1,093 research outputs found
Supersampling and network reconstruction of urban mobility
Understanding human mobility is of vital importance for urban planning,
epidemiology, and many other fields that aim to draw policies from the
activities of humans in space. Despite recent availability of large scale data
sets related to human mobility such as GPS traces, mobile phone data, etc., it
is still true that such data sets represent a subsample of the population of
interest, and then might give an incomplete picture of the entire population in
question. Notwithstanding the abundant usage of such inherently limited data
sets, the impact of sampling biases on mobility patterns is unclear -- we do
not have methods available to reliably infer mobility information from a
limited data set. Here, we investigate the effects of sampling using a data set
of millions of taxi movements in New York City. On the one hand, we show that
mobility patterns are highly stable once an appropriate simple rescaling is
applied to the data, implying negligible loss of information due to subsampling
over long time scales. On the other hand, contrasting an appropriate null model
on the weighted network of vehicle flows reveals distinctive features which
need to be accounted for. Accordingly, we formulate a "supersampling"
methodology which allows us to reliably extrapolate mobility data from a
reduced sample and propose a number of network-based metrics to reliably assess
its quality (and that of other human mobility models). Our approach provides a
well founded way to exploit temporal patterns to save effort in recording
mobility data, and opens the possibility to scale up data from limited records
when information on the full system is needed.Comment: 14 pages, 4 figure
Conditional maximum likelihood timing recovery
The conditional maximum likelihood (CML) principle, well known in the context of sensor array processing, is applied to the problem of timing recovery. A new self-noise free CML-based timing error detector is derived. Additionally, a new (conditional) Cramer-Rao bound (CRB) for timing estimation is obtained, which is more accurate than the extensively used modified CRB (MCRB).Peer ReviewedPostprint (published version
Non-data-aided frequency offset and symbol timing estimation for binary CPM: performance bounds
The use of (spectrally efficient) CPM modulations may lead to a serious performance degradation of the classical non-data-aided (NDA) frequency and timing estimators due to the presence of self noise. The actual performance of these estimators is usually much worse than that predicted by the classical modified Cramer-Rao bound. We apply some well known results in the field of signal processing to these two important problems of synchronization. In particular we propose and explain the meaning of the unconditional CRB in the synchronization task. Simulation results for MSK and GMSK, along with the performance of some classical and previously proposed synchronizers, show that the proposed bound (along with the MCRB) is useful for a better prediction of the ultimate performance of the NDA estimators.Peer ReviewedPostprint (published version
Robust beamforming for interference rejection in mobile communications
The problem of robust beamformer design in the presence of moving sources is considered. A new technique based on a generalization of the constrained minimum variance beamformer is proposed. The method explicitly takes into account changes in the scenario due to the movement of the desired and interfering sources, requiring only estimation of the desired DOA. Computer simulations show that the resulting performance constitutes a compromise between interference and noise rejection, computational complexity, and sensitivity to source movement.Peer ReviewedPostprint (published version
Near-far resistant CML propagation delay estimation and multi-user detection for asynchronous DS-CDMA systems
Multi-user receivers in asynchronous direct sequence code division multiple access (DS-CDMA) systems require the knowledge of several parameters such as timing delay between users. The goal of this work is to present a near-far resistant joint multi-user synchronization and detection algorithm for DS-CDMA systems. The solution is based on the conditional maximum likelihood (CML) estimation method (classically used in the context of sensor array processing) that leads to a fast convergence algorithm to estimate the time delays among users. At the same time the estimator implements the decorrelating detector, identifying the transmitted symbols for the different users.Peer ReviewedPostprint (published version
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