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Visible light communication (VLC) has emerged as a secure, cost-effective, and green supplement to the existing radio frequency (RF) communication systems. However, the performance of a typical VLC link is degraded by the following factors: (a) inter-symbol interference (ISI), which arises due to limited modulation bandwidth of light-emitting diode (LED), (b) the dispersion due to multi-path reflections, and (c) nonlinear transfer characteristics of LED. To mitigate ISI and LED nonlinearity, existing blind post-distorters, like the Volterra modified cascaded multimodulus algorithm (MCMMA) and the Hammerstein improved multistage clustering (HIMSC) approaches, experience degradations from modeling errors due to abrupt polynomial-series truncation. To mitigate these degradations, we propose a novel random Fourier features (RFF) based improved multi-stage clustering (RFF-IMSC) algorithm for blind post-distortion. Simulations performed over standardized IEEE 802.15 PAN VLC channels indicate that the proposed RFF-RIMSC post-distorter delivers improved performance as compared to the existing blind post-distorters. Also, analytical guarantees are presented and error-rate performance are analyzed for the $\epsilon $ -optimality of this approach with respect to supervised loss-functions.

Nonlinear device characteristics present a severe performance-bottleneck for several upcoming next-generation wireless communication systems and prevent them from delivering high data-rates to the end-users. In this context, reproducing kernel Hilbert space (RKHS) based signal processing methods have gained widespread deployment and have been found to outperform classical polynomial-filtering-based solutions significantly. Furthermore, recent RKHS based techniques that rely on explicit feature-maps called random Fourier features (RFF) have emerged. These techniques alleviate the dependence on learning a dictionary and avoid the computations and errors incurred in dictionary-based learning. However, the performance of existing RKHS based solutions depends on choosing a suitable kernel-width. For the widely-used Gaussian kernel, we propose a methodology of assigning kernel-bandwidths that capitalizes on a stochastic sampling of kernel-widths using an ensemble drawn from a pre-designed probability density function. The technique is found to deliver a comparable convergence/error-rate performance to the scenario when the kernel-width is chosen by brute-force trial and error for tuning it for best performance. The desirable properties of the proposed kernel-sampling technique are supported by analytical proofs and are further highlighted by computer-simulations presented in the form of case studies in the context of next-generation communication systems.

Ultraviolet (UV) communication has emerged as a promising solution for providing non-line-of-sight (NLOS) wireless connectivity due to strong molecular and aerosol scattering at UV wavelength. However, performance of UV based communication systems is severely impaired due to nonlinear transfer-characteristics of light emitting diode (LED), which degrades the overall symbol error rate (SER) performance. In addition, UV based communication systems are also impaired by multiplicative distortion due to turbulence, that causes detrimental instantaneous outages. Hence, in this work, first an expression for the outage probability is derived for a nonlinear UV communication system via analytical characterization of the statistics of the additive distortion. Further, utilizing the proposed analytical model for additive distortion, the error rate of reproducing kernel Hilbert space (RKHS) based detectors is quantified for the nonlinear outdoor NLOS UV channel. Additionally, using the derived expression for error-rate, an RKHS based minimum symbol error rate (MSER) equalizer is formulated to mitigate the distortion due to LED nonlinearity, and to enhance the error-rate performance of the considered nonlinear NLOS UV link. Convergence of the proposed MSER equalizer is analyzed, and improvements in error-rate promised by the proposed equalizer are validated by computer simulations over typical NLOS UV channels.

Visible light communications (VLC) has emerged as a promising technology for the next-generation communication systems. For VLC, several non-orthogonal multiple access (NOMA) techniques have emerged, among which sparse-code multiple access (SCMA) is particularly viable due to promised shaping and coding gain, and typically minimal/no error propagation as compared to power-domain NOMA (PD-NOMA). In this work, we introduce using polychromatic light emitting diodes (LEDs) as transmitters, where several users are overlapped on each color using SCMA; consequently, the SCMA codewords on each color are overlapped in the color-domain before transmission. At the receiver, after color-filtering, the residual color-coupling is removed by inverting the coupling matrix. Finally, the users’ signals over each color-channel are recovered using the message passing algorithm. Further, asymptotic error-rate expressions are derived for the proposed color-domain SCMA. These expressions are validated by simulations assuming VLC channel-models for random waypoint user-mobility. The analytical results promise a potential gain in the sum-rate while supporting a larger number of users as compared to a monochromatic white-LED based SCMA system.

The next-generation of communication systems must be capable of serving a significantly higher traffic generated by a large number of devices. To support massive connectivity over limited time-frequency resources, several non-orthogonal multiple access (NOMA) paradigms have emerged. In this context, sparse code multiple access (SCMA) based NOMA is particularly attractive due to its robustness to error-propagation, and its potentially high coding-gain with appropriate codebook design. However, the performance of SCMA based systems is severely degraded by distortions introduced by non-ideal hardware, e.g. power-amplifier (PA) nonlinearity. To mitigate such artefacts, in this letter, a random Fourier feature (RFF) based hybrid message passing algorithm (MPA) is proposed, and validated through computer simulations. Lastly, an analytical proof is presented that indicates that the use of RFFs significantly improves the convergence of the MPA in the presence of impairments, and renders error-rate performance equivalent to that of a linear Gaussian channel under approximate MPA.

Vehicular visible light communications (VLC) has emerged as a viable supplement for high speed next-generation vehicle to vehicle (V2V) communication systems. However, performance of a V2V-VLC link is impaired due to nonlinear transfer-characteristics of light emitting diodes (LEDs), and inter-symbol interference (ISI). In this article, a low-complexity least-squares based post-distortion algorithm is formulated over reproducing kernel Hilbert space (RKHS) for a multi-hop V2V-VLC link. The impairments encountered in V2V-VLC channels are mitigated in RKHS by a minimum symbol error-rate post-distorter using a low dimensional approximation of random Fourier features (RFF) (which is a soft approximation of the feature-map to RKHS), that facilitates computationally simple post-distortion under finite memory-budget. The convergence and the BER-performance of the proposed post-distorter is analyzed over realistic V2V VLC channels obtained via ray-tracing. From the analysis, and the presented computer-simulations, the proposed post-distorter is found to exhibit equivalent convergence characteristics and error-rate over reasonable distances, with much lower computational complexity. Publisher's Version

Visible light communications (VLC) has emerged as a viable supplement for high speed next-generation communication systems. However, performance of a VLC link is limited by the nonlinear characteristics of light emitting diodes (LEDs), ambient light, and inter-symbol interference (ISI). In this letter, the paradigm of least-squares based post-distortion over reproducing kernel Hilbert spaces (RKHS) is considered for a visible light communication (VLC) link. The performance-limiting impairments (viz. LED nonlinearity, and ISI), are mitigated by random Fourier features (RFF) based least minimum symbol error-rate post-distorter in RKHS, which facilitates post-distortion under finite memory-budget constrained scenarios. Performance of the proposed algorithm is tested over IEEE 802.15r1 PAN VLC channels, and the proposed algorithm is observed to converge significantly faster, whilst supporting higher data rates as compared to the existing RKHS based post-distorters.

Two of the most challenging goals for the fifth generation (5G) and beyond communication systems are massive connectivity and higher capacity. The use of traditional orthogonal multiple access techniques limits the number of users that can be served using available resources due to orthogonality constraint. Moreover, the available resources may not be utilized effectively by alloted users thereby resulting in inefficiency and user unfairness. This imposes a severe drawback in cases where the number of users to be served are high, like in the Internet of Things or ultra-dense 5G networks. Hence, introducing non-orthogonality to multiple access scheme is advocated as a superior methodology to serve multiple users simultaneously, thereby achieving multi-fold enhancement in connectivity. In scenarios with massive number of users, non-orthogonal multiple access scheme (NOMA) increases the number of active connections by superimposing signals of multiple users on the same resource block, thereby also utilizing the available resources efficiently. This article presents an overview of the integration of NOMA with several other leading technologies for 5G and beyond networks to enhance the connectivity.

Visible light communication (VLC) has emerged as a viable supplement to the existing radio frequency based communication systems. However, its performance is severely impaired by a) nonlinear characteristics of light emitting diode (LED), which reduces the Euclidean distance between neighboring constellation points, and b) intersymbol interference (ISI) due to time-dispersive nature of VLC channel, which reduces the eye opening of the received symbols and degrades the bit error rate (BER) performance. In this paper, we propose a novel kernel least mean square (KLMS) with adaptive decision feedback equalizer based post-distorter for VLC for joint mitigation of LED nonlinearity and ISI. In this work, minimum mean square error criterion based joint optimization problem is formulated in a reproducing kernel Hilbert space for optimization of the feedforward and feedback filter coefficients. Simulations indicate that the proposed post-distorter yields better BER performance as compared to existing algorithms.

Visible light communication (VLC) based systems are a viable green supplement to existing radio frequency based communication systems. However, it has been found that the performance of VLC based systems is impaired in conditions when the users are mobile with respect to the transmit luminaire. The relative motion of the mobile users with respect to the luminaire renders the overall VLC channel to be time-varying. Recently, the impact of user mobility on the overall channel impulse response has been modeled by a generalized time-varying VLC channel model, which necessitates for an efficient mechanism at the receiver to tackle this phenomenon. In addition to user mobility, the inter-symbol interference, and the nonlinear characteristics of the light emitting diode are major factors that limit throughput of a VLC-based communication system. To mitigate these impairments, existing techniques such as Volterra/Hammerstein based receivers suffer from modeling error due to truncation of the polynomial kernel till second order terms. Recently, sparse reproducing kernel Hilbert space (RKHS) based methods have been suggested that guarantee universal approximation with the reasonable computational simplicity. However, the choice of a single hyper-parameter restricts its ability to model time-varying channels/systems. Therefore, this paper proposes a novel RKHS based post-distorter that adaptively learns a sparse dictionary based on the incoming observations, and monitors validity of the dictionary based on a proposed metric in RKHS. In order to mitigate the time-varying VLC channel based on this metric, a criterion for clearing the contents of the existing dictionary is proposed, and the requirement to learn a new dictionary is detected. Furthermore, the concept of mixture-adaptive kernel learning is introduced in this work for the minimum symbol error rate (MSER) criterion. From the convergence analysis presented in this paper, faster mean squared error (MSE) convergence is proved for the mixture-kernel based post-distorter. Additionally, it is also proven that for a given step-size, the proposed mixture-kernel MSER post-distorter always converges to a lower MSE as compared to the classical single-kernel MSER.

Massive multiple input multiple output (m-MIMO) visible light communication (VLC) has emerged as a viable technology to enhance the throughput of an existing VLC based systems in order to serve the high speed data requirement for beyond 5G and 6G communication systems. However, performance of m-MIMO VLC is severely impaired by (1) columns of m-MIMO VLC channel are highly correlated which makes the channel matrix ill-conditioned, and (2) nonlinear transfer-characteristics of light emitting diode (LED). The aforementioned channel impairments collectively degrade the overall bit error rate (BER) at the receiver. In this paper, finite memory budget adaptive precoder is proposed to decrease the channel correlation/condition number of MIMO channel matrix. Reproducing kernel Hilbert space (RKHS) based post-distorters have been proposed in the literature for VLC which rely on growing dictionary of kernel evaluations, and hence it is difficult to practically implement them under finite memory budget. In this paper, random Fourier features (RFF) based kernel least mean square (RFF - KLMS) algorithm is proposed for post-distortion over m-MIMO VLC channels which alleviates the requirement of dictionary and facilitates post-distortion under finite memory budget. Computer simulations performed over m-MIMO VLC channels show that the proposed RFF based algorithm exhibit similar BER performance with reduced computational complexity as compared to the dictionary based post-distortion algorithm.

Visible light communication (VLC) is a promising and eco-friendly complementary technology to the existing radio frequency (RF) based communication system. However, the performance of VLC based system is limited by dispersive characteristics of the VLC channel, and restricted modulation bandwidth of light emitting diode (LED). To mitigate the ISI, orthogonal time frequency space (OTFS) modulation is proposed in the literature. However, it has been found that the performance analysis of OTFS over multipath VLC channels has not been investigated. This paper investigates the performance of OTFS over static multipath channels for the VLC system. Simulations performed over the standardized IEEE 802.15.7 VLC channel indicate that OTFS with message passing detector delivers an approximate 6 dB SNR gain at BER of 10 −4 over the conventional orthogonal frequency division multiplexing (OFDM) scheme with minimum mean square error (MMSE) based detector.

Visible light communication (VLC) is eco-friendly and low-cost supplement to the existing radio frequency (RF) based communication system. However, the performance of VLC based system is limited by dispersive characteristics of the VLC channel which leads to inter-symbol-interference (ISI) and inter-carrier-interference (ICI). To alleviate the ISI and ICI, orthogonal time frequency space (OTFS) modulation has been proposed in the literature for both RF and millimeter wave communication systems. However, the performance analysis of OTFS over mobile multipath VLC channels is still an open area to investigate. This paper investigates the performance of OTFS over mobile multipath channels for the VLC system. Simulations performed over the realistic mobile multipath VLC channel indicate that OTFS with message passing detector exhibit better bit error rate over the conventional orthogonal frequency division multiplexing scheme with minimum mean square error based detector.

Multi user massive multiple input multiple output (MU-m-MIMO) has emerged as a viable technology for scaling up existing communication systems, and in serving increasing number of users for the next-generation communication systems. Several signal processing algorithms exist for mitigating the performance-limiting artefacts encountered in MU-m-MIMO systems (like inter-symbol interference, inter-channel interference, and device nonlinearities), among which, reproducing kernel Hilbert space (RKHS) based approaches have emerged to provide effective solutions. However, most of the existing RKHS based detectors for MU-m-MIMO are dictionary-based, which makes it difficult to gauge the memory requirements beforehand, and are prone to error in the presence of noisy observations. Hence, to reduce the computational complexity, a Random Fourier Features (RFF) based parallel detection algorithm is proposed for MU-m-MIMO, that uses decomposed blocks of high dimensional observations, and makes the proposed detector scalable for parallel computation using modern multicore compute-units at the receivers (which is possible today due to advances in computing). Further, the RFF based explicit feature map to RKHS alleviates the requirement of a dictionary, and facilitates ease of practical implementation. Simulations are performed over realistic MU-m-MIMO systems, which indicates that the proposed approach delivers an acceptable uncoded BER performance, whilst maintaining a finite implementation budget, which makes the proposed approach attractive for implementation. Lastly, the error-rate analysis of the proposed detector is performed, and validated through simulations.

Visible light communication (VLC) has emerged as a promising, green, and interference-free supplement to existing radio frequency-based communication systems. To enhance the capacity of existing VLC-based systems, using massive arrays of light emitting diodes (LEDs) at the transmitter and photodiodes at the receiver has been proposed recently, resulting in a massive multiple-input multiple-output (m-MIMO) VLC system. However, by increasing LED array pitch in m-MIMO, the VLC channel matrices are generally ill conditioned which makes them sensitive to small perturbations and degrades the overall bit error rate (BER) performance. To reduce the condition number of the overall channel matrix, a novel precoder using an exponent-based singular value decomposition is proposed for m-MIMO VLC system. Furthermore, a joint optimization problem is formulated to optimize the exponent and to detect symbols iteratively using the minimum symbol error rate criterion. Simulations show that the proposed adaptive precoding technique exhibits superior BER performance over existing techniques. Analytical upper bounds for BER are also derived and validated by simulations.

One of the proposed solutions to meet the ever growing demand for data rates in 5G communication systems is to use large number of antennas (100–1000) in a massive multiple input multiple output (MIMO) communication system. Performing multi-user (MU) detection over massive-MIMO systems presents many challenges, prime among them being: large-dimensionality of the received dataset which can increase the computational complexity of traditional algorithms, and susceptibility to device impairments like power amplifier (PA) nonlinearity. Due to these factors, detection of the users’ symbols over uplink-MU massive-MIMO systems in a fast and computationally efficient way is an open problem. In this work, a reproducing kernel Hilbert space (RKHS) based block symbol detector is proposed for uplink-MU massive-MIMO systems that works on decomposed blocks of the observations, and selectively decides the use of an incoming observation, thereby rendering the detector to be computationally tractable, and robust to PA-nonlinearity encountered in uplink-MU massive-MIMO. Simulations have been carried out in this work that demonstrate superior performance of the proposed approach as compared to batch/iterative least squares based algorithms.

In the context of beyond-5G indoor communication systems, visible light communication (VLC) has emerged as a viable supplement for existing RF-based systems and as an enabler for high datarate communications. However, the existing indoor VLC systems are limited by detrimental outages caused by fluctuations in the VLC channel-gain due to user-mobility. Furthermore, the nonlinear characteristics of the light-emitting diode (LED) degrade the performance of VLC systems in the highpower regime by warping the input constellation. Additional performance-limits are introduced by inter-symbol interference (ISI) due to finite modulation-bandwidth of LEDs, and reflections from walls. In this paper, a random Fourier feature (RFF) based post-distorter is considered for mitigating the LED nonlinearity, and relevant expressions for the signal to noise ratio (SNR) are derived for a direct current biased optical orthogonal frequency division multiplexing (DCO-OFDM) system. Based on the derived expressions for SNR, the effects of user-mobility and ISI are mitigated by a DCO-OFDM based adaptive VLC transmission technique, which varies the transmission-rate/modulation-order under a specified error-rate constraint. Simulations are presented over channels obtained by ray-tracing, which indicates that the proposed algorithm achieves superior data-rates with a significantly lower error-rate. Publisher's Version

Visible light communication (VLC) is one of the main technologies driving the future 5G communication systems due to its ability to support high data rates with low power consumption, thereby facilitating high speed green communications. To further increase the capacity of VLC systems, a technique called non-orthogonal multiple access (NOMA) has been suggested to cater to increasing demand for bandwidth, whereby users’ signals are superimposed prior to transmission and detected at each user equipment using successive interference cancellation. Some recent results on NOMA exist which greatly enhance the achievable capacity as compared with the orthogonal multiple access techniques. However, one of the performance-limiting factors affecting VLC systems is the nonlinear characteristics of a light emitting diode (LED). This paper considers the nonlinear LED characteristics in the design of pre-distorter for cognitive radio inspired NOMA in VLC, and proposes singular value decomposition-based Chebyshev precoding to improve performance of nonlinear multiple-input multiple-output NOMA-VLC. A novel and generalized power allocation strategy is also derived in this paper, which is valid even in scenarios when users experience similar channels. Additionally, in this paper, analytical upper bounds for the bit error rate of the proposed detector are derived for square $M$ -quadrature amplitude modulation.

Multicore Fiber based backhaul network is essential to support huge data for future wireless applications. Performance of multi-core fiber (MCF) communication systems is severely affected by inter-core crosstalk (IC-XT), which limits its application for long-reach backhaul optical network. The nonlinear IC-XT interference in MCF makes the overall system nonlinear, thereby resulting in a poor bit error rate (BER) performance. Conventional Volterra series based nonlinear equalizers have high computational complexity, and are impaired by modeling error due to the truncation of polynomial kernel. Recently, reproducing kernel Hilbert space (RKHS) based kernel least mean square (KLMS) equalizer has been proposed in the literature for mitigating IC-XT interference in MCF communication systems. However, KLMS based equalizer is based on minimum mean square error (MMSE) criterion which considers only second order statistics of error. In this paper, multivariate kernel minimum symbol error rate (KMSER) adaptive nonlinear equalizer in RKHS is proposed for mitigating IC-XT impairments in MCF communication systems. Simulations show that the proposed KMSER equalizer exhibits superior BER performance and less computational complexity over the existing Volterra series equalizer, and KLMS equalizer.

Visible light communication (VLC) has emerged as a promising supplement to the existing radio frequency (RF) technology, which facilitates high speed communication for next generation communication systems. Although promising, the performance in a practical VLC system is severely impaired by ambient light interference. Furthermore, nonlinearity of light emitting diodes (LEDs) and imperfect/oudated channel state information (CSI) are other factors that degrade the achievable bit error rate (BER) performance. In this work, an analytical framework for analyzing the expression for BER of a wide class of modulation techniques is derived for an impaired VLC system considering: (a) ambient light interference, (b) LED nonlinearity, and (c) imperfect and outdated CSI. The derived analytical expressions for BER are validated through extensive computer simulations performed over typical VLC channels. Lastly, the utility of the derived analytical framework is demonstrated in the context of high data-rate VLC systems, wherein the performance of DC biased optical orthogonal frequency division multiplexing (DCO-OFDM) is quantified for VLC links impaired by the aforementioned degradations.

Visible light communications (VLC) has lately emerged as a viable supplement to existing radio frequency (RF) based communication systems, and is an integral component of future communication systems. The possibility of deploying massive arrays of light emitting diodes (LED) and photo-detectors (PD), which translates to a massive array of multiple input multiple output (MIMO) system for VLC, have been recently proposed. However, massive-MIMO in VLC has the following drawbacks which limit its practical deployment: a) high condition number of the channel matrix, which negatively affects the robustness of traditional channel-inversion based detection, and b) high interference in a multi-user setting due to correlated columns of the overall MIMO channel matrix. In this paper, the multi-user (MU) massive-MIMO in VLC is considered, and a precoding technique is proposed that induces diverse effective channel matrices for different users, and hence facilitates MU detection using ordered successive interference cancellation. Further, it is shown that the proposed precoding technique maximizes an upper bound of the overall sum-rate of the MU massive-MIMO system. Lastly, simulations have been performed for MU massive LED and PD arrays demonstrating that the proposed precoding technique outperforms existing precoding techniques, and hence is a viable solution for massive-MIMO in VLC.