Detection of direct sequence spread spectrum transmissions without prior knowledge

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Detection of Direct Sequence Spread Spectrum Transmissions without Prior Knowledge

Abstract – Direct sequence spread spectrum transmissions (DS-SS) are now widely used for secure communications, as well as for multiple access. Since the transmission uses a large bandwidth, the power spectral density of a DS-SS signal can be below the noise level. Hence, such a signal is difficult to detect. In this paper, we propose a method which is able to detect a spread spectrum signal hidden in the noise. The method does not require a priori knowledge about the spreading sequence used by the transmitter. It is based on two parallel computations: the “theoretical path”, in which we compute the theoretical behavior of the fluctuations of second order moments estimators in the case noise alone is present, and the “experimental path”, in which we compute the actual fluctuations. When a DS-SS signal is hidden in the noise, the results provided by both paths diverge, hence the presence of the signal is detected. Experimental results show that the method can detect a signal far below the noise level. I

Optimal Minimum Distance-Based Precoder for MIMO Spatial Multiplexing Systems

International audienceWe describe a new precoder based on optimization of the minimum Euclidean distance dmin between signal points at the receiver side and for use in multiple-input multiple-output (MIMO) spatial multiplexing systems. Assuming that channel state information (CSI) can be made available at the transmitter, the three steps noise whitening, channel diagonalization and dimension reduction, currently used in investigations on MIMO systems, are performed. Thanks to this representation, an optimal dmin precoder is derived in the case of two different transmitted data streams. For QPSK modulation, a numerical approach shows that the precoder design depends on the channel characteristics. Comparisons with maximum SNR strategy and other precoders based on criteria such as water-filling (WF), minimum mean square error (MMSE) and maximization of the minimum singular value of the global channel matrix are performed to illustrate the significant bit-error-rate (BER) improvement of the proposed precoder

Soft vs. hard antenna selection based on the minimum distance for MIMO systems

International audienceAssuming that Channel State Information (CSI) can be available at the transmitter, we provide a simplified representation of Multi-Input Multi-Output (MIMO) systems and derive a new precoder which maximizes the smallest distance between the received symbols. When the number of transmit antennas nt is greater than the number of transmit data streams b, Heath and Paulraj have proposed a ”hard” antenna selection (or switch precoder) which consists in choosing the best b (among nt) antennas of the transmitter according to the criterion based on the minimum distance. Using the same criterion, we propose in this paper a ”soft” (or linear) precoder that performs power allocation among the transmit antennas. Comparisons in term of Bit Error Rate (BER) between switch and linear precoders are performed considering b=2 independent data streams, a QPSK modulation and the Maximum Likelihood (ML) receiver

Blind estimation of scrambler offset using encoder redundancy

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Minimum Ber Diagonal Precoder For Mimo Systems

We report on a simplified representation of Multi-Input Multi-Output (MIMO) systems and propose a Minimum Bit Error Rate (MBER) diagonal precoder. Assuming that channel information can be available at the transmitter, we show that the proposed representation decouples the MIMO channel into parallel subchannels, which greatly facilitates and speeds up further processing. Using traditional criteria such as the minimum mean square error (MMSE) and the maximum capacity, eigen diagonal precoders and decoders can be obtained, leading to the same transmit and receive filters as those reported in the literature but in a simpler and faster way. A new diagonal precoder is also derived using the minimum bit error rate (MBER) criterion and compared to the others in term of bit error rate and achieved capacity. An approximation of the MBER precoder (AMBER) is finally proposed, whose performances remain close to the optimal in spite of its low complexity

Digital transmission combining BLAST and OFDM concepts: experimentation on the UHF COST 207 channel

International audienceRecent papers have shown that multipath wireless channels are capable of enormous capacities, provided that the multipath scattering is sufficiently rich and is properly exploited. A layered space-time architecture, known as BLAST, has been proposed. A basic hypothesis made by the BLAST algorithm is that the symbol period is large compared to the maximum echo delay (hence, the data rate cannot be too high). In this paper, we use an approach that combines BLAST and OFDM. Its interest is to suppress the data rate constraint. First, the symbols are packed into matrices; then matrix manipulations prior to BLAST transmission provide a transmission system which is theoretically equivalent to many independent BLAST channels. Results obtained with the UHF COST 207 channel corresponding to GSM transmission in urban area are provided and discussed

Minimum BER diagonal precoder for MIMO digital transmissions

International audienceWe propose a Minimum Bit Error Rate (MBER) diagonal Precoder for Multi-Input Multi-Output (MIMO)transmission systems. This work is based on previous results obtained by Sampath et al.[1] in which the global transmission system (precoder and equalizer) is optimized with the Minimum Mean Square Error (MMSE) criterion. This process leads to an interesting diagonality property which decouples the MIMO channel into parallel and independent data streams and allows to perform an easy ML detection. This system is then optimized using a new diagonal precoder that minimizes the BER. Our work is motivated by the fact that, from a practical point of view, people are likely to prefer a system that minimizes the BER rather than the Mean Square Error. The performance improvement is illustrated via Monte Carlo simulations using a Quadratic Amplitude Modulation (QAM)