51,731 research outputs found
Reduced complexity optimal detection of binary faster-than-Nyquist signaling
In this paper, we investigate the detection problem of binary faster-than-Nyquist (FTN) signaling and propose a novel sequence estimation technique that exploits its special structure. In particular, the proposed sequence estimation technique is based on sphere decoding (SD) and exploits the following two characteristics about the FTN detection problem: 1) the correlation between the noise samples after the receiver matched filter, and 2) the structure of the intersymbol interference (ISI) matrix. Simulation results show that the proposed SD-based sequence estimation (SDSE) achieves the optimal performance of the maximum likelihood sequence estimation (MLSE) at reduced computational complexity. This paper demonstrates that FTN signaling has the great potential of increasing the data rate and spectral efficiency substantially, when compared to Nyquist signaling, for the same bit-error-rate (BER) and signal-to-noise ratio (SNR)
A low-cost time-hopping impulse radio system for high data rate transmission
We present an efficient, low-cost implementation of time-hopping impulse
radio that fulfills the spectral mask mandated by the FCC and is suitable for
high-data-rate, short-range communications. Key features are: (i) all-baseband
implementation that obviates the need for passband components, (ii) symbol-rate
(not chip rate) sampling, A/D conversion, and digital signal processing, (iii)
fast acquisition due to novel search algorithms, (iv) spectral shaping that can
be adapted to accommodate different spectrum regulations and interference
environments. Computer simulations show that this system can provide 110Mbit/s
at 7-10m distance, as well as higher data rates at shorter distances under FCC
emissions limits. Due to the spreading concept of time-hopping impulse radio,
the system can sustain multiple simultaneous users, and can suppress narrowband
interference effectively.Comment: To appear in EURASIP Journal on Applied Signal Processing (Special
Issue on UWB - State of the Art
Advanced Algorithms for Satellite Communication Signal Processing
Dizertační práce je zaměřena na softwarově definované přijímače určené k úzkopásmové družicové komunikaci. Komunikační kanály družicových spojů zahrnujících komunikaci s hlubokým vesmírem jsou zatíženy vysokými úrovněmi šumu, typicky modelovaného AWGN, a silným Dopplerovým posuvem signálu způsobeným mimořádnou rychlostí pohybu objektu. Dizertační práce představuje možné postupy řešení výpočetně efektivní digitální downkonverze úzkopásmových signálů a systému odhadu kmitočtu nosné úzkopásmových signálů zatížených Dopplerovým posuvem v řádu násobků šířky pásma signálu. Popis navrhovaných algoritmů zahrnuje analytický postup jejich vývoje a tam, kde je to možné, i analytické hodnocení jejich chování. Algoritmy jsou modelovány v prostředí MATLAB Simulink a tyto modely jsou využity pro ověření vlastností simulacemi. Modely byly také využity k experimentálním testům na reálném signálu přijatém z družice PSAT v laboratoři experimentálních družic na ústavu radioelektroniky.The dissertation is focused on software defined receivers intended for narrowband satellite communication. The satellite communication channel including deep space communication suffers from a high level of noise, typically modeled by AWGN, and from a strong Doppler shift of a signal caused by the unprecedented speed of an object in motion. The dissertation shows possible approaches to the issues of computationally efficient digital downconversion of narrowband signals and the carrier frequency estimation of narrowband signals distorted by the Doppler shift in the order of multiples of the signal bandwidth. The description of the proposed algorithms includes an analytical approach of its development and, if possible, the analytical performance assessment. The algorithms are modeled in MATLAB Simulink and the models are used for validating the performance by the simulation. The models were also used for experimental tests on the real signal received from the PSAT satellite at the laboratory of experimental satellites at the department of radio electronics.
Improving and Assessing Planet Sensitivity of the GPI Exoplanet Survey with a Forward Model Matched Filter
We present a new matched filter algorithm for direct detection of point
sources in the immediate vicinity of bright stars. The stellar Point Spread
Function (PSF) is first subtracted using a Karhunen-Lo\'eve Image Processing
(KLIP) algorithm with Angular and Spectral Differential Imaging (ADI and SDI).
The KLIP-induced distortion of the astrophysical signal is included in the
matched filter template by computing a forward model of the PSF at every
position in the image. To optimize the performance of the algorithm, we conduct
extensive planet injection and recovery tests and tune the exoplanet spectra
template and KLIP reduction aggressiveness to maximize the Signal-to-Noise
Ratio (SNR) of the recovered planets. We show that only two spectral templates
are necessary to recover any young Jovian exoplanets with minimal SNR loss. We
also developed a complete pipeline for the automated detection of point source
candidates, the calculation of Receiver Operating Characteristics (ROC), false
positives based contrast curves, and completeness contours. We process in a
uniform manner more than 330 datasets from the Gemini Planet Imager Exoplanet
Survey (GPIES) and assess GPI typical sensitivity as a function of the star and
the hypothetical companion spectral type. This work allows for the first time a
comparison of different detection algorithms at a survey scale accounting for
both planet completeness and false positive rate. We show that the new forward
model matched filter allows the detection of fainter objects than a
conventional cross-correlation technique with a Gaussian PSF template for the
same false positive rate.Comment: ApJ accepte
Synaptic Transmission: An Information-Theoretic Perspective
Here we analyze synaptic transmission from an information-theoretic
perspective. We derive closed-form expressions for the lower-bounds on the
capacity of a simple model of a cortical synapse under two explicit coding
paradigms. Under the ``signal estimation'' paradigm, we assume the signal to be
encoded in the mean firing rate of a Poisson neuron. The performance of an
optimal linear estimator of the signal then provides a lower bound on the
capacity for signal estimation. Under the ``signal detection'' paradigm, the
presence or absence of the signal has to be detected. Performance of the
optimal spike detector allows us to compute a lower bound on the capacity for
signal detection. We find that single synapses (for empirically measured
parameter values) transmit information poorly but significant improvement can
be achieved with a small amount of redundancy.Comment: 7 pages, 4 figures, NIPS97 proceedings: neuroscience. Originally
submitted to the neuro-sys archive which was never publicly announced (was
9809002
Uplink Linear Receivers for Multi-cell Multiuser MIMO with Pilot Contamination: Large System Analysis
Base stations with a large number of transmit antennas have the potential to
serve a large number of users at high rates. However, the receiver processing
in the uplink relies on channel estimates which are known to suffer from pilot
interference. In this work, making use of the similarity of the uplink received
signal in CDMA with that of a multi-cell multi-antenna system, we perform a
large system analysis when the receiver employs an MMSE filter with a pilot
contaminated estimate. We assume a Rayleigh fading channel with different
received powers from users. We find the asymptotic Signal to Interference plus
Noise Ratio (SINR) as the number of antennas and number of users per base
station grow large while maintaining a fixed ratio. Through the SINR expression
we explore the scenario where the number of users being served are comparable
to the number of antennas at the base station. The SINR explicitly captures the
effect of pilot contamination and is found to be the same as that employing a
matched filter with a pilot contaminated estimate. We also find the exact
expression for the interference suppression obtained using an MMSE filter which
is an important factor when there are significant number of users in the system
as compared to the number of antennas. In a typical set up, in terms of the
five percentile SINR, the MMSE filter is shown to provide significant gains
over matched filtering and is within 5 dB of MMSE filter with perfect channel
estimate. Simulation results for achievable rates are close to large system
limits for even a 10-antenna base station with 3 or more users per cell.Comment: Accepted for publication in IEEE Transactions on Wireless
Communication
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