On the Low-SNR Capacity of Phase-Shift Keying with Hard-Decision Detection

Gursoy, M. Cenk

doi:10.1109/isit.2007.4557221

Cited by 8 publications

(2 citation statements)

References 10 publications

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“…This also provides an asymptotic upper bound on the performance degradation of optimal combining relative to ideal receive beamforming. Our results for QAM can be viewed as a generalization of classical results on the hard decision penalty for binary communication in [1]- [3], while our results for larger PSK alphabets draw on the relatively recent low-SNR analysis in [4]. Prior work: There is a large body of related literature dating back more than three decades on the broad subjects of "multiterminal inference" [5]- [7], "distributed hypothesis testing" [8]- [10], and "distributed detection" [11]- [15].…”

supporting

confidence: 55%

Distributed Reception with Hard Decision Exchanges

Brown

Madhow

et al. 2014

IEEE Trans. Wireless Commun.

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Abstract-This paper considers the problem of jointly processing messages received over a forward link from a single distant transmitter to a cooperative receive cluster connected by a local area network with finite available throughput. For N cooperating receivers, ideal distributed receive beamforming with direct exchange of unquantized observations leads to an Nfold gain in signal-to-noise ratio (SNR) for equal-gain additive white Gaussian noise channels, with significant additional gains over fading channels due to diversity. It is shown in this paper that a significant portion of these gains can be obtained simply by exchanging hard decisions among some or all of the nodes in the receive cluster. Mutual information computations and simulations of LDPC-coded systems show that optimal combining of hard decisions tends to perform within 0.5-2 dB of ideal receive beamforming. For the low per-node SNR regime of interest with large receive clusters, asymptotic analysis of a suboptimal combining technique termed "pseudo-beamforming" shows that distributed reception with hard decision exchanges performs within 1-2 dB of ideal receive beamforming.

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supporting

confidence: 55%

Distributed Reception with Hard Decision Exchanges

Brown

Madhow

et al. 2014

IEEE Trans. Wireless Commun.

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“…The SIMULINK models made and the MATLAB algorithms done take into account the presence of environmental factors which may affect the output signal of the modulation schemes which is why the use of the Additive White Gaussian Noise Channel is a must in the simulation of the BPSK system or any digital communication system as it emulates the noise due to natural environmental factors [25]. Without the use of such artificial components which can simulate what can affect the system in actuality can hinder the accuracy of the resulting output signal as well as give a false reading on its practicality.…”

Section: Theoretical Considerationsmentioning

confidence: 99%

Binary Phase Shift Keying Simulation with MATLAB and SIMULINK

Africa¹

2020

IJETER

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Digital Communication follows one fundamental concept and it is the transfer of information from one point to another over an analog channel. In our modern society there is one method which is versatile and widely used in transferring digital data and this method is called Digital Phase Modulation. In Digital Phase Modulation it is possible to use discrete values in the carrier frequency or amplitude in order to represent their values in ones and zeros. Given this possibility, it can be concluded that it is also possible to represent digital data using phase. Such technique is called Phase Shift Keying. The easiest approach to Phase Shift Keying is the Binary Phase Shift keying or BPSK. In Binary Phase Shift Keying, hinted from the keyword binary, it uses only two phases with each used for logic high and logic low which can be represented with a minimum and maximum value of 0 degrees for logic low and 180 degrees for logic high. This Modulation Technique utilizes a balance modulator which consists of a carrier sine wave and a binary sequence which is to be used as input in order to generate the Phase Shift Keying Output desired.

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SNR Estimation in Communication Systems Using Cognitive Radio

Turkben

Al-Akraa

2022

2022 5th International Conference on Engineering Technology and Its Applications (IICETA)

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On the Low-SNR Capacity of Phase-Shift Keying with Hard-Decision Detection

Cited by 8 publications

References 10 publications

Distributed Reception with Hard Decision Exchanges

Distributed Reception with Hard Decision Exchanges

Binary Phase Shift Keying Simulation with MATLAB and SIMULINK

SNR Estimation in Communication Systems Using Cognitive Radio

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