Spatial Multiplexing of QPSK Signals with a Single Radio: Antenna Design and Over-the-Air Experiments

The paper describes the implementation and performance analysis of the first fully-operational beam-space MIMO antenna for the spatial multiplexing of two QPSK streams. The antenna is composed of a planar three-port radiator with two varactor diodes terminating the passive ports. Pattern reconfiguration is used to encode the MIMO information onto orthogonal virtual basis patterns in the far-field. A measurement campaign was conducted to compare the performance of the beam-space MIMO system with a conventional 2-by-?2 MIMO system under realistic propagation conditions. Propagation measurements were conducted for both systems and the mutual information and symbol error rates were estimated from Monte-Carlo simulations over the measured channel matrices. The results show the beam-space MIMO system and the conventional MIMO system exhibit similar finite-constellation capacity and error performance in NLOS scenarios when there is sufficient scattering in the channel. In comparison, in LOS channels, the capacity performance is observed to depend on the relative polarization of the receiving antennas.Comment: 31 pages, 23 figure

Quasi-deterministic channel modeling and experimental validation in cooperative and massive MIMO deployment topologies

Das enorme Wachstum des mobilen Datenaufkommens wird zu substantiellen Veränderungen in mobilen Netzwerken führen. Neue drahtlose Funksysteme müssen alle verfügbaren Freiheitsgrade des Übertragungskanals ausnutzen um die Kapazität zu maximieren. Dies beinhaltet die Nutzung größerer Bandbreiten, getrennter Übertragungskanäle, Antennenarrays, Polarisation und Kooperation zwischen Basisstationen. Dafür benötigt die Funkindustrie Kanalmodelle, welche das wirkliche Verhalten des Übertragungskanals in all diesen Fällen abbilden. Viele aktuelle Kanalmodelle unterstützen jedoch nur einen Teil der benötigten Funktionalität und wurden nicht ausreichend durch Messungen in relevanten Ausbreitungsszenarien validiert. Es ist somit unklar, ob die Kapazitätsvorhersagen, welche mit diesen Modellen gemacht werden, realistisch sind. In der vorliegenden Arbeit wird ein neuen Kanalmodell eingeführt, welches korrekte Ergebnisse für zwei wichtige Anwendungsfälle erzeugt: Massive MIMO und Joint-Transmission (JT) Coordinated Multi-Point (CoMP). Dafür wurde das häufig verwendete WINNER Kanalmodell um neue Funktionen erweitert. Dazu zählen 3-D Ausbreitungseffekte, sphärische Wellenausbreitung, räumliche Konsistenz, die zeitliche Entwicklung von Kanälen sowie ein neues Modell für die Polarisation. Das neue Kanalmodell wurde unter dem Akronym "QuaDRiGa" (Quasi Deterministic Radio Channel Generator, dt.: quasideterministischer Funkkanalgenerator) eingeführt. Um das Modell zu validieren wurden Messungen in Dresden und Berlin durchgeführt. Die Messdaten wurden zunächst verwendet um die Modellparameter abzuleiten. Danach wurden die Messkampagnen im Modell nachgestellt um die Reproduzierbarkeit der Ergebnisse nachzuweisen. Essentielle Leistungsindikatoren wie z.B. der Pfadverlust, die Laufzeitstreuung, die Winkelstreuung, der Geometriefaktor, die MIMO Kapazität und die Dirty-Paper-Coding Kapazität wurden für beide Datensätze berechnet. Diese wurden dann miteinander sowie mit Ergebnissen aus dem Rayleigh i.i.d. Modell und dem 3GPP-3D Kanalmodell verglichen. Für die Messungen in Dresden erzeugt das neue Modell nahezu identische Ergebnisse wenn die nachsimulierten Kanäle anstatt der Messdaten für die Bestimmung der Modellparameter verwendet werden. Solch ein direkter Vergleich war bisher nicht möglich, da die vorherigen Modelle keine ausreichend langen Kanalsequenzen erzeugen können. Die Kapazitätsvorhersagen des neuen Modells sind zu über 90% korrekt. Im Vergleich dazu konnte das 3GPP-3D Model nur etwa 80% Genauigkeit aufweisen. Diese Vorhersagen konnten auch für das Messszenario in Berlin gemacht werden, wo mehrere Basisstationen zeitgleich vermessen wurden. Dadurch konnten die gegenseitigen Störungen mit in die Bewertung eingeschlossen werden. Die Ergebnisse bestätigen die generelle Annahme, dass es möglich ist den Ausbreitungskanal sequenziell für einzelne Basisstationen zu vermessen und danach Kapazitätsvorhersagen für ganze Netzwerke mit der Hilfe von Modellen zu machen. Das neue Modell erzeugt Kanalkoeffizienten welche ähnliche Eigenschaften wie Messdaten haben. Somit können neue Algorithmen in Funksystemen schneller bewertet werden, da es nun möglich ist realistische Ergebnisse in einem frühen Entwicklungsstadium zu erhalten.The tremendous growth of mobile data traffic will lead to substantial architectural changes in wireless networks. New wireless systems need to exploit all available degrees of freedom in the wireless channel such as wider bandwidth, multi-carrier operation, large antenna arrays, polarization, and cooperation between base stations, in order to maximize the performance. The wireless industry needs channel models that reproduce the true behavior of the radio channel in all these use cases. However, many state-of-the-art models only support parts of the required functionality and have not been thoroughly validated against measurements in relevant propagations scenarios. It is therefore unclear if the performance predictions made by these models are realistic. This thesis introduces a new geometry-based stochastic channel model that creates accurate results for two important use cases: massive multiple-input multiple-output (MIMO) and joint transmission (JT) coordinated multi-point (CoMP). For this, the popular WINNER channel model was extended to incorporate 3-D propagation, spherical wave propagation, spatial consistency, temporal evolution of channels, and a new model for the polarization. This model was introduced under the acronym ``QuaDRiGa'' - quasi deterministic radio channel generator. To validate the model, measurements were done in downtown Dresden, Germany, and downtown Berlin, Germany. Those were used to derive the model parameters. Then, the measurements were resimulated with the new channel model and benchmarked against the Rayleigh i.i.d. model and the 3GPP-3D channel model. Essential performance indicators such as path gain, shadow fading, delay spread, angular spreads, geometry factor, single-link capacity, and the dirty-paper coding capacity were computed from both the measured and resimulated data. In Dresden, the resimulated channels produce almost identical results as the measured channels. When using the resimulated channels to derive the model parameters, the same results can be obtained as when using the measurement data. Such a direct comparison was not possible with the previous models because they cannot produce sufficiently long sequences of channel data. The performance predictions from the new model are more than 90% accurate whereas only 80% accuracy could be achieved with the 3GPP-3D model. In Berlin, accurate performance predictions could also be made in a multi-cellular environment where the mutual interference between the base stations could be studied. This confirms that it is generally sufficient to use single-link measurements to parameterize channel models that are then used to predict the achievable performance in wireless networks. The new model can generate channel traces with similar characteristics as measured data. This might speed up the evaluation of new algorithms because it is now possible to obtain realistic performance results already in an early stage of development

Optical MIMO communication systems under illumination constraints

Technology for wireless information access has enabled innovation of 'smart' portable consumer devices. These have been widely adopted and have become an integral part of our daily lives. They need ubiquitous connectivity to the internet to provide value added services, maximize their functionality and create a smarter world to live in. Cisco's visual networking index currently predicts wireless data consumption to increase by 61% per year. This will put additional stress on the already stressed wireless access network infrastructure creating a phenomenon called 'spectrum crunch'. At the same time, the solid state devices industry has made remarkable advances in energy efficient light-emitting-diodes (LED). The lighting industry is rapidly adopting LEDs to provide illumination in indoor spaces. Lighting fixtures are positioned to support human activities and thus are well located to act as wireless access points. The visible spectrum (380 nm - 780 nm) is yet unregulated and untapped for wireless access. This provides unique opportunity to upgrade existing lighting infrastructure and create a dense grid of small cells by using this additional 'optical' wireless bandwidth. Under the above model, lighting fixtures will service dual missions of illumination and access points for optical wireless communication (OWC). This dissertation investigates multiple-input multiple-output (MIMO) optical wireless broadcast system under unique constraints imposed by the optical channel and illumination requirements. Sample indexed spatial orthogonal frequency division multiplexing (SIS-OFDM) and metameric modulation (MM) are proposed to achieve higher spectral efficiency by exploiting dimensions of space and color respectively in addition to time and frequency. SIS-OFDM can provide significant additional spectral efficiency of up to (Nsc/2 - 1) x k bits/sym where Nsc is total number of subcarriers and k is number of bits per underlying spatial modulation symbol. MM always generates the true requested illumination color and has the potential to provide better color rendering by incorporating multiple LEDs. A normalization framework is then developed to analyze performance of optical MIMO imaging systems. Performance improvements of up to 45 dB for optical systems have been achieved by decorrelating spatially separate links by incorporating an imaging receiver. The dissertation also studies the impact of visual perception on performance of color shift keying as specified in IEEE 802.15.7 standard. It shows that non-linearity for a practical system can have a performance penalty of up to 15 dB when compared to the simplified linear system abstraction as proposed in the standard. Luminous-signal-to-noise ratio, a novel metric is introduced to compare performance of optical modulation techniques operating at same illumination intensity. The dissertation then introduces singular value decomposition based OWC system architecture to incorporate illumination constraints independent of communication constraints in a MIMO system. It then studies design paradigm for a multi-colored wavelength division multiplexed indoor OWC system

Novel Complex Adaptive Signal Processing Techniques Employing Optimally Derived Time-varying Convergence Factors With Applicatio

In digital signal processing in general, and wireless communications in particular, the increased usage of complex signal representations, and spectrally efficient complex modulation schemes such as QPSK and QAM has necessitated the need for efficient and fast-converging complex digital signal processing techniques. In this research, novel complex adaptive digital signal processing techniques are presented, which derive optimal convergence factors or step sizes for adjusting the adaptive system coefficients at each iteration. In addition, the real and imaginary components of the complex signal and complex adaptive filter coefficients are treated as separate entities, and are independently updated. As a result, the developed methods efficiently utilize the degrees of freedom of the adaptive system, thereby exhibiting improved convergence characteristics, even in dynamic environments. In wireless communications, acceptable co-channel, adjacent channel, and image interference rejection is often one of the most critical requirements for a receiver. In this regard, the fixed-point complex Independent Component Analysis (ICA) algorithm, called Complex FastICA, has been previously applied to realize digital blind interference suppression in stationary or slow fading environments. However, under dynamic flat fading channel conditions frequently encountered in practice, the performance of the Complex FastICA is significantly degraded. In this dissertation, novel complex block adaptive ICA algorithms employing optimal convergence factors are presented, which exhibit superior convergence speed and accuracy in time-varying flat fading channels, as compared to the Complex FastICA algorithm. The proposed algorithms are called Complex IA-ICA, Complex OBA-ICA, and Complex CBC-ICA. For adaptive filtering applications, the Complex Least Mean Square algorithm (Complex LMS) has been widely used in both block and sequential form, due to its computational simplicity. However, the main drawback of the Complex LMS algorithm is its slow convergence and dependence on the choice of the convergence factor. In this research, novel block and sequential based algorithms for complex adaptive digital filtering are presented, which overcome the inherent limitations of the existing Complex LMS. The block adaptive algorithms are called Complex OBA-LMS and Complex OBAI-LMS, and their sequential versions are named Complex HA-LMS and Complex IA-LMS, respectively. The performance of the developed techniques is tested in various adaptive filtering applications, such as channel estimation, and adaptive beamforming. The combination of Orthogonal Frequency Division Multiplexing (OFDM) and the Multiple-Input-Multiple-Output (MIMO) technique is being increasingly employed for broadband wireless systems operating in frequency selective channels. However, MIMO-OFDM systems are extremely sensitive to Intercarrier Interference (ICI), caused by Carrier Frequency Offset (CFO) between local oscillators in the transmitter and the receiver. This results in crosstalk between the various OFDM subcarriers resulting in severe deterioration in performance. In order to mitigate this problem, the previously proposed Complex OBA-ICA algorithm is employed to recover user signals in the presence of ICI and channel induced mixing. The effectiveness of the Complex OBA-ICA method in performing ICI mitigation and signal separation is tested for various values of CFO, rate of channel variation, and Signal to Noise Ratio (SNR)

Securing NextG networks with physical-layer key generation: A survey

As the development of next-generation (NextG) communication networks continues, tremendous devices are accessing the network and the amount of information is exploding. However, with the increase of sensitive data that requires confidentiality to be transmitted and stored in the network, wireless network security risks are further amplified. Physical-layer key generation (PKG) has received extensive attention in security research due to its solid information-theoretic security proof, ease of implementation, and low cost. Nevertheless, the applications of PKG in the NextG networks are still in the preliminary exploration stage. Therefore, we survey existing research and discuss (1) the performance advantages of PKG compared to cryptography schemes, (2) the principles and processes of PKG, as well as research progresses in previous network environments, and (3) new application scenarios and development potential for PKG in NextG communication networks, particularly analyzing the effect and prospects of PKG in massive multiple-input multiple-output (MIMO), reconfigurable intelligent surfaces (RISs), artificial intelligence (AI) enabled networks, integrated space-air-ground network, and quantum communication. Moreover, we summarize open issues and provide new insights into the development trends of PKG in NextG networks

Seventy Years of Radar and Communications: The road from separation to integration

Radar and communications (R&C) as key utilities of electromagnetic (EM) waves have fundamentally shaped human society and triggered the modern information age. Although R&C had been historically progressing separately, in recent decades, they have been converging toward integration, forming integrated sensing and communication (ISAC) systems, giving rise to new highly desirable capabilities in next-generation wireless networks and future radars. To better understand the essence of ISAC, this article provides a systematic overview of the historical development of R&C from a signal processing (SP) perspective. We first interpret the duality between R&C as signals and systems, followed by an introduction of their fundamental principles. We then elaborate on the two main trends in their technological evolution, namely, the increase of frequencies and bandwidths and the expansion of antenna arrays. We then show how the intertwined narratives of R&C evolved into ISAC and discuss the resultant SP framework. Finally, we overview future research directions in this field

Analysis and Design of Cell-Free Massive MIMO Systems under Spatially Correlated Fading Channels

Mención Internacional en el título de doctorWireless communications have become a key pillar in our modern society. It can be hard to think of a service that somehow does not rely on them. Particularly, mobile networks are one of the most necessary technologies in our daily life. This produces that the demand for data rates is by no means stopping from increasing. The cellular architecture is facing a crucial challenge under limited performance by interference and spectrum saturation. This involves cell-edge users experiencing poor performance due to the close vicinity of base stations (BSs) using the same carrier frequency. Based on a combination of the coordinated multi-point (CoMP) technique and traditional massive multiple-input multiple-output (MIMO) systems, cell-free (CF) massive MIMO networks have irrupted as a solution for avoiding inter-cell interference issues and for providing uniform service in large coverage areas. This thesis focuses on the analysis and design of CF massive MIMO networks assuming a spatially correlated fading model. A general-purpose channel model is provided and the whole network functioning is given in detail. Despite the many characteristics a CF massive MIMO system shares with conventional colocated massive MIMO its distributed nature brings along new issues that need to be carefully accounted for. In particular, the so-called channel hardening effect that postulates that the variance of the compound wireless channel experienced by a given user from a large number of transmit antennas tends to vanish, effectively making the channel deterministic. This critical assumption, which permeates most theoretical results of massive MIMO, has been well investigated and validated in centralized architectures, however, it has received little attention in the context of CF massive MIMO networks. Hardening in CF architectures is potentially compromised by the different large-scale gains each access point (AP) impinges on the transmitted signal to each user, a condition that is further stressed when not all APs transmit to all users as proposed in the user-centric (UC) variations of CF massive MIMO. In this document, the presence of channel hardening in this new architecture scheme is addressed using distributed and cooperative precoders and combiners and different power control strategies. It is shown that the line-of-sight (LOS) component, spatially correlated antennas, and clustering schemes have an impact on how the channel hardens. In addition, we examine the existent gap between the estimated achievable rate and the true network performance when channel hardening is compromised. Exact closed-form expressions for both a hardening metric and achievable downlink (DL) and uplink (UL) rates are given as well. We also look into the pilot contamination problem in the UL and DL with different degrees of cooperation between the APs. The optimum minimum mean-squared error (MMSE) processing can take advantage of large-scale fading coefficients for canceling the interference of pilot-sharing users and thus achieves asymptotically unbounded capacity. However, it is computationally demanding and can only be implemented in a fully centralized network. Here, sub-optimal schemes are derived that provide unbounded capacity with much lower complexity and using only local channel estimates but global channel statistics. This makes them suited for both centralized and distributed networks. In this latter case, the best performance is achieved with a generalized maximum ratio combiner that maximizes a capacity bound based on channel statistics only.Programa de Doctorado en Multimedia y Comunicaciones por la Universidad Carlos III de Madrid y la Universidad Rey Juan CarlosPresidente: Rui Dinis.- Secretario: María Julia Fernández-Getino García.- Vocal: Carmen Botella Mascarel