The fundamental condition for the legal approval of dynamic spectrum access approaches is the protection of the primary user. However, for dynamic spectrum access to become an attractive service reality, it is crucial to also ensure some quality of service support for the secondary user communication. In this article we discuss sensing-based opportunistic spectrum access approaches, in which primary user protection is achieved by a properly organized sensing process and secondary user communication reconfiguration. While the required reliability of the sensing process can be expressed in terms of rarely enough overlooking the primary user, we assume that the proper QoS for the secondary user is given by maintaining — with a given confidence level — a minimum bandwidth availability for the secondary user in spite of primary user dynamics. In this article we present an overview of approaches that might be used to achieve these objectives. In addition, we point out that both the sensing process and the secondary link maintenance (necessary to keep the required bandwidth in spite of reconfiguration due to detected primary users) require significant spectrum overhead. We identify and elaborate a fundamental trade-off in using these overheads in either sensing or link maintenance, and present examples of its optimization.

In the uplink of OFDMA systems, Multiple Access Interference (MAI) can cause considerable reduction in the throughputs of the User Terminals (UTs). It is well known that applying optimal resource allocation is an efficient means to mitigate MAI, thereby improving UTs' throughputs. In this paper, we show the importance of the consideration of MAI in the resource allocation optimization. To do that we develop a new optimization model based on a solvable minimization of maximum of normalized MAI, which considers MAI and offers suboptimal resource allocation subject to the desired throughput goal. We show that the proposed optimization model improves significantly the minimum UT throughput by approximately 32%. Further, we numerically evaluate and analyze the spread of the resource allocation. As a result of the analysis, we show that, counterintuitively, spreading resource allocation can mitigate MAI and improve user throughputs.

IEEE 802.11 WLANs are currently one of the most popular wireless technologies, but their immediate success results in dense deployments and high demand of user traffic. This in turn leads to decrease in throughput and poor spectrum utilization. Especially in the 2.4 GHz ISM band, where the spectrum is a very scarce resource, all available WLAN channels should be exploited in the best possible way to achieve higher utilization. One way to reach this goal is the usage of partially overlapping channels (POC). Most of the previous work related to POC is based on two major studies addressing 802.11 b, but none of them evaluates the POC behavior in the 802.11 g networks. Moreover, most of the previous results are based on simulations. The main contribution of this work is an experimental evaluation of POC in 802.11g networks. In this paper we confirm quantitatively that 802.11b reacts as expected from the previous studies, while 802.11 g reacts entirely different to the presence of adjacent channel interference. That leads to the conclusion that the usage of POC for 802.11g is not recommended.

In the 2.4 GHz ISM band RF interference is becoming an ever-increasing problem. While there have been several attempts to mitigate the impact of RF interference on (body) sensor networks, e.g. via frequency hopping, it is often unclear how these solutions perform in different interference environments and when they are actually useful. This is not least due to a lack of knowledge about the characteristics of environmental 2.4 GHz RF noise as perceived by a BSN in realistic scenarios. Such knowledge would, for example, help to better understand the communication challenges in a BSN and derive design decisions for interference mitigation techniques. Our work targets this under explored area: we present the results from an urban measurement campaign, in which a mobile BSN collected about half a billion RF noise samples in various urban environments (park, campus, residential area, shopping street, urban transportation system). Our setup captured the entire 2.4 GHz band, on five different body positions simultaneously. Among other things, our results indicate that WLAN was the dominating source of 2.4 GHz RF noise, significant spectrum activity was typically detected during about 5% of the time, but there is a large variation among the scenarios, and, to detect the presence of RF interference the body position is of no of major importance, however, the difference in interference power measured at two different body positions is not negligible.

In the ISM band multiple wireless technologies compete for a limited amount of spectrum, leading to interference and performance degradation. Reliable information on the spectrum occupation enables more optimal usage and can improve co-existence in the ISM band. In this paper, we study the robustness of the information obtained about the propagation environment when sensing with multiple, heterogeneous devices, at multiple diverse locations. More specifically, we look into the impact on the path loss estimation depending on the type, number and the location of the sensing devices. The analysis in this paper is done based on indoor measurements in the ISM band. Based on the presented measurements and analysis we conclude that analysis based on only one device type or in specific locations can lead to suboptimal or even incorrect estimation results.

The sub-optimal exploitation of radio spectrum is widely accepted. Cognitive radio is a technology that aims to address this issue and improve the overall efficiency of radio spectrum utilization. However, this promising technology is far from being mature at present. In addition to theoretical research, experimentally-driven research is needed to convince industry and regulators of the benefits of cognitive radio. Several initiatives in this direction are taking place or are currently operational in both Europe and the United States. Most of them feature testbeds devoted to a specific radio access technology, network topology or application. A “federation” of testbeds, addressing different applications or technologies each, can offer a richer and more powerful framework to tackle the large variety of challenges of experimentally-driven research in cognitive radio. The approach proposed in this paper combines the existing capabilities of several testbeds to build a “federation”. Through intelligent combination of hardware and software components originating from different testbeds and linking them together via standardized interfaces, new components with enhanced capabilities are created. Another key feature of the “federation” is the establishment of a benchmarking framework, enabling repeatable and reproducible results in a controlled wireless environment and allowing a fair comparison between experiments.

This paper reports experimental results comparing the performance of four platforms employed in spectrum sensing and dynamic spectrum access research: a sensing engine developed at imec and built around a prototype RFIC; the Universal Software Radio Peripheral (USRP) with the Iris software defined radio (SDR) solution; the TelosB sensor network platform; and the Wi-Spy low cost spectrum sensor solution targeted at the ISM band. We use experimental data to derive the receiver operating characteristics (ROC) of each of the four platforms. We observe that for low signal powers, narrow bandwidth signals, high shadowing, or stringent probability of false alarm (PFA) requirements tradeoffs among the platforms tested are most pronounced, whereas for high signal powers, large bandwidths, stable environments, and more flexible PFA requirements less expensive, commercial-off-the-shelf equipment performs sufficiently well.

Sensing mechanisms that estimate the occupancy of wireless spectrum are crucial to the success of approaches based on Dynamic Spectrum Access. In this paper, we present key insights into this problem by empirically investigating the design of sensing mechanisms applied to check the availability of excess capacity in CDMA voice networks. We focus on power-based sensing mechanisms since they are arguably the easiest and the most cost-effective. Our insights are developed using a unique dataset consisting of sensed power measurements in the band of a CDMA network operator as well as "ground-truth" information about primary users based on operator data. We find that although power at a single sensor is too noisy to help us accurately estimate unused capacity, there are well-defined signatures of call arrival and termination events. Using these signatures, we show that we can derive lower bound estimates of unused capacity that are both useful (non-zero) and conservative (never exceed the true value). We also use a combination of measurement data and analysis to deduce that multiple sensors are likely to be quite effective in eliminating the inaccuracies of single-sensor estimates.

This document presents five internal usage scenarios that focus on different areas of cognitive radio and cognitive networking research. In each of those a general wireless setup is identified. Aspects of scientific and practical relevance are studied in individual use cases. The first usage scenario holds research objectives and experiments related to context awareness and sensing of a wireless environment. The second scenario is focused on robustness and quality of service in cognitive radio applications. The third, fourth and fifth usage scenarios deal with the question of how to make use of context information to enhance communication in different applications and frequency ranges. This document is to serve as a guideline for the definition of external usage scenarios in later stages of the project and will play a central role in the Definition of the Federation Functionality.

Energy eciency has always been a major issue for battery- powered mobile or embedded devices such as smart-phones or wireless sensor nodes. Interestingly enough the amount of energy which can be drawn out of a given battery does not only depend on the parameters of this battery, but also on the operational modus of its discharge. As the communication is known to have a signicant share in the energy consumption of cooperating objects, this phenomenon should inuence the way such communication is to be designed. In fact, after some stud- ies have provided patterns of \favorable battery usage, the question appears if such patterns should be necessarily enforced into cooperating objects communication scenarios. Using an accurate, well-accepted bat- tery simulator we demonstrate that | surprisingly enough | in order to use the battery capacity in \almost the best way, it is enough to enforce a \favorable discharge modus shortly before complete battery depletion. The modus of battery operation during the majority of its lifetime seems, in contrast, to have only a marginal inuence.

The Physical Layer (PHY) is serving as the interface between the Data Link Layer (DLL) and the environment. Accordingly, it defines the relation between the device and the physical medium. In wireless systems, the general task of the PHY is to convert bit streams into radio waves and vice versa. Though the transmitter and the receiver are dual, they are comprised of different components in the physical layer. The transmitter takes digital input in form of (payload) bits and converts them into an analog signal, generally around a given carrier frequency which is then radiated via the antenna. At the receiver, this analog signal which has been distorted during the propagation is then converted back into a (payload) bit stream. The general goal of the PHY is to ensure that the bit stream at the transmitter and at the receiver are identical. This is a very challenging task as the wireless channel (see Section 11) can distort and corrupt the analog signal in many different, random ways. In the following, we first provide an overview of the different functionalities of the PHY at the transmitter and receiver as applied in most common standards today like for cellular networks (such as Global System for Mobile Communications (GSM), Universal Mobile Telecommunications System (UMTS), Long Term Evolution (LTE)) or local/metropolitan area networks (e.g. IEEE 802.11, IEEE 802.16) as well as for broadcast networks (Digital Audio Broadcasting (DAB), Digital Video Broadcasting (DVB)). Then we discuss common simulation approaches used in the PHY and their shortcomings for network simulation. Finally, we comment on ways to include selected aspects of the PHY in network simulation models.

The fundamental condition for the legal approval of dynamic spectrum access approaches is the protection of the primary user. However, for dynamic spectrum access to become an attractive service reality, it is crucial to also ensure some quality of service support for the secondary user communication. In this article we discuss sensing-based opportunistic spectrum access approaches, in which primary user protection is achieved by a properly organized sensing process and secondary user communication reconfiguration. While the required reliability of the sensing process can be expressed in terms of rarely enough overlooking the primary user, we assume that the proper QoS for the secondary user is given by maintaining - with a given confidence level - a minimum bandwidth availability for the secondary user in spite of primary user dynamics. In this article we present an overview of approaches that might be used to achieve these objectives. In addition, we point out that both the sensing process and the secondary link maintenance (necessary to keep the required bandwidth in spite of reconfiguration due to detected primary users) require significant spectrum overhead. We identify and elaborate a fundamental trade-off in using these overheads in either sensing or link maintenance, and present examples of its optimization.

Energy Framework is an extensible OMNeT++ framework for modeling battery consumption in wireless networks. It is designed so there is a clear separation between modeling of battery state and energy consuming operations, enabling more sophisticated modeling of system behavior. The Energy Framework is largely implemented in "pure" OMNeT++; it has been successfully incorporated into the Mobility Framework and MiXiM.

The major requirement for Cognitive Radio (CR) based opportunistic spectrum re-usage is reliable protection of the primary communication. This calls for a reliable detection of the presence of the Primary Users (PUs) as well as for an immediate reconfiguration of the secondary communication: Each time the PU has been detected, the Secondary Users (SUs) have to vacate the respective part of the spectrum and continue their communication elsewhere. Unfortunately enough, also false positives in the sensing process trigger the same type of reconfiguration, leading to more reconfigurations than actually necessary. Therefore, the efficiency of this reconfiguration process is of high interest. For a frequently postulated OFDM based spectrum pooling SU system two basic questions are considered: (1) How should the parameters of the secondary communication link be selected in order to achieve a stable Quality of Service (QoS) in spite of reconfigurations, and (2) how strongly is the QoS of the SU influenced by reconfigurations caused by a non ideal sensing process, i. e. by an excessive number of false positives.

Frequency Assignment is an important approach to mitigate multi-cell interference in cellular systems. In this paper, we consider frequency hopping as one possible frequency assignment approach. In particular we focus our attention on cognitive radio cellular systems as one of the very promising future access technologies, taking IEEE 802.22 as an example. While the optimal frequency assignment for such a system is conceptually straightforward as well as computationally complex, we demonstrate that usage of distributed methods leads to a significant loss of assignment efficiency. In addition, we suggest means of mitigating this adverse effect.