Achieving near exponential diversity on uncoded low-dimensional MIMO, multi-user and multi-carrier systems without transmitter

Abstract-It is well-known that for single-input and singleoutput (SISO) narrow-band transmission on frequency-flat fading channels, uncoded communication with only receiver channel state information (Rx-CSI) leads to extremely poor reliability performance whereas transmitter CSI (Tx-CSI) allows us approach the reliability of an additive white Gaussian noise (AWGN) channel via power control. In this paper, we propose a novel approach to achieve reliability close to the AWGN channel for uncoded transmissions on SISO frequency-flat Rayleigh fading channels without Tx-CSI. Our approach employs pseudo-random phase precoding (PRPP) of modulation symbols prior to temporal multiplexing, and joint-detection at the receiver that has polynomial complexity in the precoder size. With a precoder size of 400 binary symbols, we demonstrate that the proposed system achieves performance within 0.1 dB of the AWGN channel at a bit error rate of 10 −5 , and is also robust to fading correlation and channel estimation errors. Furthermore, we present extensions to multiple-user multiple-input and multiple-output (MU-MIMO) systems and wideband transmission schemes such as orthogonal frequency-division multiplexing (OFDM) and singlecarrier frequency-domain multiple access (SC-FDMA) systems. We show, through extensive simulations, that i) with an 8-by-8 MIMO system per-stream AWGN channel reliability is achieved with 8 spatial streams and 50 channel uses, ii) for a 5 user multiple-access channel with one antenna per user and 5 antennas at the receiver, 80 channel uses eliminates fading and interference completely while simultaneously providing a power gain of approximately 6.9 dB, and iii) for OFDM and SC-FDMA systems with single antenna at the transmitter and two antennas at the receiver, within 0.1 and 0.3 dB of the matched-filter bound performance is achieved with a precoder size of 96 and 400 symbols, respectively. Index Terms-Single-antenna transmission, pseudo-random phase precoding, multi-user MIMO, matched-filter bound, uncoded multi-carrier systems, large-dimensional detection

Parameter Estimation of Hybrid Sinusoidal FM-Polynomial Phase Signal

This paper considers parameter estimation of a hybrid sinusoidal frequency modulated (FM) and polynomial phase signal (PPS) from a finite number of samples. We first show limitations of an existing method, the high-order ambiguity function (HAF), and then propose a new method by adopting the high-order phase function which was originally designed for the pure PPS. The proposed method estimates parameters of interest from peak locations in the time-frequency rate domain, which are less perturbed by the noise than peak values used by the HAF-based method. Numerical evaluation shows the proposed method can handle the hybrid FM-PPS signal with low sinusoidal frequency and improve estimation accuracy in terms of mean squared error for several orders of magnitude

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

Online voltage prediction using gaussian process regression for fault-tolerant photovoltaic standalone applications

This paper presents a fault detection system for photovoltaic standalone applications based on Gaussian Process Regression (GPR). The installation is a communication repeater from the Confederacion Hidrografica del Ebro (CHE), public institution which manages the hydrographic system of Aragon, Spain. Therefore, fault-tolerance is a mandatory requirement, complex to fulfill since it depends on the meteorology, the state of the batteries and the power demand. To solve it, we propose an online voltage prediction solution where GPR is applied in a real and large dataset of two years to predict the behavior of the installation up to 48 hour. The dataset captures electrical and thermal measures of the lead-acid batteries which sustain the installation. In particular, the crucial aspect to avoid failures is to determine the voltage at the end of the night, so different GPR methods are studied. Firstly, the photovoltaic standalone installation is described, along with the dataset. Then, there is an overview of GPR, emphasizing in the key aspects to deal with real and large datasets. Besides, three online recursive multistep GPR model alternatives are tailored, justifying the selection of the hyperparameters: Regular GPR, Sparse GPR and Multiple Experts (ME) GPR. An exhaustive assessment is performed, validating the results with those obtained by Long Short-Term Memory (LSTM) and Nonlinear Autoregressive Exogenous Model (NARX) networks. A maximum error of 127 mV and 308 mV at the end of the night with Sparse and ME, respectively, corroborates GPR as a promising tool