of opportunistic small-cell technologies in emerging multi-tier architectures. IEEE 802.11 Wi-Fi networks provide a real-world example of such a large-scale random network structure. In this paper we report on a high-resolution measurement survey of Wi-Fi deployments in Germany as a step towards deriving more sophisticated spatial models for transmitter distributions in emerging small-cell networks, which are the core of offloading strategies for future wireless Internet. Using a custom setup, our measurement campaign covered a range of urbanization and land use scenarios representative of Wi-Fi deployments in developed countries. Our data indicates a 14-fold increase in Wi-Fi density in urban residential areas over the last decade, consistent with increased broadband penetration. This supports our hypothesis that household density has become a strong predictor of access point (AP) density. We infer AP locations using a novel localization technique suitable for large measurement campaigns using off-the-shelf equipment. From this data, we derive pertinent spatial statistics to characterize the topologies of opportunistic networks. We derive nearest-neighbour distributions showing that realistic inter-neighbour distances are higher than predicted by a homogeneous Poisson Point Process, underlining the need for more refined spatial models than the random node location models which are currently prevalent. We also derive the two-pair correlation functions for the AP locations, showing that AP clustering is apparent over a large range of distances in our data set, which has implications for routing and interference mitigation.

The prospect of increasing wireless capacity via secondary access to spatio-temporally underutilized chunks of spectrum, so-called whitespaces, has been proposed as a central aspect of emerging radio systems in response to the imminent spectrum scarcity problem. In this demonstration we present a novel software tool that helps researchers, industry, and regulators in assessing the feasibility and value of secondary spectrum access beyond simple whitespace availability calculation. Whereas existing software applications merely provide visualization of estimated secondary spectrum over a geographic area, our tool uniquely enables a holistic evaluation of the realistic potential of whitespace technologies, by modelling the performance of entire secondary systems in the envisioned eco-system of dynamic spectrum access policy and technology. Our tool provides a unified and flexible software framework and assessment methodology to conduct such studies, and is composed of an extensive primary spectrum usage database, a graphical interface for user interaction, and an interface to an extensible MATLAB backend for numerical calculations. We showcase the deployment scenarios of cellular and Wi-Fi-like secondary networks in TVWS (TV whitespaces). We also compare the impact of employing FCC-type of regulatory rules (with a fixed power/no-talk distance configuration) against European WG-SE43 regulatory proposals (with probabilistic access and power control). The case studies we will demonstrate are based on real network configuration data of European and US TV networks.

Wireless network deployments are becoming increasingly complex in order to cope with the exponential growth in mobile data traffic. Multi-tier technologies capable of supporting spatially dense networks enable high data rates, but require timely and accurate models of the radio environment, particularly for scenarios that incorporate dynamic access to spectrum. However, network planners, algorithm designers, and policy makers are often forced to rely on a small set of radio propagation scenarios, often assuming fixed receiver antenna heights (RAHs). In this paper we show that the RAH in fact plays a key role not only in terms of reception quality but also in determining the interference originating from other transmitters. Our extensive simulation studies show a large variability in key performance metrics of realistic wireless network topologies as RAH is varied, which are not captured through the current practice of selecting few effectively two-dimensional scenarios and drawing general conclusions from them. These results underline the importance of adopting more realistic assumptions on RAH for design, assessment, and policy making for wireless communication systems, and the need for new propagation models valid for a wider range of RAH values than models currently in use.

In this paper we analyze the prospects of deploying a cellular network in the TV whitespaces. We study the challenges of planning for a large-scale transmitter network that is constrained by an interference-to-primary regulation. For this purpose we derive a novel methodology to maximize the downlink capacity at the cell edge of base stations that makes use of a heuristic algorithm for per-channel power allocation. A discretized formulation as a multiple-choice nested knapsack problem is presented and scenario-specific algorithmic improvements are discussed. The methodology is assessed for the case of Germany which, due to the specific challenges of the geographic region, can be considered indicative for similar deployments in other countries.

A growing demand for bandwidth in wireless data networks has motivated policy makers to consider opening underused frequencies, e.g. in the TV broadcasting bands, to opportunistic secondary access. To support secondary network operations in these TV whitespaces (TVWS), centralized databases are envisioned that employ radio propagation models to derive the spectrum usage of the primary system. Precise estimation of the actual spectrum usage is highly important in this scenario, because maladjusted models can cause primary outage or hamper secondary capacity. The requirements for accurate propagation estimation have hence further increased. Using the example of a single TV transmitter, we study in this poster the prospects of maximum likelihood estimation for generic power law propagation models. Transmitter characteristics are considered known, but environment-specific parameters of the model are derived through fitting measurement results, obtained, e.g., through drive tests. We derive for the case of uncorrelated shadow fading the error distributions and their parameters for two parameters, namely pathloss coefficient and shadow variance. Our results are applicable to other large-scale scenarios where precise signal strength estimation is required. They can help to minimize the number of required measurements and to determine necessary protection policies.

Future wireless networks will be able to exploit unused spectrum whitespaces in the currently underutilized terrestrial TV bands. In order to protect incumbent broadcasting systems from extensive interference from whitespace devices, accurate signal power estimations are needed. Reliable and robust models for predicting the radio propagation in those bands are thus a key enabler of secondary operations. Depending on their level of abstraction and the complexity of the environment, these models can perform quite well, but they require a significant amount of auxiliary information and fine-tuning. Additionally, they usually consider transmitters in one frequency band to have uncorrelated signals, an uncommon scenario in today's digital TV networks where the same geographical area is often served by multiple towers that form a single-frequency network (SFN). Using data from a measurement campaign carried out in a mid-sized Central European city we assess the accuracy of three widely used propagation models in predicting TV signal strengths for configurations of multiple high-power transmitters. We empirically show that the standard deviation of the estimation error is up to 4 dB higher in a multi-transmitter scenarios with correlated signals than in the single-transmitter case. We put the results in contrast to the prediction capabilities of a generic propagation model that estimates pathloss coefficients and individual correction factors from measurements and combines them with information on transmitter locations, power emissions and antenna patterns. Finally, we study the use of spatial statistics based techniques for directly estimating the coverage characteristics without relying on explicit transmitter information. We show that with only a small subset of measurement locations accuracy beyond standard pathloss models can be achieved.

In this paper, we study the availability of TV white spaces in Europe. Specifically, we focus on the 470-790 MHz UHF band, which will predominantly remain in use for TV broadcasting after the analog-to-digital switch-over and the assignment of the 800 MHz band to licensed services have been completed. The expected number of unused, available TV channels in any location of the 11 countries we studied is 56 percent when we adopt the statistical channel model of the ITU-R. Similarly, a person residing in these countries can expect to enjoy 49 percent unused TV channels. If, in addition, restrictions apply to the use of adjacent TV channels, these numbers reduce to 25 and 18 percent, respectively. These figures are significantly smaller than those recently reported for the United States. We also study how these results change when we use the Longley-Rice irregular terrain model instead. We show that while the overall expected availability of white spaces is essentially the same, the local variability of the available spectrum shows significant changes. This underlines the importance of using appropriate system models before making far-reaching conclusions.

Cognitive radios are becoming the technological foundation for efficiently managing the scarcity of wireless spectrum, fulfilling various QoS demands and allowing different networks to coexist. Cognition and spectrum agility in MAC protocols require adaptability and close PHY-MAC interaction. Classically, MAC protocols have been implemented in hardware, which gives a limited possibility for reconfiguration and customization. Recently, software based MAC implementations have emerged although a close hardware-software co-design is typically required to keep the time critical operations in ASICs or FPGAs. We introduce a MAC development framework for enabling fast composition of MAC protocols, which are best fitted to the application requirements, communication capabilities of the radio, and current spectrum regulations and policies. We decompose MAC protocols into their basic functionalities which are perceived as building blocks and are partitioned across hardware/software. Our framework allows on-the-fly realization of the envisioned MAC protocol through wiring of these fundamental components. By exposing extended metadata and hardware functionalities for the MAC implementation through our granular components, together with the support for run-time re-configuration, spectrum agile and cognitive MAC solutions can be easily realized. In this paper, we describe the design rationale and implementation details of our framework on WARP boards. We show through experimental evaluation that the framework provides flexible means for prototyping different reconfigurable cognitive and spectrum agile MAC protocols.

A common concept to mitigate the effects of spectrum scarcity is to allow opportunistic dynamic spectrum access (DSA) to licensed frequency bands. In this context, the license holder may experience a decrease in the performance of its network. For cellular networks this may lead to unwanted coverage holes at locations where the secondary-induced interference is too strong. In this paper we propose a planning tool and a channel assignment mechanism for cellular OFDMA-based networks that takes the coverage requirements of the primary system into account. By keeping a dynamic reserve of channels for those nodes that experience the highest interference, we can maximize spectrum utilization while guaranteeing a predefined service reliability. Our simulations show that only a small fraction of channels will need exclusive reservation, hence large parts of the spectrum may be employed in secondary systems.

The use of beamforming to enable higher data rates in telecommunications is widely appreciated, but performance gains are typically calculated assuming delay-free feedback from the receiver and neglecting processing time. This paper introduces a mathematical framework based on outage probability that measures the extent to which current channel state information is accurate. Performance gains from beamforming can then be evaluated as a function of the currency of system state. Results are provided for Multiple Input Single Output (MISO) and for Multiuser Multiple Input Multiple Output (MU-MIMO) systems. Outage probabilities and effective diversity orders are calculated for widely used methods of beamforming such as Transmit Antenna Selection as a function of the speed of channel variation.

In this paper we discuss the design of optimization algorithms for cognitive wireless networks (CWNs). Maximizing the perceived network performance towards applications by selecting appropriate protocols and carrying out cross-layer optimization on the resulting stack is a key functionality of any CWN. We take a "black box" approach to the problem and study the use of simulated annealing for solving it. To improve the convergence rate of the basic algorithm we apply machine learning techniques to construct graphical models on the perceived relations between network stack parameters and application-specific network utilities. We test our optimizer design both in a simulation environment as well as on a network testbed with low-power radios. Our results show that even basic simulated annealing works well, but simple graphical models can further increase the convergence rate. However, use of sophisticated models such as Bayesian networks does not always lead to substantially better performance. The results indicate that enhanced simulated annealing indeed appears to be a promising foundation for future cognitive engine designs.

In the LEAP framework for wireless sensor networks a set of keys is used to secure communication. LEAP distinguishes between unicast (pairwise) communication, group (cluster) communication and global (broadcast) communication. The keys used in pairwise communication are derived from an initial key KIthat nodes are equipped with prior to deployment and that is deleted after link setup. Further keys are distributed encrypted with these pairwise keys. It is a weakness that, if the initial key is ever disclosed, the whole network is compromised. To lower the threat of KIdisclosure, we present a KI-less scheme for key predistribution. Our scheme is based on random key predistribution, and proves to perform better in medium sized networks than previous proposals. It is resilient against node capture attacks and allows node to node authentication. Attacks against overlying protocols in the network are more difficult with this scheme. We have conducted computations to show the feasibility of our scheme for networks up to a size of 1000 nodes. By introducing a key reuse system we are able to increase the probability of a successful link setup. We have included a security analysis that discusses our scheme's resistance against commonly known attacks.

We present a protocol for query authentication in a sensor network where there is multi-hop communication and the queries are broadcasted by the base station into the network. Authenticating the queries is important so attackers cannot modify existing queries because this would lead to wrong readings; or insert new ones into the network because this would lead to waste of energy. We propose a layered query authentication protocol that ensures that, in the presence of less than n captured nodes, unauthorized queries are stopped after a small number of hops. When more than n nodes are captured, the unauthorized queries will only spread in one direction with a limited angle. Message authentication codes (MACs) are used to protect the authenticity and integrity of the query, n MACs are attached to the query message at the base station and the nodes replace MACs from this message in an interleaved manner.

We investigate application of agreement protocols tolerating malicious failures in sensor networks. We identify several scenarios where agreement can be used, and report on our experience with implementing an agreement protocol. The ultimate goal is to implement a secure and energy-efficient agreement protocol for sensor networks