A New Robust Interference Reduction Scheme for Low Complexity Direct-Sequence Spread-Spectrum Receivers: Performance

Goiser, A.M.J.; Khattab, Samar; Fassl, Gerhard; Schmid, Ulrich

doi:10.1109/ctrq.2010.52

Cited by 6 publications

(8 citation statements)

References 11 publications

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“…So for Δ = 0 we see the conversion-gain of the HL-detector. For the HL-device the conversion-gain ranges from about -2 dB (WGN) to about -7 dB (CW) which is in agreement with the theory [4]. The RCS-device adjust the threshold Δ for varying interference compositions always to its optimum location.…”

Section: B Blind Adaptive Interference Reductionsupporting

confidence: 73%

“…The mean conversion-gain for one sample, sampled at the chip-rate, is drawn against the power-ratio of the ratio of the SONIs (I ... power of the CW, N ... power of the AWGN), while the power-ratio of the SOI respective the SONI is kept fixed at -15 dB (poor signal condition). A detailed evaluation of the conversion-gain can be found in [4]. The significant improvement for dominating CW-interference is remarkable.…”

Section: B Blind Adaptive Interference Reductionmentioning

confidence: 99%

“…The inclusion of the information of the level-crossings to the information content of the magnitude statistics bridge the gap to optimum and fast adaptation using simple and low complex memoryless nonlinearities prior to spread-spectrum detection [3], [4]. That previous analysis are done for the single-link case.…”

Section: Contribution To Literaturementioning

confidence: 99%

“…The improvement in symbolerror-probability for the RCS-detector, originated from the conversion-gain for dominating CW-interference, is obvious. Details about the performance evaluation for a single link (K=1) structure can be found in [4].…”

Section: B Blind Adaptive Interference Reductionmentioning

confidence: 99%

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Low-Complex Reliable Communications between Wireless Network-Nodes

Goiser¹

2015

Proceedings of the 1st International Conference on Industrial Networks and Intelligent Systems

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Abstract-We present a low-complex blind interference reduction scheme embedded in the receiver to enhance correlative data detection. The key element is a statistically controlled adaptive nonlinearity prior to correlation. This add-on feature guaranties reliable communication between network-nodes in any type of noise and/or interference. Additionally the concept provides accurate position measurements to make services flexible and intelligent.

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Section: B Blind Adaptive Interference Reductionsupporting

confidence: 73%

Section: B Blind Adaptive Interference Reductionmentioning

confidence: 99%

Section: Contribution To Literaturementioning

confidence: 99%

Section: B Blind Adaptive Interference Reductionmentioning

confidence: 99%

See 2 more Smart Citations

Low-Complex Reliable Communications between Wireless Network-Nodes

Goiser¹

2015

Proceedings of the 1st International Conference on Industrial Networks and Intelligent Systems

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“…by the following arguments: Equation (5) states that the information at m has been transmitted to at least f + 1 nodes. By assumption In i (G 2 ) ≥ n − f for all i ∈ [n].…”

Section: Nonsplit Network From Asynchronous Roundsmentioning

confidence: 99%

On the radius of nonsplit graphs and information dissemination in dynamic networks

Függer

Nowak

Winkler

2020

Discrete Applied Mathematics

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A nonsplit graph is a directed graph where each pair of nodes has a common incoming neighbor. We show that the radius of such graphs is in O(log log n), where n is the number of nodes. We then generalize the result to products of nonsplit graphs.The analysis of nonsplit graph products has direct implications in the context of distributed systems, where processes operate in rounds and communicate via message passing in each round: communication graphs in several distributed systems naturally relate to nonsplit graphs and the graph product concisely represents relaying messages in such networks. Applying our results, we obtain improved bounds on the dynamic radius of such networks, i.e., the maximum number of rounds until all processes have received a message from a common process, if all processes relay messages in each round. We finally connect the dynamic radius to lower bounds for achieving consensus in dynamic networks.

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Gracefully Degrading Consensus and k-Set Agreement in Directed Dynamic Networks

et al. 2015

Self Cite

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We study distributed agreement in synchronous directed dynamic networks, where an omniscient message adversary controls the presence/absence of communication links. We prove that consensus is impossible under a message adversary that guarantees weak connectivity only, and introduce vertex-stable root components (VSRCs) as a means for circumventing this impossibility: A VSRC(k, d) message adversary guarantees that, eventually, there is an interval of d consecutive rounds where every communication graph contains at most k strongly connected components consisting of the same processes (with possibly varying interconnect topology), which have at most out-going links to the remaining processes. We present a consensus algorithm that works correctly under a VSRC(1, 4H + 2) message adversary, where H is the dynamic causal network diameter. Our algorithm maintains local estimates of the communication graphs, and applies techniques for detecting network stability and univalent system configurations. Several related impossibility results and lower bounds, in particular, that neither a VSRC(1, H − 1) message adversary nor a VSRC(2, ∞) one allow to solve consensus, reveal that there is not much hope to deal with (much) stronger message adversaries here. However, we show that gracefully degrading consensus, which degrades to general k-set agreement in case of unfavorable network conditions, allows to cope with stronger message adversaries: We provide a k-uniform k-set agreement algorithm, where the number of system-wide decision values k is not encoded in the algorithm, but rather determined by the actual power of the message adversary in a run: Our algorithm guarantees at most k decision values under a VSRC(n, d) + MAJINF(k) message adversary, which combines VSRC(n, d) (with some small value of d, ensuring termination) with some information flow guarantee MAJINF(k) between certain VSRCs (ensuring k-agreement).Since related impossibility results reveal that a VSRC(k, d) message adversary is too strong for solving k-set agreement and that some information flow between VSRCs is mandatory for this purpose as well, our results provide a significant step towards the exact solvability/impossibility border of general k-set agreement in directed dynamic networks.Dynamic networks, instantiated, e.g., by wireless sensor networks, mobile ad-hoc networks and vehicle area networks, are becoming ubiquitous nowadays. The primary properties of such networks are sets of participants (called processes in the sequel) that are a priori unknown and potentially changing, timevarying connectivity between processes, and the absence of a central control. Dynamic networks is an important and very active area of research [37].Accurately modeling dynamic networks is challenging, for several reasons: First, process mobility, process crashes/recoveries, deliberate joins/leaves, and peculiarities in the low-level system design like duty-cycling (used to save energy in wireless sensor networks) make static communication topologies, as typically used in class...

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A New Robust Interference Reduction Scheme for Low Complexity Direct-Sequence Spread-Spectrum Receivers: Performance

Cited by 6 publications

References 11 publications

Low-Complex Reliable Communications between Wireless Network-Nodes

Low-Complex Reliable Communications between Wireless Network-Nodes

On the radius of nonsplit graphs and information dissemination in dynamic networks

Gracefully Degrading Consensus and k-Set Agreement in Directed Dynamic Networks

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