Browsing by Subject "Cognitive radio"

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Bandwidth and power efficient wireless spectrum sensing networks
(2011-05) Kim, Jaeweon; Andrews, Jeffrey G.; Vishwanath, Sriram; Arapostathis, Aristotle; Vikalo, Haris; Barr, Ronald E.
Opportunistic spectrum reuse is a promising solution to the two main causes of spectrum scarcity: most of the radio frequency (RF) bands are allocated by static licensing, and many of them are underutilized. Frequency spectrum can be more efficiently utilized by allowing communication systems to find out unoccupied spectrum and to use it harmlessly to the licensed users. Reliable sensing of these spectral opportunities is perhaps the most essential element of this technology. Despite significant work on spectrum sensing, further performance improvement is needed to approach its full potential. In this dissertation, wireless spectrum sensing networks (WSSNs) are investigated for reliable detection of the primary (licensed) users, that enables efficient spectrum utilization and minimal power consumption in communications. Reliable spectrum sensing is studied in depth in two parts: a single sensor algorithm and then cooperative sensing are proposed based on a spectral covariance sensing (SCS). The first novel contribution uses different statistical correlations of the received signal and noise in the frequency domain. This detector is analyzed theoretically and verified through realistic simulations using actual digital television signals captured in the US. The proposed SCS detector achieves significant improvement over the existing solutions in terms of sensitivity and also robustness to noise uncertainty. Second, SCS is extended to a distributed WSSN architecture to allow cooperation between 2 or more sensors. Theoretical limits of cooperative white space sensing under correlated shadowing are investigated. We analyze the probability of a false alarm when each node in the WSSN detects the white space using the SCS detection and the base station combines individual results to make the final decision. The detection performance compared with that of the cooperative energy detector is improved and fewer sensor nodes are needed to achieve the same sensitivity. Third, we propose a low power source coding and modulation scheme for power efficient communication between the sensor nodes in WSSN. Complete analysis shows that the proposed scheme not only minimizes total power consumption in the network but also improves bit error rate (BER).
Beyond white space : robust spectrum sensing and channel statistics based spectrum accessing strategies for cognitive radio network
(2013-08) Liu, Yingxi; Tewfik, Ahmed
Cognitive radio refers to the technology that the devices can intelligently access unused frequency resources which are originally reserved for legacy services in order to increase the spectrum utilization. At the mean time, the legacy services should not be affected by the access of cognitive radio devices. The common problems in cognitive radio are how to find unused frequency resources (spectrum sensing) and how to access them (spectrum accessing). This dissertation focuses on the robust methods of spectrum sensing as well as spectrum accessing strategies with the statistics of channel availabilities. The first part of the thesis studies non-parametric robust hypothesis testing problem to eliminate the effect of the uncertainty and instability introduced by non-stationary noise, which is constantly observed in communication systems. An empirical likelihood ratio test with density function constraints is proposed. This test outperforms many popular goodness-of-fit tests, including the robust Kolmogorov-Smirnov test and the Cramér-von Mises test, etc. Examples using spectrum sensing data with real-world noise samples are provided to show their performance. The second part focuses on channel idle time distribution based spectrum accessing strategies. Through the study of the real-world wireless local area network traffic, it is identified that the channel idle time distribution can be modeled using hyper-exponential distribution. With this model, the performance of a single cognitive radio, or the secondary user, is studied when the licensed user, or the primary user, does not react to interference. It is also shown that with the complete information of the hyper-exponential distribution, the secondary user can achieve a desirable performance. But when the model exhibits uncertainty and time non-stationarity, which would happen for any kind of wireless traffic, the secondary user suffers from huge performance loss. A strategy that is robust to the uncertainty is proposed. The performance of this strategy is demonstrated using experimental data. Another aspect of the problem is when the PU is reactive. In this case, a spectrum accessing strategy is devised to avoid large-duration interference to the PU. Additionally, the spectrum accessing strategies are also extended to the cognitive radio networks with multiple secondary users. A decentralized MAC protocol is devised which reaches a total secondary capacity performance close to the optimal. A discussion of the engineering aspects with practical consideration of spectrum sensing and accessing is given at the end.
Cognitive radios : fundamental limits and applications to cellular and wireless local networks
(2012-05) Chung, Goochul; Vishwanath, Sriram; Shakkottai, Sanjay; Andrews, Jeffrey; Caramanis, Constantine; Choi, Jihwan
An ever increasing number of wirelessly-enabled applications places a very high demand on stringent spectral resources. Cognitive radios have the potential of enhancing spectral efficiency by improving the usage of channels that are already licensed for a specific purpose. Research on cognitive radios involves answering questions such as: how can a cognitive radio transmit at a high data rate while maintaining the same quality of service for the licensed user? There are multiple forms of cognition studied in literature, and each of these models must be studied in detail to understand its impact on the overall system performance. Specifically, the information-theoretic capacity of such systems is of great interest. Also, the design of cognitive radio is necessary to achieve those capacities in real applications. In this dissertation, we formulate different problems that relate to the performance of such systems and methods to increase their efficiency. This dissertation discusses, firstly, the means of "sensing" in cognitive systems, secondly, the optimal resource allocation algorithms for interweave cognitive radio, and finally, the fundamental limits of partially and overly cognitive overlay systems.
Designing MIMO interference alignment networks
(2012-08) Nosrat Makouei, Behrang; Heath, Robert W., Jr, 1973-; Andrews, Jeffrey G.; Evans, Brian L.; Hasenbein, John; Nettles, Scott; Vishwanath, Sriram
Wireless networks are increasingly interference-limited, which motivates the development of sophisticated interference management techniques. One recently discovered approach is interference alignment, which attains the maximum sum rate scaling (with signal-to-noise ratio) in many network configurations. Interference alignment is not yet well understood from an engineering perspective. Such design considerations include (i) partial rather than complete knowledge of channel state information, (ii) correlated channels, (iii) bursty packet-based network traffic that requires the frequent setup and tear down of sessions, and (iv) the spatial distribution and interaction of transmit/receive pairs. This dissertation aims to establish the benefits and limitations of interference alignment under these four considerations. The first contribution of this dissertation considers an isolated group of transmit/receiver pairs (a cluster) cooperating through interference alignment and derives the signal-to-interference-plus-noise ratio distribution at each receiver for each stream. This distribution is used to compare interference alignment to beamforming and spatial multiplexing (as examples of common transmission techniques) in terms of sum rate to identify potential switching points between them. This dissertation identifies such switching points and provides design recommendations based on severity of the correlation or the channel state information uncertainty. The second contribution considers transmitters that are not associated with any interference alignment cooperating group but want to use the channel. The goal is to retain the benefits of interference alignment amid interference from the out-of-cluster transmitters. This dissertation shows that when the out-of-cluster transmitters have enough antennas, they can access the channel without changing the performance of the interference alignment receivers. Furthermore, optimum transmit filters maximizing the sum rate of the out-of-cluster transmit/receive pairs are derived. When insufficient antennas exist at the out-of-cluster transmitters, several transmit filters that trade off complexity and sum rate performance are presented. The last contribution, in contrast to the first two, takes into account the impact of large scale fading and the spatial distribution of the transmit/receive pairs on interference alignment by deriving the transmission capacity in a decentralized clustered interference alignment network. Channel state information uncertainty and feedback overhead are considered and the optimum training period is derived. Transmission capacity of interference alignment is compared to spatial multiplexing to highlight the tradeoff between channel estimation accuracy and the inter-cluster interference; the closer the nodes to each other, the higher the channel estimation accuracy and the inter-cluster interference.
Novel channel sensing and access strategies in opportunistic spectrum access networks
(2012-05) Kundargi, Nikhil Ulhas; Tewfik, Ahmed; Andrews, Jeffrey; Qiu, Lili; Sanghavi, Sujay; Vishwanath, Sriram
Traditionally radio spectrum was considered a commodity to be allocated in a fixed and centralized manner, but now the technical community and the regulators approach it as a shared resource that can be flexibly and intelligently shared between competing entities. In this thesis we focus on novel strategies to sense and access the radio spectrum within the framework of Opportunistic Spectrum Access via Cognitive Radio Networks (CRNs). In the first part we develop novel transmit opportunity detection methods that effectively exploit the gray space present in packet based networks. Our methods proactively detect the maximum safe transmit power that does not significantly affect the primary network nodes via an implicit feedback mechanism from the Primary network to the Secondary network. A novel use of packet interarrival duration is developed to robustly perform change detection in the primary network's Quality of Service. The methods are validated on real world IEEE 802.11 WLANs. In the second part we study the inferential use of Goodness-of-Fit tests for spectrum sensing applications. We provide the first comprehensive framework for decision fusion of an ensemble of goodness-of-fit tests through use of p-values. Also, we introduce a generalized Phi-divergence statistic to formulate goodness-of-fit tests that are tunable via a single parameter. We show that under uncertainty in the noise statistics or non-Gaussianity in the noise, the performance of such non-parametric tests is significantly superior to that of conventional spectrum sensing methods. Additionally, we describe a collaborative spatially separated version of the test for robust combining of tests in a distributed spectrum sensing setting. In the third part we develop the sequential energy detection problem for spectrum sensing and formulate a novel Sequential Energy Detector. Through extensive simulations we demonstrate that our doubly hierarchical sequential testing architecture delivers a significant throughput improvement of 2 to 6 times over the fixed sample size test while maintaining equivalent operating characteristics as measured by the Probabilities of Detection and False Alarm. We also demonstrate the throughput gains for a case study of sensing ATSC television signals in IEEE 802.22 systems.