Sensing-Throughput Tradeoff for Interweave Cognitive Radio System: A Deployment-Centric Viewpoint

Secondary access to the licensed spectrum is viable only if interference is avoided at the primary system. In this regard, different paradigms have been conceptualized in the existing literature. Of these, Interweave Systems (ISs) that employ spectrum sensing have been widely investigated. Baseline models investigated in the literature characterize the performance of IS in terms of a sensing-throughput tradeoff, however, this characterization assumes the knowledge of the involved channels at the secondary transmitter, which is unavailable in practice. Motivated by this fact, we establish a novel approach that incorporates channel estimation in the system model, and consequently investigate the impact of imperfect channel estimation on the performance of the IS. More particularly, the variation induced in the detection probability affects the detector's performance at the secondary transmitter, which may result in severe interference at the primary users. In this view, we propose to employ average and outage constraints on the detection probability, in order to capture the performance of the IS. Our analysis reveals that with an appropriate choice of the estimation time determined by the proposed model, the degradation in performance of the IS can be effectively controlled, and subsequently the achievable secondary throughput can be significantly enhanced.Comment: 13 pages, 10 figures, Accepted to be published in IEEE Transactions on Wireless Communication

Predicting expected TCP throughput using genetic algorithm

Predicting the expected throughput of TCP is important for several aspects such as e.g. determining handover criteria for future multihomed mobile nodes or determining the expected throughput of a given MPTCP subflow for load-balancing reasons. However, this is challenging due to time varying behavior of the underlying network characteristics. In this paper, we present a genetic-algorithm-based prediction model for estimating TCP throughput values. Our approach tries to find the best matching combination of mathematical functions that approximate a given time series that accounts for the TCP throughput samples using genetic algorithm. Based on collected historical datapoints about measured TCP throughput samples, our algorithm estimates expected throughput over time. We evaluate the quality of the prediction using different selection and diversity strategies for creating new chromosomes. Also, we explore the use of different fitness functions in order to evaluate the goodness of a chromosome. The goal is to show how different tuning on the genetic algorithm may have an impact on the prediction. Using extensive simulations over several TCP throughput traces, we find that the genetic algorithm successfully finds reasonable matching mathematical functions that allow to describe the TCP sampled throughput values with good fidelity. We also explore the effectiveness of predicting time series throughput samples for a given prediction horizon and estimate the prediction error and confidence.Peer ReviewedPostprint (author's final draft

Imperfect Digital Fibre Optic Link Based Cooperative Distributed Antennas with Fractional Frequency Reuse in Multicell Multiuser Networks

The achievable throughput of the entire cellular area is investigated, when employing fractional frequency reuse techniques in conjunction with realistically modelled imperfect optical fibre aided distributed antenna systems (DAS) operating in a multicell multiuser scenario. Given a fixed total transmit power, a substantial improvement of the cell-edge area's throughput can be achieved without reducing the cell-centre's throughput. The cell-edge's throughput supported in the worst-case direction is significantly enhanced by the cooperative linear transmit processing technique advocated. Explicitly, a cell-edge throughput of $\eta=5$ bits/s/Hz may be maintained for an imperfect optical fibre model, regardless of the specific geographic distribution of the users

Digital RoF Aided Cooperative Distributed Antennas with FFR in Multicell Multiuser Networks

The achievable throughput of the entire cellular area is investigated, when employing fractional frequency reuse techniques in conjunction with realistically modelled imperfect optical fibre aided distributed antenna systems (DAS). Given a fixed total transmit power, a substantial improvement of the cell-edge area’s throughput can be achieved without reducing the cell-centre’s throughput. The cell-edge’s throughput supported in the worst-case direction is significantly enhanced by the cooperative linear transmit processing technique advocated. Explicitly, a cell-edge throughput of η = 5 bits/s/Hz may be maintained for a imperfect optical fibre model, regardless of the specific geographic distribution of the users

RNA-aptamers-in-droplets (RAPID) high-throughput screening for secretory phenotypes.

Synthetic biology and metabolic engineering seek to re-engineer microbes into living foundries for the production of high value chemicals. Through a design-build-test cycle paradigm, massive libraries of genetically engineered microbes can be constructed and tested for metabolite overproduction and secretion. However, library generation capacity outpaces the rate of high-throughput testing and screening. Well plate assays are flexible but with limited throughput, whereas droplet microfluidic techniques are ultrahigh-throughput but require a custom assay for each target. Here we present RNA-aptamers-in-droplets (RAPID), a method that greatly expands the generality of ultrahigh-throughput microfluidic screening. Using aptamers, we transduce extracellular product titer into fluorescence, allowing ultrahigh-throughput screening of millions of variants. We demonstrate the RAPID approach by enhancing production of tyrosine and secretion of a recombinant protein in Saccharomyces cerevisiae by up to 28- and 3-fold, respectively. Aptamers-in-droplets affords a general approach for evolving microbes to synthesize and secrete value-added chemicals.Screening libraries of genetically engineered microbes for secreted products is limited by the available assay throughput. Here the authors combine aptamer-based fluorescent detection with droplet microfluidics to achieve high throughput screening of yeast strains engineered for enhanced tyrosine or streptavidin production