Capacity Bounds for Wireless Optical Intensity Channels With Gaussian Noise

Farid, A.A.; Hranilovic, Steve

doi:10.1109/tit.2010.2080470

Cited by 125 publications

(108 citation statements)

References 14 publications

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“…Studying the capacity of this channel is important for understanding the fundamental limits of OWC, which has witnessed increasing attention recently, see [2], [7]- [10] and references therein. In this context, the capacity of the singleinput single-output (SISO) IM-DD channel has been studied in [4], [11], [12]. The SISO IM-DD channel with input-dependent (relative intensity) Gaussian noise has been studied in [5].…”

Section: Introductionmentioning

confidence: 99%

Low-SNR Asymptotic Capacity of MIMO Optical Intensity Channels with Peak and Average Constraints

Chaaban

Rezki

Alouini

2018

IEEE Trans. Commun.

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Abstract-The low-SNR asymptotic capacity of the multipleinput multiple-output (MIMO) optical intensity channel is studied under both average and peak intensity constraints. We focus on low SNR, which can be modeled as the scenario where both constraints proportionally vanish, or where the peak constraint is held constant while the average constraint vanishes. A capacity upper bound is derived, and is shown to be tight at low SNR under both scenarios. The capacity achieving input distribution at low SNR is shown to be a maximally-correlated vectorbinary input distribution. Consequently, the low-SNR capacity of the channel is characterized. As a byproduct, it is shown that for a channel with peak intensity constraints only, or with peak intensity constraints and individual (per aperture) average intensity constraints, a simple scheme composed of coded onoff keying, spatial repetition, and maximum-ratio combining is optimal at low SNR.

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Section: Introductionmentioning

confidence: 99%

Low-SNR Asymptotic Capacity of MIMO Optical Intensity Channels with Peak and Average Constraints

Chaaban

Rezki

Alouini

2018

IEEE Trans. Commun.

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“…The derived upper bound is improved over the previous spherepacking upper bounds in [8], [9] but not over the upper bound in [3]. The upper bound in [3] has the advantage over the sphere-packing upper bounds that no optimization is required in calculation.…”

Section: Introductionmentioning

confidence: 81%

“…Proof: According to (9) and (10), the upper bound can be obtained by the inequality (13), where we define ζ = {c ∈ R|0 ≤ c ≤ 1} and the value of σ cm and δ cm are calculated in Appendix C and D, respectively.…”

Section: Derivation Of the Upper Bound On Optical Channel Capacitymentioning

confidence: 99%

“…It should be pointed out that our upper bound and the previous sphere-packing upper bounds in [8], [9] are all derived using the Steiner-Minkowski formula. The difference lies in the approximation method for the intrinsic volumes of the simplex, which eventually leads to the different performance in some OSNR region.…”

Section: Derivation Of the Upper Bound On Optical Channel Capacitymentioning

confidence: 99%

“…Based on the wellknown sphere packing method [7], tight closed-form upper bounds are derived in [8], [9]. However, there is an obvious gap between these upper bounds and the lower bound in high optical signal-to-noise ratios (OSNRs) region.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Tight Upper Bound on Channel Capacity for Visible Light Communications

et al. 2016

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Abstract-Since the optical wireless channel in visible light communication (VLC) systems is subject to the nonnegativity of the signal and the average optical power, the classic Shannon channel capacity formula is not applicable to VLC systems. To derive a simple closed-form upper bound on channel capacity, sphere packing argument method has been applied previously. However, there is an obvious gap between the existing spherepacking upper bounds and the lower bounds at high optical signal-to-noise-ratios (OSNRs), which is mainly caused by the inaccurate mathematical approximation of the intrinsic volumes of the simplex. In this letter, a tight sphere-packing upper bound is derived with a new approximation method. Numerical results demonstrate that compared to the existing sphere-packing upper bounds, our proposed upper bound is tighter at high OSNRs.

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