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

Chaaban, Anas; Rezki, Zouheir; Alouini, Mohamed‐Slim

doi:10.1109/tcomm.2018.2841903

Cited by 22 publications

(34 citation statements)

References 40 publications

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“…The works most related to ours are [9], [10], [15]. For the MISO case, [9], [10] show that the optimal signaling strategy is to rely as much as possible on antennas with larger channel gains.…”

Section: Introductionmentioning

confidence: 69%

“…♦ We now generalize Example 2 to formally solve the optimization problem in (15) for an arbitrary n T × n R channel matrix H. To this end, we need some further definitions. Denote by U the set of all choices of n R columns of H that are linearly independent:…”

Section: Minimum-energy Signalingmentioning

confidence: 99%

“…IM-DD systems have been extensively studied in recent years [1]- [15], with an increasing interest in multiple-input multiple-output (MIMO) systems where transmitters are equipped with n T > 1 LEDs or LDs and receivers with n R > 1 photo detectors. Practical transmission schemes for such systems with different modulation methods, such as pulse-position modulation or LED index modulation based on orthogonal frequencydivision multiplexing, were presented in [16]- [18].…”

Section: Introductionmentioning

confidence: 99%

“…In [15], the asymptotic capacity in the low-SNR regime is considered for general MIMO channels under both a peak-and an average-power constraint. It is shown that the asymptotically-optimal input distribution in the low-SNR regime puts the antennas in a certain order, and assigns positive mass points only to input vectors in {0, A} n T in such a way that, if a given input antenna is set to full power A, then also all preceding antennas in the specified order are set to A.…”

Section: Introductionmentioning

confidence: 99%

“…3. Maximizing the Trace of the Covariance Matrix: The low-SNR slope of the capacity of the MIMO channel is determined by the trace of the covariance matrix ofX [15]. Lemmas 9, 10, and 11 establish several properties for the optimal input distribution that maximizes this trace.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

On the Capacity of MIMO Optical Wireless Channels

Li¹,

Moser²,

Wang³

et al. 2018

2018 IEEE Information Theory Workshop (ITW)

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This paper studies the capacity of a general multiple-input multiple-output (MIMO) free-space optical intensity channel under a per-input-antenna peak-power constraint and a total average-power constraint over all input antennas. The main focus is on the scenario with more transmit than receive antennas. In this scenario, different input vectors can yield identical distributions at the output, when they result in the same image vector under multiplication by the channel matrix. We first determine the most energy-efficient input vectors that attain each of these image vectors. Based on this, we derive an equivalent capacity expression in terms of the image vector, and establish new lower and upper bounds on the capacity of this channel. The bounds match when the signal-to-noise ratio (SNR) tends to infinity, establishing the high-SNR asymptotic capacity. We also characterize the low-SNR slope of the capacity of this channel.

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Section: Introductionmentioning

confidence: 69%

Section: Minimum-energy Signalingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

On the Capacity of MIMO Optical Wireless Channels

Li¹,

Moser²,

Wang³

et al. 2018

2018 IEEE Information Theory Workshop (ITW)

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On Optimizing VLC Networks for Downlink Multi-User Transmission: A Survey

Obeed

Salhab

Alouini

et al. 2019

IEEE Commun. Surv. Tutorials

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193

101

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The evolving explosion in high data rate services and applications will soon require the use of untapped, abundant unregulated spectrum of the visible light for communications to adequately meet the demands of the fifth-generation (5G) mobile technologies. Radio-frequency (RF) networks are proving to be scarce to cover the escalation in data rate services. Visible light communication (VLC) has emerged as a great potential solution, either in replacement of, or complement to, existing RF networks, to support the projected traffic demands. Despite of the prolific advantages of VLC networks, VLC faces many challenges that must be resolved in the near future to achieve a full standardization and to be integrated to future wireless systems.Here, we review the new, emerging research in the field of VLC networks and lay out the challenges, technological solutions, and future work predictions. Specifically, we first review the VLC channel capacity derivation, discuss the performance metrics and the associated variables; the optimization of VLC networks are also discussed, including resources and power allocation techniques, user-to-access point (AP) association and APs-toclustered-users-association, APs coordination techniques, nonorthogonal multiple access (NOMA) VLC networks, simultaneous energy harvesting and information transmission using the visible light, and the security issue in VLC networks. Finally, we propose several open research problems to optimize the various VLC networks by maximizing either the sum rate, fairness, energy efficiency, secrecy rate, or harvested energy.

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