Browsing by Author "Vosoughi, Aida"

Now showing 1 - 7 of 7
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    A Context-Aware Trust Framework for Resilient Distributed Cooperative Spectrum Sensing in Dynamic Settings
    (IEEE, 2017) Vosoughi, Aida; Cavallaro, Joseph R.; Marshall, Alan
    Cognitive radios enable dynamic spectrum access where secondary users (SUs) are allowed to operate on the licensed spectrum bands on an opportunistic noninterference basis. Cooperation among the SUs for spectrum sensing is essential for environments with deep shadows. In this paper, we study the adverse effect of insistent spectrum sensing data falsification (ISSDF) attack on iterative distributed cooperative spectrum sensing. We show that the existing trust management schemes are not adequate in mitigating ISSDF attacks in dynamic settings where the primary user (PU) of the band frequently transitions between active and inactive states. We propose a novel context-aware distributed trust framework for cooperative spectrum sensing in mobile cognitive radio ad hoc networks (CRAHN) that effectively alleviates different types of ISSDF attacks (Always-Yes, Always-No, and fabricating) in dynamic scenarios. In the proposed framework, the SU nodes evaluate the trustworthiness of one another based on the two possible contexts in which they make observations from each other: PU absent context and PU present context. We evaluate the proposed context-aware scheme and compare it against the existing context-oblivious trust schemes using theoretical analysis and extensive simulations of realistic scenarios of mobile CRAHNs operating in TV white space. We show that in the presence of a large set of attackers (as high as 60% of the network), the proposed context-aware trust scheme successfully mitigates the attacks and satisfy the false alarm and missed-detection rates of 10−2 and lower. Moreover, we show that the proposed scheme is scalable in terms of attack severity, SU network density, and the distance of the SU network to the PU transmitter.
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    Baseband Signal Compression in Wireless Base Stations
    (IEEE, 2012-12-01) Vosoughi, Aida; Wu, Michael; Cavallaro, Joseph R.; CMC
    To comply with the evolving wireless standards, base stations must provide greater data rates over the serial data link between base station processor and RF unit. This link is especially important in distributed antenna systems and cooperating base stations settings. This paper explores the compression of baseband signal samples prior to transfer over the above-mentioned link. We study lossy and lossless compression of baseband signals and analyze the cost and gain of each approach. Sample quantizing is proposed as a lossy compression scheme and it is shown to be effective by experiments. With QPSK modulation, sample quantizing achieves a compression ratio of 4:1 and 3.5:1 in downlink and uplink, respectively. The corresponding compression ratios are 2.3:1 and 2:1 for 16-QAM. In addition, lossless compression algorithms including arithmetic coding, Elias-gamma coding, and unused significant bit removal, and also a recently proposed baseband signal compression scheme are evaluated. The best compression ratio achieved for lossless compression is 1.5:1 in downlink. Our over-the-air experiments suggest that compression of baseband signal samples is a feasible and promising solution for increasing the effective bit rates of the link to/from remote RF units without requiring much complexity and cost to the base station.
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    Data Compression in Base Transceiver Systems
    (2012-10) Vosoughi, Aida; Cavallaro, Joseph R.; Wu, Michael
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    Dataflow Modeling and Design for Cognitive Radio Networks
    (8th International Conference on Cognitive Radio Oriented Wireless Networks, 2013-10-01) Wang, Lai-Huei; Bhattacharyya, Shuvra S.; Vosoughi, Aida; Cavallaro, Joseph R.; Juntti, Markku; Boutellier, Jani; Silven, Olli; Valkama, Mikko; CMC
    Cognitive radio networks present challenges at many levels of design including configuration, control, and crosslayer optimization. In this paper, we focus primarily on dataflow representations to enable flexibility and reconfigurability in many of the baseband algorithms. Dataflow modeling will be important to provide a layer of abstraction and will be applied to generate flexible baseband representations for cognitive radio testbeds, including the Rice WARP platform. As RF frequency agility and reconfiguration for carrier aggregation are important goals for 4G LTE Advanced systems, we also focus on dataflow analysis for digital pre-distortion algorithms. A new design method called parameterized multidimensional design hierarchy mapping(PMDHM) is presented, along with initial speedup results from applying PMDHM in the mapping of channel estimation onto a GPU architecture.
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    Highly Scalable On-the-Fly Interleaved Address Generation for UMTS/HSPA+ Parallel Turbo Decoder
    (24th IEEE International Conference on Application-specific Systems, Architectures and Processors, 2013-06-01) Vosoughi, Aida; Wang, Guohui; Shen, Hao; Cavallaro, Joseph R.; Guo, Yuanbin; CMC
    High throughput parallel interleaver design is a major challenge in designing parallel turbo decoders that conform to high data rate requirements of advanced standards such as HSPA+. The hardware complexity of the HSPA+ interleaver makes it difficult to scale to high degrees of parallelism. We propose a novel algorithm and architecture for on-the-fly parallel interleaved address generation in UMTS/HSPA+ standard that is highly scalable. Our proposed algorithm generates an interleaved memory address from an original input address without building the complete interleaving pattern or storing it; the generated interleaved address can be used directly for interleaved writing to memory blocks. We use an extended Euclidean algorithm for modular multiplicative inversion as a step towards reversed intra-row permutations in UMTS/HSPA+ standard. As a result, we can determine interleaved addresses from original addresses. We also propose an efficient and scalable hardware architecture for our method. Our design generates 32 interleaved addresses in one cycle and satisfies the data rate requirement of 672 Mbps in HSPA+ while the silicon area and frequency is improved compared to recent related works.
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    Parallel Interleaver Architecture with New Scheduling Scheme for High Throughput Configurable Turbo Decoder
    (IEEE, 2013-05) Wang, Guohui; Vosoughi, Aida; Shen, Hao; Cavallaro, Joseph R.; Guo, Yuanbin
    Parallel architecture is required for high throughput turbo decoder to meet the data rate requirements of the emerging wireless communication systems. However, due to the severe memory conflict problem caused by parallel architectures, the interleaver design has become a major challenge that limits the achievable throughput. Moreover, the high complexity of the interleaver algorithm makes the parallel interleaving address generation hardware very difficult to implement. In this paper, we propose a parallel interleaver architecture that can generate multiple interleaving addresses on-the-fly. We devised a novel scheduling scheme with which we can use more efficient buffer structures to eliminate memory contention. The synthesis results show that the proposed architecture with the new scheduling scheme can significantly reduce memory usage and hardware complexity. The proposed architecture also shows great flexibility and scalability compared to prior work.
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    Robust Distributed Cooperative Spectrum Sensing for Cognitive Radio Ad Hoc Networks
    (2016-04-25) Vosoughi, Aida; Cavallaro, Joseph R
    Dynamic spectrum access paradigm, enabled by cognitive radios, presents an adaptive approach for spectrum sharing by allowing secondary users to use licensed spectrum bands on an opportunistic non-interference basis. Cooperation among cognitive radios for spectrum sensing is deemed essential for environments with deep shadows. However, the existing cooperative spectrum sensing schemes for mobile ad hoc networks are high-overhead and vulnerable to spectrum sensing data falsification attacks. In this thesis, we propose a novel trust-aware consensus-inspired cooperative sensing scheme based on iterative broadcast and linear updates that is fully distributed, low-cost and resilient to malicious behavior in the cooperative network. Unlike the existing schemes, our method does not require any network discovery by the nodes for cooperation; therefore, it offers significantly lower overhead with no degradation in the sensing performance. We study Insistent Spectrum Sensing Data Falsification (ISSDF) attack aimed at iterative cooperative sensing schemes and show its destructive effect on the cooperation performance which accordingly results in reduced spectrum efficiency and increased interference with primary users. We design a novel distributed trust management scheme that is integrated into cooperation to mitigate different types of ISSDF attacks in practical scenarios where the primary user and secondary users of the spectrum and the malicious users behave dynamically. The characteristics of the proposed trust scheme is thoroughly analyzed by theory and experiments. We evaluate our proposed trust-aware distributed cooperative sensing scheme by extensive Monte Carlo simulations modeling realistic scenarios of mobile cognitive radio ad hoc networks in TV white space. We show that the proposed scheme reduces the harm of a set of collusive ISSDF attackers up to two orders of magnitude in terms of missed-detection and false alarm error rates. In addition, in a hostile environment, integration of trust management into distributed cooperative sensing considerably relaxes the sensitivity requirements on the cognitive radio devices. Furthermore, in order to evaluate the scalability, we analyze the impact of various parameters of the cognitive radio network, the cooperation scheme and the trust management scheme on the sensing performance in the presence of malicious behavior.