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On the Probability of Erasure for MIMO-OFDM

Authors

  • Kasturi Vasudevan Email ORCID Indian Institute of Technology Kanpur, India
  • A. Phani Kumar Reddy Indian Institute of Technology Kanpur, India
  • Gyanesh Kumar Pathak Indian Institute of Technology Kanpur, India
  • Shivani Singh Indian Institute of Technology Kanpur, India

DOI:

https://doi.org/10.30564/ssid.v2i1.1689
Received: 6 February 2020 | Published Online: 30 April 2020

Abstract

Detecting the presence of a valid signal is an important task of a telecom
munication receiver. When the receiver is unable to detect the presence of
a valid signal, due to noise and fading, it is referred to as an erasure. This
work deals with the probability of erasure computation for orthogonal
frequency division multiplexed (OFDM) signals used by multiple input
multiple output (MIMO) systems. The theoretical results are validated by
computer simulations. OFDM is widely used in present day wireless com
munication systems due to its ability to mitigate intersymbol interference
(ISI) caused by frequency selective fading channels. MIMO systems offer
the advantage of spatial multiplexing, resulting in increased bit-rate, which
is the main requirement of the recent wireless standards like 5G and be
yond.

Keywords:

Frequency selective fading, ISI, Millimeter-wave, MIMO, OFDM, Preamble, Probability of erasure

References

[1] K. Vasudevan, K. Madhu, Shivani Singh. Data Detection in Single User Massive MIMO Using Re-Transmissions. The Open Signal Processing Journal, 2019, 6: 15-26. https://opensignalprocessingjournal.com/VOLUME/6/PAGE/15/

[2] K. Vasudevan, K. Madhu, Shivani Singh. Scilab Code for Data Detection in Single User Massive MIMO Using Re-Transmissions. The Open Signal Processing Journal, 2019. https://codeocean.com/capsule/6552386/tree/v1

[3] K. Vasudevan. Coherent Detection of Turbo-Coded OFDM Signals Transmitted Through Frequency Selective Rayleigh Fading Channels with Receiver Diversity and Increased Throughput. Wireless Personal Communications, 2015, 82: 1623–1642. http://dx.doi.org/10.1007/s11277-015-2303-8

[4] K. Vasudevan. Digital Communications and Signal Processing, Second edition (CDROM included). Universities Press (India), Hyderabad, 2010. http://www.universitiespress.com/

[5] K. Vasudevan. Coherent detection of turbo coded OFDM signals transmitted through frequency selective Rayleigh fading channels. 1-6 In Signal Processing, Computing and Control (ISPCC), 2013 IEEE International Conference on, 2013. https://ieeexplore.ieee.org/document/6663392/

[6] K. Vasudevan. Scilab Code for Coherent detection of turbo coded OFDM signals transmitted through frequency selective Rayleigh fading channels. 2013 IEEE International Conference on Signal Processing, Computing and Control (ISPCC), 2019. https://codeocean.com/capsule/9256060/tree/v1

[7] K. Vasudevan. Coherent Turbo Coded MIMO OFDM. 91-99 In ICWMC 2016, The 12th International Conference on Wireless and Mobile Communications, 2016.

[8] K. Vasudevan. Near Capacity Signaling over Fading Channels using Coherent Turbo Coded OFDM and Massive MIMO. International Journal On Advances in Telecommunications, 2017, 10: 22-37.

[9] K. Vasudevan, Shivani Singh, A. Phani Kumar Reddy. Coherent Receiver for Turbo Coded Single-User Massive MIMO-OFDM with Retransmissions. 1-21 In Multiplexing. IntechOpen, 2019. http://dx.doi.org/10.5772/intechopen.85893

[10] K. Vasudevan, Shivani Singh, A. Phani Kumar Reddy. Scilab Code for Coherent Receiver for Turbo Coded Single-User Massive MIMO-OFDM with Retransmissions. Multiplexing [Working Title], 2019.https://codeocean.com/capsule/1694839/tree/v1

[11] John G. Proakis. Digital Communications. McGraw Hill, 1995.

[12] A. Papoulis. Probability, Random Variables and Stochastic Processes. McGraw-Hill, 1991.

[13] K. Vasudevan. Analog Communications: Problems & Solutions. Ane Books, 2018.

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