Probability Of Wrong Detection Research Articles

Selection of Parity Check Equations For the Iterative Message-Passing Detection of M-Sequences

We consider the joint detection and decoding of m-sequences. The receiver has to decide whether an m-sequence is received and possibly to decode its initial state. To do so, it implements an iterative message-passing decoding algorithm that operates on a parity check matrix, built upon a number of reference parity-check equations satisfied by the m-sequence. This matrix concatenates several elementary parity check matrices which are derived from reference equations. Unlike the conventional decoding case, the detection problem imposes to consider false alarms that may occur when the decoder is only fed with noise. While absorbing sets are known to be responsible for the error floor phenomenon of iterative message-passing decoders, we show that they may have a beneficial effect on the detection performance, in that they may prevent the decoder to produce false alarms. We further compute the number of hybrid cycles of length six and eight in the Tanner graph of the decoder and use the minimization of this number as criterion to derive an algorithm for selecting the reference parity check equations. This algorithm was found to be efficient for minimizing the probability of false alarm and decreases also the probability of wrong detection in the very small SNR region. This has been achieved at the cost of a reduction of the probability of correct detection.

Performance improvement of spatial modulation-assisted FSO systems over Gamma–Gamma fading channels with geometric spreading

A number of studies recently have proposed optical spatial modulation (SM) as a simple, power- and bandwidth efficient modulation scheme for free-space optical communication (FSO) systems. In these studies, it was assumed that an active laser source only sends the signal to one targeted photodetector (PD). However, undesirable PDs still can receive the signal from the active source due to geometric spreading (i.e., laser beam broadening). In addition, if the fading channels between the active source and multiple PDs are correlated, the probability of wrong detection of the active source’s index during spatial demodulation process may increase. In this paper, we first analyze the impact of geometric spreading on the performance of FSO systems using SM over uncorrelated Gamma–Gamma fading channel. We find that the advantage in reducing the transmission bandwidth of SM cannot compensate its limitation in suffering from geometric spreading. We then propose to combine N-SM with pulse-position modulation (L-PPM) and transmit diversity (\(M\,\times \,1\) MISO) to improve the performance of SM-based FSO systems. The numerical results, which are validated by Monte–Carlo simulations, confirm the superiority of the proposed system in comparison with the conventional ones.

HTRCI and Channel Ranking Based Joint Symbols Detection for MQRD-PCM/MIMO-OFDM

MIMO-OFDM is considered a key technology in emerging high-data rate systems. In MIMO-OFDM systems, channel estimation and signal detection are important to distinguish transmit signals from multiple transmit antennas. Previously, we have proposed a parallel detection algorithm using multiple QR decompositions (Q is an orthogonal square matrix, R is upper triangular matrix) with permuted channel matrix (MQRD-PCM) to reduce the system complexity of MIMO-OFDM. This method achieves a good BER performance with a low system complexity. However, since MQRD-PCM is a kind of parallel detection method, the wrong detection probability is increased due to the bad channel signal-to-interference plus noise power ratio (SINR) of the transmitted signals. As a result, the average BER performance is influenced by the wrong detection probability of the bad channel SINR. To overcome the above-mentioned problems, in this paper, we propose the high time resolution carrier interferometry and channel ranking based joint signal detection for MQRD-PCM/MIMO-OFDM.

Performance Enhancement of MQRD-PCM/MIMO-OFDM Using Channel Ranking Based Joint Symbols Detection

MIMO-OFDM is considered a key technology in emerging high-data rate systems. With MIMO techniques, the transmission quality deteriorates due to inter-antenna interference (IAI). Several signal detection schemes have been proposed to mitigate this problem. However, it is impractical to use the conventional methods without reducing theirs computational complexity. Previously, we have proposed a parallel detection algorithm using multiple QR decompositions with permuted channel matrix (MQRD-PCM) for MIMO-OFDM to reduce the system complexity. This method achieves a good BER performance with low system complexity. However, since MQRD-PCM is a kind of parallel detection method, the wrong detection probability is increased due to the bad channel SINR of the transmitted signal. As a result, the average BER performance is influenced by the wrong detection probability of the bad channel SINR. To overcome this problem, in this paper, we propose the channel ranking based joint symbols detection for MQRD-PCM/MIMO-OFDM.

Model selection for canonical correlation analysis

In this paper, we study a general criterion for estimating the rank of canonical correlation matrix (CCM). Besides the strong consistency, we give the exponential-type bounds under certain conditions on the probability of wrong detection of the rank of CCM. On the basis of this criterion, we give two methods to determine the multiplicities of canonical correlation coefficients. And the strong consistency of them is established.

Estimating the number of sinusoids in additive white noise

In this article we propose a simple method for estimating the number of sinusoids in additive noise by using the penalty function approach. We establish the strong consistency of the proposed method under the assumption of independent and identically distributed random errors. We also provide an upper bound of the probability of wrong detection under the same assumptions.

On rates of convergence of general information criteria in signal processing when the noise covariance matrix is arbitrary

The authors give exponential-type bounds on the probabilities of detection error under certain conditions. The bounds tend to zero rapidly as the sample size increases. These procedures are referred to as general information criterion (GIC) procedures since each is consistent and, under certain conditions, the rate of convergence of the estimate of the number of signals to the true value is rapid. The authors give bounds on the probability of wrong detection of the GIC procedure when the noise variance is unknown. Upper bounds on the probabilities of detection error are also obtained. >