Constant-Composition Codes for Maximum Likelihood Detection Without CSI in Diffusive Molecular Communications

Jamali V, Ahmadzadeh A, Farsad N, Schober R (2018)


Publication Language: English

Publication Type: Journal article

Publication year: 2018

Journal

Book Volume: 66

Pages Range: 1981 - 1995

Journal Issue: 5

DOI: 10.1109/TCOMM.2018.2796612

Abstract

Instantaneous or statistical channel state information (CSI) is needed for most detection schemes developed for molecular communication (MC) systems. Since the MC channel changes over time, e.g., due to variations in the velocity of flow, the temperature, or the distance between transmitter and receiver, CSI acquisition has to be conducted repeatedly to keep track of CSI variations. Frequent CSI acquisition may entail a large overhead whereas infrequent CSI acquisition may result in a low CSI estimation accuracy. To overcome these challenges, we design codes which enable maximum likelihood sequence detection at the receiver without instantaneous or statistical CSI. In particular, assuming concentration shift keying modulation, we show that a class of codes, known as constant-composition (CC) codes, enables optimal CSI-free sequence detection at the expense of a decrease in data rate. We analyze the code rate, the error rate, and the average number of released molecules for the adopted CC codes. In addition, we study the properties of binary CC codes and balanced CC codes in further detail. Simulation results verify our analytical derivations and reveal that CC codes with CSI-free detection outperform uncoded transmission with optimal coherent and noncoherent detection.

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APA:

Jamali, V., Ahmadzadeh, A., Farsad, N., & Schober, R. (2018). Constant-Composition Codes for Maximum Likelihood Detection Without CSI in Diffusive Molecular Communications. IEEE Transactions on Communications, 66(5), 1981 - 1995. https://doi.org/10.1109/TCOMM.2018.2796612

MLA:

Jamali, Vahid, et al. "Constant-Composition Codes for Maximum Likelihood Detection Without CSI in Diffusive Molecular Communications." IEEE Transactions on Communications 66.5 (2018): 1981 - 1995.

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