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The technology of reconfigurable intelligent surfaces (RIS) has been showing promising potential in a variety of applications relying on Beyond-5G networks. Reconfigurable intelligent surface (RIS) can indeed provide fine channel flexibility to improve communication quality of service (QoS) or restore localization capabilities in challenging operating conditions, while conventional approaches fail (e.g., due to insufficient infrastructure, severe radio obstructions). In this paper, we tackle a general low-complexity approach for optimizing the precoders that control such reflective surfaces under hardware constraints. More specifically, it allows the approximation of any desired beam pattern using a pre-characterized look-up table of feasible complex reflection coefficients for each RIS element. The proposed method is first evaluated in terms of beam fidelity for several examples of RIS hardware prototypes. Then, by means of a theoretical bounds analysis, we examine the impact of RIS beams approximation on the performance of near-field downlink positioning in non-line-of-sight conditions, while considering several RIS phase profiles (incl. directional, random and localization-optimal designs). Simulation results in a canonical scenario illustrate how the introduced RIS profile optimization scheme can reliably produce the desired RIS beams under realistic hardware limitations. They also highlight its sensitivity to both the underlying hardware characteristics and the required beam kinds in relation to the specificity of RIS-aided localization applications., 27 pages, 8 figures, journal

Upcoming beyond fifth generation (5G) communications systems aim at further enhancing key performance indicators and fully supporting brand new use cases by embracing emerging techniques, e.g., reconfigurable intelligent surface (RIS), integrated communication, localization, and sensing, and mmWave/THz communications. The wireless intelligence empowered by state-of-the-art artificial intelligence techniques has been widely considered at the transceivers, and now the paradigm is deemed to be shifted to the smart control of radio propagation environment by virtue of RISs. In this article, we argue that to harness the full potential of RISs, localization and communication must be tightly coupled. This is in sharp contrast to 5G and earlier generations, where localization was a minor additional service. To support this, we first introduce the fundamentals of RIS mmWave channel modeling, followed by RIS channel state information acquisition and link establishment. Then, we deal with the connection between localization and communications, from a separate and joint perspective., Comment: 7 pages, 6 figures, submitted to IEEE Vehicular Technology Magazine

The rising concept of reconfigurable intelligent surface (RIS) has promising potential for Beyond 5G localization applications. We herein investigate different phase profile designs at a reflective RIS, which enable non-line-of-sight positioning in nearfield from downlink single antenna transmissions. We first derive the closed-form expressions of the corresponding Fisher information matrix (FIM) and position error bound (PEB). Accordingly, we then propose a new localization-optimal phase profile design, assuming prior knowledge of the user equipment location. Numerical simulations in a canonical scenario show that our proposal outperforms conventional RIS random and directional beam codebook designs in terms of PEB. We also illustrate the four beams allocated at the RIS (i.e., one directional beam, along with its derivatives with respect to space dimensions) and show how their relative weights according to the optimal solution can be practically implemented through time sharing (i.e., considering feasible beams sequentially)., 6 pages, 7 figures

openaire: EC/H2020/101017011/EU//RISE-6G We address the localization of a reconfigurable intelligent surface (RIS) for a single-input single-output multi-carrier system using bi-static sensing between a fixed transmitter and a fixed receiver. Due to the deployment of RISs with a large dimension, near-field (NF) scenarios are likely to occur, especially for indoor applications, and are the focus of this work. We first derive the Cramér-Rao bounds (CRBs) on the estimation error of the RIS position and orientation and the time of arrival (TOA) for the path transmitter-RIS-receiver. We propose a multi-stage low-complexity estimator for RIS localization purposes. In this proposed estimator, we first perform a line search to estimate the TOA. Then, we use the far-field approximation of the NF signal model to implicitly estimate the angle of arrival and the angle of departure at the RIS center. Finally, the RIS position and orientation estimate are refined via a quasi-Newton method. Simulation results reveal that the proposed estimator can attain the CRBs.We also investigate the effects of several influential factors on the accuracy of the proposed estimator like the RIS size, transmitted power, system bandwidth, and RIS position and orientation.

Smart radio environments (SREs) are seen as a key rising concept of next generation wireless networks, where propagation channels between transmitters and receivers are purposely controlled. One promising approach to achieve such channel flexibility relies on semipassive reflective Reconfigurable intelligent surfaces (RISs), which can shape the bouncing multipath signals for enhancing communication quality of service, making localization feasible in adverse operating conditions, or reducing unwanted electromagnetic emissions. This paper introduces a generic framework that aims at optimizing the end-to-end precoder controlled by RISs, so that arbitrary beam patterns can be generated, given a predefined lookup table of RIS element-wise complex reflection coefficients. This method is validated and illustrated for different targeted beam patterns in both the far-field and the near-field regimes, while considering the prior characterization of real-life RIS hardware prototypes. These results show how, and to which extent, RIS configuration optimization can approximate the desired beams under realistic hardware limitations and low-complexity implementation practicability, or conversely, which RIS elements' lookup tables would be more suitable. The latter can provide useful guidelines for future RIS hardware designs., Comment: 6 pages, 6 figures

Exploiting wavefront curvature enables localization with limited infrastructure and hardware complexity. With the introduction of reconfigurable intelligent surfaces (RISs), new opportunities arise, in particular when the RIS is functioning as a lens receiver. We investigate the localization of a transmitter using a RIS-based lens in close proximity to a single receive antenna element attached to reception radio frequency chain. We perform a Fisher information analysis, evaluate the impact of different lens configurations, and propose a two-stage localization algorithm. Our results indicate that positional beamforming can lead to better performance when a priori location information is available, while random beamforming is preferred when a priori information is lacking. Our simulation results for a moderate size lens operating at 28 GHz showcased that decimeter-level accuracy can be attained within 3 meters to the lens.

We consider the problem of joint three-dimensional localization and synchronization for a single-input single-output (SISO) system in the presence of a reconfigurable intelligent surface (RIS), equipped with a uniform planar array. First, we derive the Cram\'er-Rao bounds (CRBs) on the estimation error of the channel parameters, namely, the angle-of-departure (AOD), composed of azimuth and elevation, from RIS to the user equipment (UE) and times-of-arrival (TOAs) for the path from the base station (BS) to UE and BS-RIS-UE reflection. In order to avoid high-dimensional search over the parameter space, we devise a low-complexity estimation algorithm that performs two 1D searches over the TOAs and one 2D search over the AODs. Simulation results demonstrate that the considered RIS-aided wireless system can provide submeter-level positioning and synchronization accuracy, materializing the positioning capability of Beyond 5G networks even with single-antenna BS and UE. Furthermore, the proposed estimator is shown to attain the CRB at a wide interval of distances between UE and RIS. Finally, we also investigate the scaling of the position error bound with the number of RIS elements., Comment: Submitted to ICC 2021

Modular optical switch architectures combining wavelength routing based on arrayed waveguide grating (AWG) devices and multicasting based on star couplers hold promise for flexibly addressing the exponentially growing traffic demands in a cost- and power-efficient fashion. In a default switching scenario, an input port of the AWG is connected to an output port via a single wavelength. This can severely limit the capacity between broadcast domains, resulting in interdomain traffic switching bottlenecks. An unexplored solution to this issue is to exploit multiple AWG free spectral ranges (FSRs), i.e., to set up multiple parallel connections between each pair of broadcast domains. In this paper, we study, for the first time, the influence of the FSR count on the throughput of a multistage switching architecture and propose a generic and novel analytical framework to estimate the blocking probability. We assess the accuracy of our analytical results via Monte Carlo simulations. Our study points to significant improvements with a moderate increase in the number of FSRs. We show that an FSR count beyond four results in diminishing returns. Furthermore, to investigate the tradeoffs between the network- and physical-layer effects, we conduct a cross-layer analysis, taking into account pulse amplitude modulation and rate-adaptive forward error correction. We illustrate how the effective bit rate per port increases with an increase in the number of FSRs.

Deploying periodic inline chromatic dispersion compensation enables reducing the complexity of the digital back propagation (DBP) algorithm. However, compared with nondispersion-managed (NDM) links, dispersion-managed (DM) ones suffer a stronger cross-phase modulation (XPM). Utilizing per-channel dispersion-managed (CDM) links (e.g., using fiber Bragg grating) allows for a complexity reduction of DBP, while abating XPM compared to DM links. In this paper, we show for the first time that CDM links enable also a more effective XPM compensation compared to NDM ones, allowing a higher achievable information rate (AIR). This is explained by resorting to the frequency-resolved logarithmic perturbation model and showing that per-channel dispersion compensation increases the frequency correlation of the distortions induced by XPM over the channel bandwidth, making them more similar to a conventional phase noise. We compare the performance (in terms of the AIR) of a DM, an NDM, and a CDM link, considering two types of mismatched receivers: one neglects the XPM phase distortion and the other compensates for it. With the former, the CDM link is inferior to the NDM one due to an increased in-band signal--noise interaction. However, with the latter, a higher AIR is obtained with the CDM link than with the NDM one owing to a higher XPM frequency correlation. The DM link has the lowest AIR for both receivers because of a stronger XPM.

Reconfigurable intelligent surfaces (RISs) are set to be a revolutionary technology in the 6th generation of wireless systems. In this work, we study the application of RIS in a multi-user passive localization scenario, where we have one transmitter (Tx) and multiple asynchronous receivers (Rxs) with known locations. We aim to estimate the locations of multiple users equipped with RISs. The RISs only reflect the signal from the Tx to the Rxs and are not used as active transceivers themselves. Each Rx receives the signal from the Tx (LOS path) and the reflected signal from the RISs (NLOS path). We show that users' 3D position can be estimated with submeter accuracy in a large area around the transmitter, using the LOS and NLOS time-of-arrival measurements at the Rxs. We do so, by developing the signal model, deriving the Cramer-Rao bounds, and devising an estimator that attains these bounds. Furthermore, by orthogonalizing the RIS phase profiles across different users, we circumvent inter-path interference.

Reconfigurable intelligent surfaces (RISs) have the potential to enable user localization in scenarios where traditional approaches fail. Building on prior work in single-antenna RIS-enabled localization, we investigate the potential to exploit wavefront curvature in geometric near-field conditions. Via a Fisher information analysis, we demonstrate that while near-field improves localization accuracy mostly at short distances when the line-of-sight (LoS) path is present, it could still provide reasonable performance when this path is blocked by relying on a single RIS reflection., Comment: 5 pages, 6 figures, SPAWC21 conference

The standard solution for short-haul fiber-optic communications is to deploy noncoherent systems, i.e., to modulate and detect only the light intensity. In such systems, the signal is corrupted with optical noise from amplifiers and with thermal (electrical) noise. The capacity of noncoherent optical links has been studied extensively in the presence of either optical noise or thermal noise. In this paper, for the first time, we characterize the capacity under an average power constraint with both noise sources by establishing upper and lower bounds. In the two extreme cases of zero optical noise or zero thermal noise, we assess our bounds against some well-known results in the literature; improvements in both cases are observed. Next, for amplified fiber-optic systems, we study the trade-off between boosting signal energy (mitigating the effects of thermal noise) and adding optical noise. For a wide spectrum of system parameters and received power levels, we determine the optimal amplification gain. While mostly either no amplification or high-gain amplification is optimal, the best performance is for some parameter intervals achieved at finite gains.

We propose a modular star-coupler-based switch architecture along with a scalable multicast scheduling algorithm to enable all-optical multicasting among data center nodes. With broadcast domain partitioning in a 126-port switch, we achieve up to 24% improvement in the maximum achievable throughput.

We design a novel receiver based on the theoretical finding that the linear phase noise is uncorrelated with the nonlinear phase noise. The implementation of the proposed receiver is straightforward and it performs almost equally to the optimal detector at a much lower complexity.

We examine the feasibility of ultrahigh-scale datacenter multicasting by simultaneously taking into account the choice of architecture, modulation, and coding. Our Monte Carlo simulations indicate the dominant impact of in-band crosstalk on the throughput performance.

An upper bound on the capacity of the nondispersive optical fiber channel is presented. This bound, which is valid for arbitrary launch powers, confines the capacity within a much narrower range compared to what the previously known upper bound provided.

Matched filtering and sampling, which is known to be the optimal receiver for the linear additive white Gaussian noise channel, is in general suboptimal for a nonlinear medium. Nonetheless, it is commonly used in fiber-optical communication systems with nonlinear distortion. In this paper, a novel demodulation scheme is proposed for a two-user memoryless interference channel, with a type of nonlinear crosstalk that occurs in wavelength-multiplexed optical transmission. We show by simulations that by using this demodulation scheme, unlike matched filtering and sampling, the symbol error rate decreases to zero in the high-power regime.

Optical multicasting based on passive star couplers and fast tunable transceivers is an attractive solution for the throughput and latency requirements of many data center applications. The limited tuning range of transceivers, however, may not be sufficient enough to enable the flexible scheduling of traffic. In this paper, we propose a suite of scalable scheduling algorithms for opticalmulticast switches with wavelength tunability constraints, considering both tunable and nontunable transmitters. To support scalability and scheduling fairness, we adopt a round-robin arbitration policy in conjunction with appropriate provisions to minimize the number of packet retransmissions. We conduct Monte Carlo simulations to compare the proposed algorithms. For 64 ports, 16 channels, and bursty multicast traffic, a scheduling that exploits transmitter tunability with minimal fan-out splitting can improve the maximum throughput by up to 60% compared to a fixed transmitter scenario.

Hybrid networking, based on electronic packet switching and optical circuit switching, has been proposed to resolve the existing switching bottlenecks in data centers in an energy-efficient and cost-effective fashion. We consider the problem of resource provisioning in hybrid data centers in terms of optical circuit switching capacity and granularity. The number of fibers connected to server racks, the number of wavelengths per fiber, and the ratio of capacity provided by the optical circuit-switched portion of the network to that of the electronic packet-switched portion are crucial design parameters to be optimized during the data center planning phase. These parameters in conjunction with the additive-increase, multiplicative-decrease (AIMD) congestion control mechanism of the Transmission Control Protocol (TCP) pose a significant impact on data center network performance. In this paper, we examine the combined impact of optical bandwidth settings and TCP dynamics using event-driven simulations. Our analysis reveals the strong dependence of overall network throughput on channel capacity (i.e., the bit rate per wavelength channel) and points to the advantages of optical bandwidth consolidation employing higher-order modulation formats.

Elastic optical networks have been proposed to support high data rates in metro and core networks. However, frequency allocation of the channels (i.e., channel ordering) in such networks is a challenging problem. This requires arranging the optical channels within the frequency grid with the objective of ensuring a minimum signal-to-noise ratio (SNR). An optimal arrangement results in the highest SNR margin for the entire network. However, determining the optimal arrangement requires an exhaustive search through all possible arrangements (permutations) of the channels. The search space increases exponentially with the number of channels. This discourages an algorithm employing an exhaustive search for the optimal frequency allocation. We utilize the Gaussian noise (GN) model to formulate the frequency allocation (channel ordering) problem as a variant of the traveling salesman problem (TSP) using graph theory. Thereafter, we utilize graph-theoretic tools for the TSP from the existing literature to solve the channel ordering problem. Performance figures obtained for the proposed scheme show that it is marginally inferior to the optimal search (through all possible permutations) and outperforms any random allocation scheme. Moreover, the proposed scheme is implementable for a scenario with a large number of channels. In comparison, an exhaustive search with the GN model and split-step Fourier method simulations are shown to be feasible for a small number of channels only. It is also illustrated that the SNR decreases with an increase in bandwidth when the frequency separation is high.

A number of simplified models, based on perturbation theory, have been proposed for the fiber-optical channel and have been extensively used in the literature. Although these models are mainly developed for the low-power regime, they are used at moderate or high powers as well. It remains unclear to what extent the capacity of these models is affected by the simplifying assumptions under which they are derived. In this paper, we consider single-channel data transmission based on three continuous-time optical models: (i) a regular perturbative channel, (ii) a logarithmic perturbative channel, and (iii) the stochastic nonlinear Schr&ouml, dinger (NLS) channel. To obtain analytically tractable discrete-time models, we consider zero-dispersion fibers and a sampling receiver. We investigate the per-sample capacity of these models. Specifically, (i) we establish tight bounds on the capacity of the regular perturbative channel, (ii) we obtain the capacity of the logarithmic perturbative channel, and (iii) we present a novel upper bound on the capacity of the zero-dispersion NLS channel. Our results illustrate that the capacity of these models departs from each other at high powers because these models yield different capacity pre-logs. Since all three models are based on the same physical channel, our results highlight that care must be exercised in using simplified channel models in the high-power regime.

The all-optical switching of multicast flows using star couplers and tunable transceivers is a promising solution for emerging cloud data center applications. However, the limited tuning range of optical components on one hand and the buffer management challenges for multicast traffic delivery on the other pose a significant impact on the performance of optical multicast scheduling algorithms. Using only one queue per input port results in head-of-line (HOL) blocking and limits the throughput, especially for bursty traffic patterns. As the number of possible multicast destinations grows exponentially with the switch size, allocating one queue per destination is not a feasible solution. To resolve HOL blocking, in this paper we consider only a handful of queues per switch input port and devise scalable scheduling algorithms that take into account transceiver tunability constraints. According to our Monte Carlo analysis of a switch with 64 ports and operating under bursty traffic, it is possible to improve the maximum achievable throughput by 44% when the number of queues per port is increased from one to eight. We show that the performance gains due to an increase in the queue count depend on the availability of the spectral resources. With the scarcity of wavelengths, an increase in the number of queues leads to diminishing returns.

In this paper, we propose an information theoretic approach to fuse images compressed by compressed sensing (CS) techniques. The goal is to fuse multiple compressed images directly using measurements and reconstruct the final image only once. Since the reconstruction is the most expensive step, it would be a more economic method than separate reconstruction of each image. The proposed scheme is based on calculating the result using weighted average on the measurements of the inputs, where weights are calculated by information theoretic functions. The simulation results show that the final images produced by our method have higher quality than those produced by traditional methods, especially if the number of input images exceeds two.

It is well known that matched filtering and sampling (MFS) demodulation together with minimum Euclidean distance (MD) detection constitute the optimal receiver for the additive white Gaussian noise channel. However, for a general nonlinear transmission medium, MFS does not provide sufficient statistics, and, therefore, is suboptimal. Nonetheless, this receiver is widely used in optical systems, where the Kerr nonlinearity is the dominant impairment at high powers. In this paper, we consider a suite of receivers for a two-user channel subject to a type of nonlinear interference that occurs in wavelength-division-multiplexed channels. The asymptotes of the symbol error rate (SER) of the considered receivers at high powers are derived or bounded analytically. Moreover, Monte-Carlo simulations are conducted to evaluate the SER for all the receivers. Our results show that receivers that are based on MFS cannot achieve arbitrary low SERs, whereas the SER goes to zero as the power grows for the optimal receiver. Furthermore, we devise a heuristic demodulator, which together with the MD detector yields a receiver that is simpler than the optimal one and can achieve arbitrary low SERs. The SER performance of the proposed receivers is also evaluated for some single-span fiber-optical channels via split-step Fourier simulations.