It is well established that the performance of reconfigurable intelligent surface (RIS)-assisted systems critically depends on the optimal placement of the RIS. Previous works consider either simple coverage maximization or simultaneous optimization of the placement of the RIS along with the beamforming and reflection coefficients, most of which assume that the location of the RIS, base station (BS), and users are known. However, in practice, only the spatial variation of user density and obstacle configuration are likely to be known prior to deployment of the system. Thus, we formulate a non-convex problem that optimizes the position of the RIS over the expected minimum signal-to-interference-plus-noise ratio (SINR) of the system with user randomness, assuming that the system employs joint beamforming after deployment. To solve this problem, we propose a recursive coarse-to-fine methodology that constructs a set of candidate locations for RIS placement based on the obstacle configuration and evaluates them over multiple instantiations from the user distribution. The search is recursively refined within the optimal region identified in each stage to determine the final optimal region for RIS deployment. Detailed numerical results are presented to corroborate our findings.

The challenges of channel estimation in reconfigurable intelligent surfaces (RIS) are well known, in particular, its high demand on pilots and channel estimation resources. This paper explores gains in channel estimation, its efficiency, and achievable rates, by leveraging the differences in antenna correlations for different links, a phenomenon known ascorrelation diversity. Antenna correlations are a well-known feature of mm-wave and massive MIMO (multiple-input multiple-output) communication, and the existence of correlation diversity in multi-user systems is well-established in the literature. In RIS systems employing frequency-division duplex (FDD) transmission, we propose a novel joint transmit/RIS beamforming that exploits antenna correlation diversity via efficient channel training and pilots. Our pilot configurations are optimized according to the degrees of freedom (DoF), and sum-rates are optimized via beamforming. The proposed approach identifies and analyzes the common and disjoint eigenspaces of the antenna correlation matrices, and exploits them utilizingproduct superpositionand rate splitting. A key contribution of this work is reconciling the requirements of transmitter/RIS beamforming on the one hand, and features of product superposition in the presence of imperfect channel state information (CSI) on the other hand. Numerical results are presented to corroborate our findings.

Due to variations in node mobility or differences in the scattering environment, wireless links in multi-user systems often experience non-identical coherence intervals; this is also true in systems assisted by reconfigurable intelligent surfaces (RIS). This paper studies RIS-assisted multi-user downlink systems under link coherence disparity. Since the RIS channel model has many parameters to be estimated, controlling the training overhead under coherence disparity has a strong impact on the practical operation of RIS. Thus motivated, we propose a novel pilot-domain non-orthogonal multiple access (NOMA) technique for RIS-assisted downlink systems. The transmit beamforming and RIS reflection coefficient vectors are jointly designed to maximize the achieved sum-rate. We analyze the resulting reduction in training overhead and the corresponding rate improvements. We investigate efficient pilot placement strategies for multi-user scenarios with arbitrary coherence intervals. Numerical results illustrate the effectiveness of the proposed technique.

This paper studies multi-user downlink systems assisted by reconfigurable intelligent surfaces (RIS), in which individual links experience non-identical coherence intervals. This is a condition that frequently occurs in practical scenar-ios, due to variations in node mobilities or differences in the scattering environment. Training the channels and RIS states is a challenging and time-consuming process, and reducing training overhead is recognized as an important task. This becomes even more challenging under coherence disparity, where transmitting ordinary pilots without attention to the unequal need of users for pilots can adversely impact the training overhead and diminish the gains in rate and degrees of freedom. Motivated by this, we propose a pilot-domain non-orthogonal multiple access (NOMA) technique for RIS-assisted downlink systems, and demonstrate how non-orthogonal pilot/data transmission can effectively reduce the training overhead and yield rate improvements. We explore channel estimation through superposition pilots and design RIS reflection coefficients to maximize the achievable sum-rate via the proposed scheme.

Non-orthogonal transmission of data and pilots using product superposition is known to be highly efficient under unequal coherence conditions in a downlink channel, improving achievable rates and degrees of freedom (DoF). However, these techniques have not been used when transmit beamforming is present, as product superposition measures and utilizes composite (virtual) link gains, while beamforming requires knowledge of true (physical) link gains at the transmitter. This paper presents new techniques that enable the gains of pilot-domain non-orthogonal multiple access (NOMA) product superposition to be combined with transmit beamforming gain. The technical novelty of this paper lies in reconciling the requirements of transmit beamforming and product superposition under perfect or imperfect channel state feedback, and demonstrating its effectiveness under multi-user scenarios. The paper begins with a multi-user generalization of product superposition rate analysis in the absence of feedback. Then, a novel non-orthogonal scheme is proposed that harmoniously combines with either perfect or imperfect feedback under disparity in coherence time or coherence bandwidth among users. The proposed scheme includes efficient pilot placement strategies under multi-user scenarios with arbitrary coherence time and coherence bandwidth for different users. Numerical results illustrate the effectiveness of the proposed techniques.

Multi-user downlink systems with reconfigurable intelligent surfaces (RIS) require considerable overhead for training the channels and RIS states. This is made even more difficult when the links have non-identical coherence times, a frequently occurring condition due to the variations in node mobility and scattering environment. In the absence of RIS, previous studies have shown that pilot reuse can reduce the pilot overhead under coherence disparity and achieve gains in both rate and degrees of freedom (DoF). This work explores the impact of pilot reuse on RIS-assisted downlink channels having unequal link coherence times and shows how overlapping pilot and data transmission can reduce the training overhead and achieve rate gains. Additionally, we jointly design the transmit beamforming and RIS reflection coefficient vectors to maximize the sum-rate achieved through the proposed transmission scheme. We employ fractional programming to solve the optimization problem and determine the optimal vectors for the beamforming and RIS precoding. Numerical results are presented to corroborate our findings.

When the individual links in a downlink channel have different coherence intervals, previous studies have shown that pilot reuse can achieve not only rate gains, but also gains in degrees of freedom (DoF). Channel state feedback is another source of gains, but combining beamforming with pilot reuse presents new and interesting design questions. The performance of such a scheme has been an open problem under coherence disparity, the regime in which pilot reuse is most promising. We propose a new non-orthogonal transmission scheme for pilots and data that harmoniously combines with either perfect or imperfect channel state feedback. The proposed scheme employs both product superposition and zero-forcing beamforming within the same framework, and improves the resulting achievable rates. The developments include careful pilot placement and an efficient pilot reuse strategy under channel state feedback in a multi-user downlink channel. Numerical results are presented to corroborate our findings.

In this paper, we investigate simultaneous lightwave information and power transfer (SLIPT) for underwater visible light communication systems. We consider three SLIPT methods namely time switching (TS), power splitting (PS) and time switching-power splitting (TS-PS) where the splitting/switching factors are defined as optimization parameters. For each of these methods, we derive closed-form expressions for the average harvested energy, bit error rate and spectral efficiency in the presence of underwater turbulence modeled by lognormal statistics. Using these expressions, we determine the optimal splitting factors to maximize the harvested energy while satisfying a given bit error rate value and a given threshold spectral efficiency value. Our results reveal that, if not optimized, SLIPT methods under consideration are outperformed by the simple AC-DC separation (ADS) method which provides the largest harvested energy versus spectral efficiency (HE-SE) region. Optimization of splitting/switching factors extends the HE-SE regions; hence, optimized versions of TS, PS and TS-PS methods are able to significantly outperform ADS for most cases. We further investigate the effect of various channel and system parameters such as water type, turbulence level, beam divergence, receiver aperture size on the harvested energy and quantify the improvements in battery lifetime through the use of SLIPT methods.

Visible light communication (VLC) has emerged as a high-capacity connectivity solution for underwater sensor networks. Since water is relatively transparent to blue or green light, visible light lasers or LEDs can be used as transmitters for underwater wireless connectivity with data rates up to hundreds of Mbps. In underwater networks, a critical system design issue is the network lifetime which highly depends on the battery capacity. Since recharging in underwater scenarios is typically very costly and impractical, energy harvesting can be considered as a promising alternative. In this paper, we explore simultaneous lightwave information and power transfer (SLIPT) for VLC-based USNs. We adopt time splitting method where the receiver switches in time between the modes of energy harvesting (EH) and information decoding (ID). We derive a closed-form expression for the average harvested energy over log-normal model underwater turbulence channel. Using this expression, we determine the splitting factor between EH and ID operation modes to maximize the harvested energy while satisfying a given bit error rate value.

Light emitting diodes (LEDs) are increasingly used in automotive exterior lighting. The expected wide availability of LED-based front and back lights makes visible light communication (VLC) a natural vehicular connectivity solution. A major challenge in vehicular VLC systems is their relatively poor performance in adverse weather conditions such as severe fog. In this paper, we propose the use of single-photon avalanche diode (SPAD) for vehicular VLC systems. With their higher sensitivity in comparison to conventional photodetectors, SPADs can be efficiently used to detect weak signals. Under the assumption of on-off keying (OOK), we present the error rate performance of vehicular VLC systems. Since the SPAD output is modelled by Poisson statistics, the bit error rate (BER) takes the form of a semi-infinite summation. Based on Anscombe transformation, we approximate Poisson noise as Gaussian and derive a closed-form BER expression. Using this expression, we obtain a closed-form expression for maximum achievable link distance to ensure a targeted BER. We present an extensive numerical study to validate our derivations and demonstrate the performance of vehicular VLC system under different weather conditions.

In Intelligent Transportation Systems, visible light communication (VLC) has emerged as a powerful candidate to enable wireless connectivity in vehicle-to-vehicle (V2V) and vehicle-to- infrastructure (V2I) links. While VLC has been studied intensively in the context of indoor communications, its application to vehicular networking is relatively new. In this paper, we carry out a comprehensive channel modeling study to quantify the effect of rain and fog on a V2V link with a high-beam headlamp acting as the transmitter. Taking advantage of advanced ray tracing features, we first develop a path loss model for V2V link as a function of distance under different weather conditions. Then, we use this expression to determine the maximum achievable distance to ensure a given bit error rate. We further investigate the deployment of relay- assisted systems to extend transmission ranges. Extensive numerical results are presented to corroborate our findings.