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Giuseppe Caire

Publications and source records attributed to Giuseppe Caire.

At least 397 records · Page 22Linked to original sources

Achievable Rates of FDD Massive MIMO Systems with Spatial Channel Correlation

It is well known that the performance of frequency-division-duplex (FDD) massive MIMO systems with i.i.d. channels is disappointing compared with that of time-division-duplex (TDD) systems, due to the prohibitively large overhead for acquiring channel state information at the transmitter (CSIT). In this paper, we investigate the achievable rates of FDD massive MIMO systems with spatially correlated channels, considering the CSIT acquisition dimensionality loss, the imperfection of CSIT and the regularized-zero-forcing linear precoder. The achievable rates are optimized by judiciously designing the downlink channel training sequences and user CSIT feedback codebooks, exploiting the multiuser spatial channel correlation. We compare our achievable rates with TDD massive MIMO systems, i.i.d. FDD systems, and the joint spatial division and multiplexing (JSDM) scheme, by deriving the deterministic equivalents of the achievable rates, based on popular channel models. It is shown that, based on the proposed eigenspace channel estimation schemes, the rate-gap between FDD systems and TDD systems is significantly narrowed, even approached under moderate number of base station antennas. Compared to the JSDM scheme, our proposal achieves dimensionality-reduction channel estimation without channel pre-projection, and higher throughput for moderate number of antennas and moderate to large channel coherence time, though at higher computational complexity.

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Max-Weight Scheduling and Quality-Aware Streaming for Device-to-Device Video Delivery

We propose and analyze centralized and distributed algorithms for device-to-device video scheduling and streaming. The proposed algorithms address jointly the problems of device-to-device link scheduling and video quality adaptation in streaming. Our simulations show that the proposed algorithms significantly outperform conventional separated approaches that treat these two problems independently.

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Wireless Backhaul Networks: Capacity Bound, Scalability Analysis and Design Guidelines

This paper studies the scalability of a wireless backhaul network modeled as a random extended network with multi-antenna base stations (BSs), where the number of antennas per BS is allowed to scale as a function of the network size. The antenna scaling is justified by the current trend towards the use of higher carrier frequencies, which allows to pack large number of antennas in small form factors. The main goal is to study the per-BS antenna requirement that ensures scalability of this network, i.e., its ability to deliver non-vanishing rate to each source-destination pair. We first derive an information theoretic upper bound on the capacity of this network under a general propagation model, which provides a lower bound on the per-BS antenna requirement. Then, we characterize the scalability requirements for two competing strategies of interest: (i) long hop: each source-destination pair minimizes the number of hops by sacrificing multiplexing gain while achieving full beamforming (power) gain over each hop, and (ii) short hop: each source-destination pair communicates through a series of short hops, each achieving full multiplexing gain. While long hop may seem more intuitive in the context of massive multiple-input multiple-output (MIMO) transmission, we show that the short hop strategy is significantly more efficient in terms of per-BS antenna requirement for throughput scalability. As a part of the proof, we construct a scalable short hop strategy and show that it does not violate any fundamental limits on the spatial degrees of freedom (DoFs).

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Joint Spatial Division and Multiplexing for mm-Wave Channels

Massive MIMO systems are well-suited for mm-Wave communications, as large arrays can be built with reasonable form factors, and the high array gains enable reasonable coverage even for outdoor communications. One of the main obstacles for using such systems in frequency-division duplex mode, namely the high overhead for the feedback of channel state information (CSI) to the transmitter, can be mitigated by the recently proposed JSDM (Joint Spatial Division and Multiplexing) algorithm. In this paper we analyze the performance of this algorithm in some realistic propagation channels that take into account the partial overlap of the angular spectra from different users, as well as the sparsity of mm-Wave channels. We formulate the problem of user grouping for two different objectives, namely maximizing spatial multiplexing, and maximizing total received power, in a graph-theoretic framework. As the resulting problems are numerically difficult, we proposed (sub optimum) greedy algorithms as efficient solution methods. Numerical examples show that the different algorithms may be superior in different settings.We furthermore develop a new, "degenerate" version of JSDM that only requires average CSI at the transmitter, and thus greatly reduces the computational burden. Evaluations in propagation channels obtained from ray tracing results, as well as in measured outdoor channels show that this low-complexity version performs surprisingly well in mm-Wave channels.

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Caching Eliminates the Wireless Bottleneck in Video-Aware Wireless Networks

Cellular data traffic almost doubles every year, greatly straining network capacity. The main driver for this development is wireless video. Traditional methods for capacity increase (like using more spectrum and increasing base station density) are very costly, and do not exploit the unique features of video, in particular a high degree of {\em asynchronous content reuse}. In this paper we give an overview of our work that proposed and detailed a new transmission paradigm exploiting content reuse, and the fact that storage is the fastest-increasing quantity in modern hardware. Our network structure uses caching in helper stations (femto-caching) and/or devices, combined with highly spectrally efficient short-range communications to deliver video files. For femto-caching, we develop optimum storage schemes and dynamic streaming policies that optimize video quality. For caching on devices, combined with device-to-device communications, we show that communications within {\em clusters} of mobile stations should be used; the cluster size can be adjusted to optimize the tradeoff between frequency reuse and the probability that a device finds a desired file cached by another device in the same cluster. We show that in many situations the network throughput increases linearly with the number of users, and that D2D communications also is superior in providing a better tradeoff between throughput and outage than traditional base-station centric systems. Simulation results with realistic numbers of users and channel conditions show that network throughput (possibly with outage constraints) can be increased by two orders of magnitude compared to conventional schemes.

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Fundamental Limits of Caching in Wireless D2D Networks

We consider a wireless Device-to-Device (D2D) network where communication is restricted to be single-hop. Users make arbitrary requests from a finite library of files and have pre-cached information on their devices, subject to a per-node storage capacity constraint. A similar problem has already been considered in an ``infrastructure'' setting, where all users receive a common multicast (coded) message from a single omniscient server (e.g., a base station having all the files in the library) through a shared bottleneck link. In this work, we consider a D2D ``infrastructure-less'' version of the problem. We propose a caching strategy based on deterministic assignment of subpackets of the library files, and a coded delivery strategy where the users send linearly coded messages to each other in order to collectively satisfy their demands. We also consider a random caching strategy, which is more suitable to a fully decentralized implementation. Under certain conditions, both approaches can achieve the information theoretic outer bound within a constant multiplicative factor. In our previous work, we showed that a caching D2D wireless network with one-hop communication, random caching, and uncoded delivery, achieves the same throughput scaling law of the infrastructure-based coded multicasting scheme, in the regime of large number of users and files in the library. This shows that the spatial reuse gain of the D2D network is order-equivalent to the coded multicasting gain of single base station transmission. It is therefore natural to ask whether these two gains are cumulative, i.e.,if a D2D network with both local communication (spatial reuse) and coded multicasting can provide an improved scaling law. Somewhat counterintuitively, we show that these gains do not cumulate (in terms of throughput scaling law).

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Performance Modeling of Next-Generation Wireless Networks

The industry is satisfying the increasing demand for wireless bandwidth by densely deploying a large number of access points which are centrally managed, e.g. enterprise WiFi networks deployed in university campuses, companies, airports etc. This small cell architecture is gaining traction in the cellular world as well, as witnessed by the direction in which 4G+ and 5G standardization is moving. Prior academic work in analyzing such large-scale wireless networks either uses oversimplified models for the physical layer, or ignores other important, real-world aspects of the problem, like MAC layer considerations, topology characteristics, and protocol overhead. On the other hand, the industry is using for deployment purposes on-site surveys and simulation tools which do not scale, cannot efficiently optimize the design of such a network, and do not explain why one design choice is better than another. In this paper we introduce a simple yet accurate analytical model which combines the realism and practicality of industrial simulation tools with the ability to scale, analyze the effect of various design parameters, and optimize the performance of real- world deployments. The model takes into account all central system parameters, including channelization, power allocation, user scheduling, load balancing, MAC, advanced PHY techniques (single and multi user MIMO as well as cooperative transmission from multiple access points), topological characteristics and protocol overhead. The accuracy of the model is verified via extensive simulations and the model is used to study a wide range of real world scenarios, providing design guidelines on the effect of various design parameters on performance.

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Demystifying the Scaling Laws of Dense Wireless Networks: No Linear Scaling in Practice

We optimize the hierarchical cooperation protocol of Ozgur, Leveque and Tse, which is supposed to yield almost linear scaling of the capacity of a dense wireless network with the number of users $n$. Exploiting recent results on the optimality of "treating interference as noise" in Gaussian interference channels, we are able to optimize the achievable average per-link rate and not just its scaling law. Our optimized hierarchical cooperation protocol significantly outperforms the originally proposed scheme. On the negative side, we show that even for very large $n$, the rate scaling is far from linear, and the optimal number of stages $t$ is less than 4, instead of $t \rightarrow \infty$ as required for almost linear scaling. Combining our results and the fact that, beyond a certain user density, the network capacity is fundamentally limited by Maxwell laws, as shown by Francheschetti, Migliore and Minero, we argue that there is indeed no intermediate regime of linear scaling for dense networks in practice.

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Wireless Device-to-Device Caching Networks: Basic Principles and System Performance

As wireless video transmission is the fastest-growing form of data traffic, methods for spectrally efficient video on-demand wireless streaming are essential to service providers and users alike. A key property of video on-demand is the asynchronous content reuse, such that a few dominant videos account for a large part of the traffic, but are viewed by users at different times. Caching of content on devices in conjunction with D2D communications allows to exploit this property, and provide a network throughput that is significantly in excess of both the conventional approach of unicasting from the base station and the traditional D2D networks for regular data traffic. This paper presents in a semi-tutorial concise form some recent results on the throughput scaling laws of wireless networks with caching and asynchronous content reuse, contrasting the D2D approach with a competing approach based on combinatorial cache design and network coded transmission from the base station (BS) only, referred to as coded multicasting. Interestingly, the spatial reuse gain of the former and the coded multicasting gain of the latter yield, somehow surprisingly, the same near-optimal throughput behavior in the relevant regime where the number of video files in the library is smaller than the number of streaming users. Based on our recent theoretical results, we propose a holistic D2D system design that incorporates traditional microwave (2 GHz) as well as millimeter-wave D2D links; the direct connections to the base station can be used to provide those rare video requests that cannot be found in local caches. We provide extensive simulations under a variety of system settings, and compare our scheme with other existing schemes by the BS. We show that, despite the similar behavior of the scaling laws, the proposed D2D approach offers very significant throughput gains with respect to the BS-only schemes.

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Cellular Interference Alignment

Interference alignment promises that, in Gaussian interference channels, each link can support half of a degree of freedom (DoF) per pair of transmit-receive antennas. However, in general, this result requires to precode the data bearing signals over a signal space of asymptotically large diversity, e.g., over an infinite number of dimensions for time-frequency varying fading channels, or over an infinite number of rationally independent signal levels, in the case of time-frequency invariant channels. In this work we consider a wireless cellular system scenario where the promised optimal DoFs are achieved with linear precoding in one-shot (i.e., over a single time-frequency slot). We focus on the uplink of a symmetric cellular system, where each cell is split into three sectors with orthogonal intra-sector multiple access. In our model, interference is "local", i.e., it is due to transmitters in neighboring cells only. We consider a message-passing backhaul network architecture, in which nearby sectors can exchange already decoded messages and propose an alignment solution that can achieve the optimal DoFs. To avoid signaling schemes relying on the strength of interference, we further introduce the notion of \emph{topologically robust} schemes, which are able to guarantee a minimum rate (or DoFs) irrespectively of the strength of the interfering links. Towards this end, we design an alignment scheme which is topologically robust and still achieves the same optimum DoFs.

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Adaptive Video Streaming in MU-MIMO Networks

We consider extensions and improvements on our previous work on dynamic adaptive video streaming in a multi-cell multiuser ``small cell'' wireless network. Previously, we treated the case of single-antenna base stations and, starting from a network utility maximization (NUM) formulation, we devised a ``push'' scheduling policy, where users place requests to sequential video chunks to possibly different base stations with adaptive video quality, and base stations schedule their downlink transmissions in order to stabilize their transmission queues. In this paper we consider a ``pull'' strategy, where every user maintains a request queue, such that users keep track of the video chunks that are effectively delivered. The pull scheme allows to download the chunks in the playback order without skipping or missing them. In addition, motivated by the recent/forthcoming progress in small cell networks (e.g., in wave-2 of the recent IEEE 802.11ac standard), we extend our dynamic streaming approach to the case of base stations capable of multiuser MIMO downlink, i.e., serving multiple users on the same time-frequency slot by spatial multiplexing. By exploiting the ``channel hardening'' effect of high dimensional MIMO channels, we devise a low complexity user selection scheme to solve the underlying max-weighted rate scheduling, which can be easily implemented and runs independently at each base station. Through simulations, we show MIMO gains in terms of video streaming QoE metrics like the pre-buffering and re-buffering times.

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A Repair Framework for Scalar MDS Codes

Several works have developed vector-linear maximum-distance separable (MDS) storage codes that min- imize the total communication cost required to repair a single coded symbol after an erasure, referred to as repair bandwidth (BW). Vector codes allow communicating fewer sub-symbols per node, instead of the entire content. This allows non trivial savings in repair BW. In sharp contrast, classic codes, like Reed- Solomon (RS), used in current storage systems, are deemed to suffer from naive repair, i.e. downloading the entire stored message to repair one failed node. This mainly happens because they are scalar-linear. In this work, we present a simple framework that treats scalar codes as vector-linear. In some cases, this allows significant savings in repair BW. We show that vectorized scalar codes exhibit properties that simplify the design of repair schemes. Our framework can be seen as a finite field analogue of real interference alignment. Using our simplified framework, we design a scheme that we call clique-repair which provably identifies the best linear repair strategy for any scalar 2-parity MDS code, under some conditions on the sub-field chosen for vectorization. We specify optimal repair schemes for specific (5,3)- and (6,4)-Reed- Solomon (RS) codes. Further, we present a repair strategy for the RS code currently deployed in the Facebook Analytics Hadoop cluster that leads to 20% of repair BW savings over naive repair which is the repair scheme currently used for this code.

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Full-Duplex Relaying with Half-Duplex Relays

We consider "virtual" full-duplex relaying by means of half-duplex relays. In this configuration, each relay stage in a multi-hop relaying network is formed by at least two relays, used alternatively in transmit and receive modes, such that while one relay transmits its signal to the next stage, the other relay receives a signal from the previous stage. With such a pipelined scheme, the source is active and sends a new information message in each time slot. We consider the achievable rates for different coding schemes and compare them with a cut-set upper bound, which is tight in certain conditions. In particular, we show that both lattice-based Compute and Forward (CoF) and Quantize reMap and Forward (QMF) yield attractive performance and can be easily implemented. In particular, QMF in this context does not require "long" messages and joint (non-unique) decoding, if the quantization mean-square distortion at the relays is chosen appropriately. Also, in the multi-hop case the gap of QMF from the cut-set upper bound grows logarithmically with the number of stages, and not linearly as in the case of "noise level" quantization. Furthermore, we show that CoF is particularly attractive in the case of multi-hop relaying, when the channel gains have fluctuations not larger than 3dB, yielding a rate that does not depend on the number of relaying stages. In particular, we argue that such architecture may be useful for a wireless backhaul with line-of-sight propagation between the relays.

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Index Coding Problem with Side Information Repositories

To tackle the expected enormous increase in mobile video traffic in cellular networks, an architecture involving a base station along with caching femto stations (referred to as helpers), storing popular files near users, has been proposed [1]. The primary benefit of caching is the enormous increase in downloading rate when a popular file is available at helpers near a user requesting that file. In this work, we explore a secondary benefit of caching in this architecture through the lens of index coding. We assume a system with n users and constant number of caching helpers. Only helpers store files, i.e. have side information. We investigate the following scenario: Each user requests a distinct file that is not found in the set of helpers nearby. Users are served coded packets (through an index code) by an omniscient base station. Every user decodes its desired packet from the coded packets and the side information packets from helpers nearby. We assume that users can obtain any file stored in their neighboring helpers without incurring transmission costs. With respect to the index code employed, we investigate two achievable schemes: 1) XOR coloring based on coloring of the side information graph associated with the problem and 2)Vector XOR coloring based on fractional coloring of the side information graph. We show that the general problem reduces to a canonical problem where every user is connected to exactly one helper under some topological constraints. For the canonical problem, with constant number of helpers (k), we show that the complexity of computing the best XOR/vector XOR coloring schemes are polynomial in the number of users n. The result exploits a special complete bi-partite structure that the side information graphs exhibit for any finite k.

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FemtoCaching: Wireless Video Content Delivery through Distributed Caching Helpers

Video on-demand streaming from Internet-based servers is becoming one of the most important services offered by wireless networks today. In order to improve the area spectral efficiency of video transmission in cellular systems, small cells heterogeneous architectures (e.g., femtocells, WiFi off-loading) are being proposed, such that video traffic to nomadic users can be handled by short-range links to the nearest small cell access points (referred to as "helpers"). As the helper deployment density increases, the backhaul capacity becomes the system bottleneck. In order to alleviate such bottleneck we propose a system where helpers with low-rate backhaul but high storage capacity cache popular video files. Files not available from helpers are transmitted by the cellular base station. We analyze the optimum way of assigning files to the helpers, in order to minimize the expected downloading time for files. We distinguish between the uncoded case (where only complete files are stored) and the coded case, where segments of Fountain-encoded versions of the video files are stored at helpers. We show that the uncoded optimum file assignment is NP-hard, and develop a greedy strategy that is provably within a factor 2 of the optimum. Further, for a special case we provide an efficient algorithm achieving a provably better approximation ratio of $1-(1-1/d)^d$, where $d$ is the maximum number of helpers a user can be connected to. We also show that the coded optimum cache assignment problem is convex that can be further reduced to a linear program. We present numerical results comparing the proposed schemes.

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On Interference Networks over Finite Fields

We present a framework to study linear deterministic interference networks over finite fields. Unlike the popular linear deterministic models introduced to study Gaussian networks, we consider networks where the channel coefficients are general scalars over some extension field $\FF_{p^m}$ (scalar $m$-th extension-field models), $m \times m$ diagonal matrices over $\FF_p$ ($m$-symbol extension ground-field models), and $m \times m$ general non-singular matrices (MIMO ground field models). We use the companion matrix representation of the extension field to convert $m$-th extension scalar models into MIMO ground-field models where the channel matrices have special algebraic structure. For such models, we consider the $2 \times 2 \times 2$ topology (two-hops two-flow) and the 3-user interference network topology. We derive achievability results and feasibility conditions for certain schemes based on the Precoding-Based Network Alignment (PBNA) approach, where intermediate nodes use random linear network coding (i.e., propagate random linear combinations of their incoming messages) and non-trivial precoding/decoding is performed only at the network edges, at the sources and destinations. Furthermore, we apply this approach to the scalar $2\times 2\times 2$ complex Gaussian IC with fixed channel coefficients, and show two competitive schemes outperforming other known approaches at any SNR, where we combine finite-field linear precoding/decoding with lattice coding and the Compute and Forward approach at the signal level. As a side result, we also show significant advantages of vector linear network coding both in terms of feasibility probability (with random coding coefficients) and in terms of coding latency, with respect to standard scalar linear network coding, in PBNA schemes.

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Joint Spatial Division and Multiplexing: Opportunistic Beamforming and User Grouping

Joint Spatial Division and Multiplexing (JSDM) is a recently proposed scheme to enable massive MIMO like gains and simplified system operations for Frequency Division Duplexing (FDD) systems. The key idea lies in partitioning the users into groups with approximately similar covariances, and use a two stage downlink beamforming: a pre-beamformer that depends on the channel covariances and minimizes interference across groups and a multiuser MIMO precoder for the effective channel after pre-beamforming, to counteract interference within a group. We first focus on the regime of a fixed number of antennas and large number of users, and show that opportunistic beamforming with user selection yields significant gain, and thus, channel correlation may yield a capacity improvement over the uncorrelated "isotropic" channel result of Sharif and Hassibi. We prove that in the presence of different correlations among groups, a block diagonalization approach for the design of pre-beamformers achieves the optimal sum-rate scaling. Next, we consider the regime of large number of antennas and users, where user selection does not provide significant gain. Here, we propose a simplified user grouping algorithm to cluster users into groups when the number of antennas becomes very large, in a realistic setting where users are randomly distributed and have different angles of arrival and angular spreads depending on the propagation environment. Our subsequent analysis leads to a probabilistic scheduling algorithm, where users within each group are preselected at random based on probabilities derived from the large system analysis, depending on the fairness criterion. This is advantageous since only the selected users are required to feedback their channel state information (CSIT).

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Optimal Throughput-Outage Trade-off in Wireless One-Hop Caching Networks

We consider a wireless device-to-device (D2D) network where the nodes have cached information from a library of possible files. Inspired by the current trend in the standardization of the D2D mode for 4th generation wireless networks, we restrict to one-hop communication: each node place a request to a file in the library, and downloads from some other node which has the requested file in its cache through a direct communication link, without going through a base station. We describe the physical layer communication through a simple "protocol-model", based on interference avoidance (independent set scheduling). For this network we define the outage-throughput tradeoff problem and characterize the optimal scaling laws for various regimes where both the number of nodes and the files in the library grow to infinity.

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