A model-based estimator-correlator (EC) structure

Ricker, Dennis W.; Cutezo, A.J.

doi:10.1109/78.869023

Cited by 5 publications

(6 citation statements)

References 14 publications

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“…The estimator-correlator (EC) cross-correlates the received signal with an estimate of the channel output signal corresponding to each possible transmitted signal [42], [43]. The signal at channel output is estimated with a minimum mean square error (MMSE) estimator from the knowledge of the received signal and the second order statistics of the channel and noise.…”

Section: B Related Workmentioning

confidence: 99%

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Direct Data Detection of OFDM Signals Over Wireless Channels

Saci

Al-Dweik

Shami

2020

IEEE Trans. Veh. Technol.

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This paper presents a novel efficient receiver design for wireless communication systems that incorporate orthogonal frequency division multiplexing (OFDM) transmission. The proposed receiver does not require channel estimation or equalization to perform coherent data detection. Instead, channel estimation, equalization, and data detection are combined into a single operation, and hence, the detector performs a direct data detector (D 3). The D 3 is applied to key practical wireless systems such as the Long Term Evolution (LTE) and the New Radio (NR) of the fifthgeneration (5G) system. The performance of the proposed D 3 is thoroughly analyzed theoretically in terms of bit error rate (BER), where closed-form accurate approximations are derived for several cases of interest, and validated by Monte Carlo simulations. Moreover, extensive complexity analysis are performed to evaluate the system suitability for implementation. The obtained theoretical and simulation results demonstrate that the BER of the proposed D 3 is only 3 dB away from coherent detectors with perfect knowledge of the channel state information (CSI) in flat and frequency-selective fading channels for a wide range of signal-to-noise ratios (SNRs). If CSI is not known perfectly, then D 3 outperforms the coherent detector substantially, particularly at high SNRs with linear interpolation. The computational complexity of D 3 depends on the length of the sequence to be detected, nevertheless, a significant complexity reduction can be achieved using the Viterbi algorithm.

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Section: B Related Workmentioning

confidence: 99%

“…In practical systems, the number of bits in the detected sequence is generally not large, which implies that the upper and lower bounds in (42) are relatively tight, and hence, the BER can be approximated as the middle point between the two bounds as,…”

Section: A Single-sided Pilotmentioning

confidence: 99%

Direct Data Detection of OFDM Signals Over Wireless Channels

Saci

Al-Dweik

Shami

2020

IEEE Trans. Veh. Technol.

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“…when the scattering is uncorrelated [9]. The elements of the vector Â(p) are the uncertainty functions…”

Section: The Linear Spreading Modelmentioning

confidence: 99%

“…Consequently with complete SF information it is possible to define the signal-to-interference ratio (SIR) for each filter realization in the delay-Doppler phase plane. These SIRs are used to compute the optimal weighting for the incoherent summation [9].…”

Section: Introductionmentioning

confidence: 99%

Detection by incoherent recombination with partial information

Ricker

Cutezo²

2001

IEEE Trans. Aerosp. Electron. Syst.

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Matched filter (MF) detection in spread environmentsis often seriously degraded by the mismatch between the waveform replica and the composite signal formed by the spreading environment. Typically the spreading is caused by multiple delayed reflections due to scatter extent or multipath especially in shallow water sonar applications. It is possible to recover some detector performance by incoherent summation of weighted MF realizations in a process called incoherent recombining (IR). Several IR strategies for Gaussian data that assume varying amounts of prior scattering function (SF) information are examined, their receiver operating characteristics (ROCs) computed, and compared with those of the unrealizable "prescient" receiver (PR). They include optimally weighted and unweighted versions of the maximum likelihood estimator-correlator (EC), and variations of the "at-least-one" (ALO) detector that examines sequences of MF realizations declaring a detection if at least one threshold is crossed. As might be expected, performance improves with the accuracy of the prior information incorporated in the detector formulation. He has conducted research on active sonar echolocation for 31 years with emphasis in detection and estimation, high resolution sonar imaging, scattering functions, waveform design, and wideband (wavelet) processing of sonar signals. His most recent work has been on techniques for echo detection and classification of sonar echos in spread channels based upon their space-time correlative properties. Dr. Ricker has issued over 275 reports and published extensively in IEEE Transactions, JASA, and JUA on various aspects of signal processing and echo location. He holds two patents in the signal processing area. Anthony J. Cutezo received the B.S.E.E. degree from the Pennsylvania State University (PSU), University Park, in 1975 and the M.S.E.E. degree from PSU in 1990.He has been with the Applied Research Laboratory at PSU since 1985 and is currently an Associate Research Engineer engaged in signal processing research. His interests include statistical detection and parameter estimation.

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“…The estimator-correlator (EC) cross-correlates the received signal with an estimate of the channel output signal corresponding to each possible transmitted signal [32], [33]. The signal at channel output is estimated with a minimum mean square error (MMSE) estimator from the knowledge of the received signal and the second order statistics of the channel and noise.…”

Section: Introductionmentioning

confidence: 99%

Direct Data Detection of OFDM Signals Over Wireless Channels

Saci¹,

Al-Dweik²,

Shami³

2019

Preprint

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This paper presents a novel efficient receiver design for wireless communication systems that incorporate orthogonal frequency division multiplexing (OFDM) transmission. The proposed receiver does not require channel estimation or equalization to perform coherent data detection. Instead, channel estimation, equalization, and data detection are combined into a single operation, and hence, the detector is denoted as a direct data detector (D 3 ). The performance of the proposed system is thoroughly analyzed theoretically in terms of bit error rate (BER), and validated by Monte Carlo simulations. The obtained theoretical and simulation results demonstrate that the BER of the proposed D 3 is only 3 dB away from coherent detectors with perfect knowledge of the channel state information (CSI) in flat fading channels, and similarly in frequencyselective channels for a wide range of signal-to-noise ratios (SNRs). If CSI is not known perfectly, then the D 3 outperforms the coherent detector substantially, particularly at high SNRs with linear interpolation. The computational complexity of the D 3 depends on the length of the sequence to be detected, nevertheless, a significant complexity reduction can be achieved using the Viterbi algorithm.

show abstract

A model-based estimator-correlator (EC) structure

Cited by 5 publications

References 14 publications

Direct Data Detection of OFDM Signals Over Wireless Channels

Direct Data Detection of OFDM Signals Over Wireless Channels

Detection by incoherent recombination with partial information

Direct Data Detection of OFDM Signals Over Wireless Channels

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