TY - GEN
T1 - Sum-Capacity-Achieving Distributions in the Input-Dependent Gaussian Noise Optical Multiple Access Channel with Peak and Average Intensity Constraints
AU - Soltani, Morteza
AU - Rezki, Zouheir
AU - Chaaban, Anas
N1 - KAUST Repository Item: Exported on 2022-06-30
Acknowledged KAUST grant number(s): OSR-2016-CRG5-2958-01
Acknowledgements: This work has been supported by King Abdullah University of Science and Technology (KAUST), under a competitive research grant (CRG) OSR-2016-CRG5-2958-01.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.
PY - 2019/12/12
Y1 - 2019/12/12
N2 - This paper introduces a two-user discrete-time input-dependent Gaussian noise optical multiple access channel (OMAC) which is applicable to a number of optical wireless links, most notably space optical communications as well as visible light communications. Under nonnegativity and peak intensity constraints, it is shown that generating the code-books of both users according to discrete distributions with finite supports achieves the largest sum-rate in the network. In other words, sum-capacity-achieving distributions for this channel are discrete with a finite number of mass points.
AB - This paper introduces a two-user discrete-time input-dependent Gaussian noise optical multiple access channel (OMAC) which is applicable to a number of optical wireless links, most notably space optical communications as well as visible light communications. Under nonnegativity and peak intensity constraints, it is shown that generating the code-books of both users according to discrete distributions with finite supports achieves the largest sum-rate in the network. In other words, sum-capacity-achieving distributions for this channel are discrete with a finite number of mass points.
UR - http://hdl.handle.net/10754/679472
UR - https://ieeexplore.ieee.org/document/8929914/
UR - http://www.scopus.com/inward/record.url?scp=85078033400&partnerID=8YFLogxK
U2 - 10.1109/CWIT.2019.8929914
DO - 10.1109/CWIT.2019.8929914
M3 - Conference contribution
SN - 9781728109541
BT - 2019 16th Canadian Workshop on Information Theory (CWIT)
PB - IEEE
ER -