arXiv subjects

Michail Matthaiou

Publications and source records attributed to Michail Matthaiou.

At least 145 records · Page 8Linked to original sources

arXiv2020

Towards Large Intelligent Surface (LIS)-based Communications

The concept of large intelligent surface (LIS)-based communication has recently raised research attention, in which a LIS is regarded as an antenna array whose entire surface area can be used for radio signal transmission and reception. To provide a fundamental understanding of LIS-based communication, this paper studies the uplink (UL) performance of LIS-based communication with matched filtering. We first investigate the new properties introduced by LIS. In particular, the array gain, spatial resolution, and the capability of interference suppression are theoretically presented and characterized. Then, we study two possible LIS system layouts in terms of UL, i.e., centralized LIS (C-LIS) and distributed LIS (D-LIS). Our analysis showcases that a centralized system has strong capability of interference suppression; in fact, interference can nearly be eliminated if the surface area is sufficient large or the frequency band is sufficient high. For D-LIS, we propose a series of resource allocation algorithms, including user association scheme, orientation control, and power control, to extend the coverage area of a distributed system. Simulation results show that the proposed algorithms significantly improve the system performance, and even more importantly, we observe that D-LIS outperforms CLIS in microwave bands, while C-LIS is superior to D-LIS in mmWave bands. These observations serve as useful guidelines for practical LIS deployments.

cs.IT↗

arXiv2020

Intelligent Reflecting Surfaces with Spatial Modulation: An Electromagnetic Perspective

Electromagnetic wave control using the concept of a reflecting surface is first studied as a near-field and a far-field problem. Using a secondary source present in a wireless communication environment, such as a backscatter tag, it is possible to leverage the incoming radiation from the source as a reference-wave to synthesize the desired wavefront across the reflecting surface, radiating a field of interest. In this geometry, the phase grating, which is synthesized using an array of sub-wavelength unit cells, is calculated by interacting the incident reference-wave and the desired wavefront, similar to a hologram. When illuminated by the reference-wave, the reflected wavefront from the calculated phase grating is guaranteed to constructively add in the direction of the desired radiation (beam-steering in the far-field) and also focus at the intended depth (beam-focusing in the radiative near-field). Leveraging a dynamic modulation mechanism in the context of an intelligent reflective surface (IRS) illuminated by a backscatter tag, later, we present that one can selectively focus and defocus at an arbitrarily positioned receiver within the 3D field of view of the reflecting surface. This enables the control of the amplitude of the radiated electric field at the receiver location, paving the way for a spatial modulation mechanism by means of reconfiguring the reflecting surface in a backscattered wireless communication environment. In addition to the phase modification approach on a unit cell level to reconfigure the aperture radiated wavefronts, we finally present a time varying IRS concept making use of a time-delay based approach relying on a delay adjustment between the reflection coefficients of the IRS' unit cell lattices.

eess.SP↗

arXiv2020

Prospective Multiple Antenna Technologies for Beyond 5G

Multiple antenna technologies have attracted large research interest for several decades and have gradually made their way into mainstream communication systems. Two main benefits are adaptive beamforming gains and spatial multiplexing, leading to high data rates per user and per cell, especially when large antenna arrays are used. Now that multiple antenna technology has become a key component of the fifth-generation (5G) networks, it is time for the research community to look for new multiple antenna applications to meet the immensely higher data rate, reliability, and traffic demands in the beyond 5G era. We need radically new approaches to achieve orders-of-magnitude improvements in these metrics and this will be connected to large technical challenges, many of which are yet to be identified. In this survey paper, we present a survey of three new multiple antenna related research directions that might play a key role in beyond 5G networks: Cell-free massive multiple-input multiple-output (MIMO), beamspace massive MIMO, and intelligent reflecting surfaces. More specifically, the fundamental motivation and key characteristics of these new technologies are introduced. Recent technical progress is also presented. Finally, we provide a list of other prospective future research directions.

cs.IT↗

arXiv2020

Large intelligent surface (LIS)-based communications: New features and system layouts

The concept of large intelligent surface (LIS)-based communication has recently attracted increasing research attention, where a LIS is considered as an antenna array whose entire surface area is available for radio signal transmission and reception. In order to provide a fundamental understanding of LIS-based communication, this paper studies the uplink performance of LIS-based communication with matched filtering in the presence of a line-of-sight channel. We first study the new features introduced by LIS. In particular, the array gain, spatial resolution, and the capability of interference suppression are theoretically presented and characterized. Then, we study two possible LIS system layouts, i.e., centralized LIS (C-LIS) and distributed LIS (D-LIS), and propose a user association scheme aiming to maximize the minimum user spectral efficiency (SE). Simulation results compare the achievable SE between two system layouts. We observe that the proposed user association algorithm significantly improves the performance of D-LIS, and with the help of it, the per-user achievable SE in D-LIS outperforms that in C-LIS in most considered scenarios.

cs.IT↗

arXiv2020

Massive MIMO Asymptotics for Ray-Based Propagation Channels

Favorable propagation (FP) and channel hardening (CH) are desired properties in massive multiple-input multiple-output (MIMO) systems. To date, these properties have primarily been analyzed for classical \textit{statistical} channel models, or \textit{ray-based} models with very specific angular parameters and distributions. This paper presents a thorough mathematical analysis of the asymptotic system behavior for ray-based channels with \textit{arbitrary} ray distributions, and considers \textit{two} types of antenna array structures at the cellular base station: a uniform linear array (ULA) and a uniform planar array (UPA). In addition to FP and channel hardening, we analyze the \textit{large system potential} (LSP) which measures the asymptotic ratio of the expected power in the desired channel to the expected total interference power when both the antenna and user numbers grow. LSP is said to hold when this ratio converges to a positive constant. The results demonstrate that while FP is guaranteed in ray-based channels, CH may or may not occur depending on the nature of the model. Furthermore, we demonstrate that LSP will not normally hold as the expected interference power grows logarithmically for both ULAs and UPAs relative to the power in the desired channel as the system size increases. Nevertheless, we identify some fundamental and attractive properties of massive MIMO in this limiting regime.

cs.IT↗

arXiv2020

DYVERSE: DYnamic VERtical Scaling in Multi-tenant Edge Environments

Multi-tenancy in resource-constrained environments is a key challenge in Edge computing. In this paper, we develop 'DYVERSE: DYnamic VERtical Scaling in Edge' environments, which is the first light-weight and dynamic vertical scaling mechanism for managing resources allocated to applications for facilitating multi-tenancy in Edge environments. To enable dynamic vertical scaling, one static and three dynamic priority management approaches that are workload-aware, community-aware and system-aware, respectively are proposed. This research advocates that dynamic vertical scaling and priority management approaches reduce Service Level Objective (SLO) violation rates. An online-game and a face detection workload in a Cloud-Edge test-bed are used to validate the research. The merits of DYVERSE is that there is only a sub-second overhead per Edge server when 32 Edge servers are deployed on a single Edge node. When compared to executing applications on the Edge servers without dynamic vertical scaling, static priorities and dynamic priorities reduce SLO violation rates of requests by up to 4% and 12% for the online game, respectively, and in both cases 6% for the face detection workload. Moreover, for both workloads, the system-aware dynamic vertical scaling method effectively reduces the latency of non-violated requests, when compared to other methods.

cs.DC↗

arXiv2020

Deep Energy Autoencoder for Noncoherent Multicarrier MU-SIMO Systems

We propose a novel deep energy autoencoder (EA) for noncoherent multicarrier multiuser single-input multipleoutput (MU-SIMO) systems under fading channels. In particular, a single-user noncoherent EA-based (NC-EA) system, based on the multicarrier SIMO framework, is first proposed, where both the transmitter and receiver are represented by deep neural networks (DNNs), known as the encoder and decoder of an EA. Unlike existing systems, the decoder of the NC-EA is fed only with the energy combined from all receive antennas, while its encoder outputs a real-valued vector whose elements stand for the subcarrier power levels. Using the NC-EA, we then develop two novel DNN structures for both uplink and downlink NC-EA multiple access (NC-EAMA) schemes, based on the multicarrier MUSIMO framework. Note that NC-EAMA allows multiple users to share the same sub-carriers, thus enables to achieve higher performance gains than noncoherent orthogonal counterparts. By properly training, the proposed NC-EA and NC-EAMA can efficiently recover the transmitted data without any channel state information estimation. Simulation results clearly show the superiority of our schemes in terms of reliability, flexibility and complexity over baseline schemes.

cs.IT↗

arXiv2020

Massive MIMO with Multi-Antenna Users under Jointly Correlated Ricean Fading

We study the uplink performance of massive multiple-input multiple-output (MIMO) when users are equipped with multiple antennas. To this end, we consider a generalized channel model that accounts for line-of-sight propagation and spatially correlated multipath fading. Most importantly, we employ the Weichselberger correlation model, which has been shown to alleviate the deficiencies of the popular Kronecker model. The main contribution of this paper is a rigorous closed-form expression for the uplink spectral efficiency using maximum-ratio combining and minimum mean square error channel estimation. Our result is a non-trivial generalization of previous results on massive MIMO with spatially correlated channels, thereby enabling us to have suitable designs for future massive MIMO systems. Numerical simulations corroborate our analysis and provide useful insights on how different propagation conditions affect system performance.

cs.IT↗

arXiv2019

3-D Positioning and Environment Mapping for mmWave Communication Systems

Millimeter-wave (mmWave) cloud radio access networks (CRANs) provide new opportunities for accurate cooperative localization, in which large bandwidths, large antenna arrays, and increased densities of base stations allow for their unparalleled delay and angular resolution. Combining localization into communications and designing simultaneous localization and mapping (SLAM) algorithms are challenging problems. This study considers the joint position and velocity estimation and environment mapping problem in a three-dimensional mmWave CRAN architecture. We first embed cooperative localization into communications and establish the joint estimation and mapping model with hybrid delay and angle measurements. Then, we propose a closed-form weighted least square (WLS) solution for the joint estimation and mapping problems. The proposed WLS estimator is proven asymptotically unbiased and confirmed by simulations as effective in achieving the Cramer-Rao lower bound (CRLB) and the desired decimeter-level accuracy. Furthermore, we propose a WLS-Net-based SLAM algorithm by embedding neural networks into the proposed WLS estimators to replace the linear approximations. The solution possesses both powerful learning ability of the neural network and robustness of the proposed geometric model, and the ensemble learning is applied to further improve positioning accuracy. A public ray-tracing dataset is used in the simulations to test the performance of the WLS-Net-based SLAM algorithm, which is proven fast and effective in attaining the centimeter-level accuracy.

cs.IT↗

arXiv2019

Channel Correlation Diversity in MU-MIMO Systems -- Analysis and Measurements

In multiuser multiple-input multiple-output (MU-MIMO) systems, channel correlation is detrimental to system performance. We demonstrate that widely used, yet overly simplified, correlation models that generate identical correlation profiles for each terminal tend to severely underestimate the system performance. In sharp contrast, more physically motivated models that capture variations in the power angular spectra across multiple terminals, generate diverse correlation patterns. This has a significant impact on the system performance. Assuming correlated Rayleigh fading and downlink zero-forcing precoding, tight closed-form approximations for the average signal-to-noise-ratio, and ergodic sum spectral efficiency are derived. Our expressions provide clear insights into the impact of diverse correlation patterns on the above performance metrics. Unlike previous works, the correlation models are parameterized with measured data from a recent 2.53 GHz urban macrocellular campaign in Cologne, Germany. Overall, results from this paper can be treated as a timely re-calibration of performance expectations from practical MU-MIMO systems.

cs.IT↗

arXiv2019

Lens-Based Beamformer for Low-Complexity Millimeter-Wave Cellular Systems

Data rate requirements for cellular communications are expected to increase 1000-fold by 2020, compared to 2010. This is mainly because of the rapid increase in the number of wireless devices and data hungry applications per-device. This creates a formidable bandwidth crisis. Milimeter-wave (mmWave) systems with massive multiple-input multiple-output (MIMO) operation are two complementary concepts poised to meet this exploding demand, as verified by the wealth of investigations by both industry and academia. Nevertheless, existing MIMO processing techniques, requiring a dedicated radio-frequency (RF) up/down-conversion chain per antenna, results in prohibitively high complexity and cost of the mmWave prototypes. The primary objective of this paper is to present a complete feasibility study on alternative beamforming techniques targeted to reduce the system complexity without drastically compromising its performance. More precisely, at 28 GHz, we investigate the end-to-end performance of two different lens-based beamforming topologies. Our study is an amalgam of theoretical modelling, electromagnetic design, and prototype manufacturing, yielding a comprehensive mmWave, massive MIMO performance evaluation.

physics.app-ph↗

arXiv2018

Massive MIMO with a Generalized Channel Model: Fundamental Aspects

Massive multiple-input multiple-output (MIMO) is becoming a mature technology, and has been approved for standardization in the 5G ecosystem. Although there is a large body of papers on the theoretical analysis of massive MIMO, the majority of relevant work assumes the simplified, yet overly idealistic, Kronecker-type model for spatial correlation. Motivated by the deficiencies of the Kronecker model, we invoke a naturally generalized spatial correlation model, that is the Weichselberger model. For this model, we pursue a comprehensive analysis of massive MIMO performance in terms of channel hardening and favorable propagation (FP). We identify a number of scenarios under which massive MIMO may fail, in terms of channel hardening and FP, and discuss their relevance from a practical perspective.

eess.SP↗

arXiv2018

Hardware-Constrained Millimeter Wave Systems for 5G: Challenges, Opportunities, and Solutions

Although millimeter wave (mmWave) systems promise to offer larger bandwidth and unprecedented peak data rates, their practical implementation faces several hardware challenges compared to sub-6 GHz communication systems. These hardware constraints can seriously undermine the performance and deployment progress of mmWave systems and, thus, necessitate disruptive solutions in the cross-design of analog and digital modules. In this article, we discuss the importance of different hardware constraints and propose a novel system architecture, which is able to release these hardware constraints while achieving better performance for future millimeter wave communication systems. The characteristics of the proposed architecture are articulated in detail, and a representative example is provided to demonstrate its validity and efficacy.

cs.IT↗

arXiv2018

On the Impact of Spillover Losses in 28 GHz Rotman Lens Arrays for 5G Applications

This work demonstrates the sensitivity of lens antenna arrays operating at millimeter-wave (mmWave) frequencies. Considering a Rotman lens array in receive mode, our investigation focuses on its most imperative defect: aberration of electromagnetic (EM) energy. Aberration leads to spillover of electric fields to neighboring ports, reducing the lens' ability to focus the EM energy to a desired port. With full EM simulations, we design a 28 GHz, 13 beam and 13 array port Rotman lens array to characterize its performance with the aforementioned impairment. Our findings show that the impact of aberration is more pronounced when the beam angles are close to the array end-fire. More critically, the corresponding impact of aberration on the desired signal and interference powers is also investigated for an uplink multiuser cellular system operating at 28 GHz. The presented results can be used as a reference to re-calibrate our expectations for Rotman lens arrays at mmWave frequencies.

eess.SP↗

arXiv2018

Hybrid Processing Design for Multipair Massive MIMO Relaying with Channel Spatial Correlation

Massive multiple-input multiple-output (MIMO) avails of simple transceiver design which can tackle many drawbacks of relay systems in terms of complicated signal processing, latency, and noise amplification. However, the cost and circuit complexity of having one radio frequency (RF) chain dedicated to each antenna element are prohibitive in practice. In this paper, we address this critical issue in amplify-and-forward (AF) relay systems using a hybrid analog and digital (A/D) transceiver structure. More specifically, leveraging the channel long-term properties, we design the analog beamformer which aims to minimize the channel estimation error and remain invariant over a long timescale. Then, the beamforming is completed by simple digital signal processing, i.e., maximum ratio combining/maximum ratio transmission (MRC/MRT) or zero-forcing (ZF) in the baseband domain. We present analytical bounds on the achievable spectral efficiency taking into account the spatial correlation and imperfect channel state information at the relay station. Our analytical results reveal that the hybrid A/D structure with ZF digital processor exploits spatial correlation and offers a higher spectral efficiency compared to the hybrid A/D structure with MRC/MRT scheme. Our numerical results showcase that the hybrid A/D beamforming design captures nearly 95% of the spectral efficiency of a fully digital AF relaying topology even by removing half of the RF chains. It is also shown that the hybrid A/D structure is robust to coarse quantization, and even with 2-bit resolution, the system can achieve more than 93% of the spectral efficiency offered by the same hybrid A/D topology with infinite resolution phase shifters.

cs.IT↗

arXiv2018

Spectral Efficiency Analysis of Multi-Cell Massive MIMO Systems with Ricean Fading

This paper investigates the spectral efficiency of multi-cell massive multiple-input multiple-output systems with Ricean fading that utilize the linear maximal-ratio combining detector. We firstly present closed-form expressions for the effective signal-to-interference-plus-noise ratio (SINR) with the least squares and minimum mean squared error (MMSE) estimation methods, respectively, which apply for any number of base-station antennas $M$ and any Ricean $K$-factor. Also, the obtained results can be particularized in Rayleigh fading conditions when the Ricean $K$-factor is equal to zero. In the following, novel exact asymptotic expressions of the effective SINR are derived in the high $M$ and high Ricean $K$-factor regimes. The corresponding analysis shows that pilot contamination is removed by the MMSE estimator when we consider both infinite $M$ and infinite Ricean $K$-factor, while the pilot contamination phenomenon persists for the rest of cases. All the theoretical results are verified via Monte-Carlo simulations.

cs.IT↗

arXiv2018

Does Massive MIMO Fail in Ricean Channels?

Massive multiple-input multiple-output (MIMO) is now making its way to the standardization exercise of future 5G networks. Yet, there are still fundamental questions pertaining to the robustness of massive MIMO against physically detrimental propagation conditions. On these grounds, we identify scenarios under which massive MIMO can potentially fail in Ricean channels, and characterize them physically, as well as, mathematically. Our analysis extends and generalizes a stream of recent papers on this topic and articulates emphatically that such harmful scenarios in Ricean fading conditions are unlikely and can be compensated using any standard scheduling scheme. This implies that massive MIMO is intrinsically effective at combating interuser interference and, if needed, can avail of the base-station scheduler for further robustness.

eess.SP↗

arXiv2017

On the Total Energy Efficiency of Cell-Free Massive MIMO

We consider the cell-free massive multiple-input multiple-output (MIMO) downlink, where a very large number of distributed multiple-antenna access points (APs) serve many single-antenna users in the same time-frequency resource. A simple (distributed) conjugate beamforming scheme is applied at each AP via the use of local channel state information (CSI). This CSI is acquired through time-division duplex operation and the reception of uplink training signals transmitted by the users. We derive a closed-form expression for the spectral efficiency taking into account the effects of channel estimation errors and power control. This closed-form result enables us to analyze the effects of backhaul power consumption, the number of APs, and the number of antennas per AP on the total energy efficiency, as well as, to design an optimal power allocation algorithm. The optimal power allocation algorithm aims at maximizing the total energy efficiency, subject to a per-user spectral efficiency constraint and a per-AP power constraint. Compared with the equal power control, our proposed power allocation scheme can double the total energy efficiency. Furthermore, we propose AP selections schemes, in which each user chooses a subset of APs, to reduce the power consumption caused by the backhaul links. With our proposed AP selection schemes, the total energy efficiency increases significantly, especially for large numbers of APs. Moreover, under a requirement of good quality-of-service for all users, cell-free massive MIMO outperforms the colocated counterpart in terms of energy efficiency.

cs.IT↗