Sherman-Morrison Regularization for ELAA Iterative Linear Precoding

The design of iterative linear precoding is recently challenged by extremely large aperture array (ELAA) systems, where conventional preconditioning techniques could hardly improve the channel condition. In this paper, it is proposed to regularize the extreme singular values to improve the channel condition by deducting a rank-one matrix from the Wishart matrix of the channel. Our analysis proves the feasibility to reduce the largest singular value or to increase multiple small singular values with a rank-one matrix when the singular value decomposition of the channel is available. Knowing the feasibility, we propose a low-complexity approach where an approximation of the regularization matrix can be obtained based on the statistical property of the channel. It is demonstrated, through simulation results, that the proposed low-complexity approach significantly outperforms current preconditioning techniques in terms of reduced iteration number for more than $10\%$ in both ELAA systems as well as symmetric multi-antenna (i.e., MIMO) systems when the channel is i.i.d. Rayleigh fading.Comment: 7 pages, 5 figures, IEEE ICC 202

Alternative Normalized-Preconditioning for Scalable Iterative Large-MIMO Detection

Signal detection in large multiple-input multiple-output (large-MIMO) systems presents greater challenges compared to conventional massive-MIMO for two primary reasons. First, large-MIMO systems lack favorable propagation conditions as they do not require a substantially greater number of service antennas relative to user antennas. Second, the wireless channel may exhibit spatial non-stationarity when an extremely large aperture array (ELAA) is deployed in a large-MIMO system. In this paper, we propose a scalable iterative large-MIMO detector named ANPID, which simultaneously delivers 1) close to maximum-likelihood detection performance, 2) low computational-complexity (i.e., square-order of transmit antennas), 3) fast convergence, and 4) robustness to the spatial non-stationarity in ELAA channels. ANPID incorporates a damping demodulation step into stationary iterative (SI) methods and alternates between two distinct demodulated SI methods. Simulation results demonstrate that ANPID fulfills all the four features concurrently and outperforms existing low-complexity MIMO detectors, especially in highly-loaded large MIMO systems.Comment: Accepted by IEEE GLOBECOM 202

The Four-C Framework for High Capacity Ultra-Low Latency in 5G Networks: A Review

Network latency will be a critical performance metric for the Fifth Generation (5G) networks expected to be fully rolled out in 2020 through the IMT-2020 project. The multi-user multiple-input multiple-output (MU-MIMO) technology is a key enabler for the 5G massive connectivity criterion, especially from the massive densification perspective. Naturally, it appears that 5G MU-MIMO will face a daunting task to achieve an end-to-end 1 ms ultra-low latency budget if traditional network set-ups criteria are strictly adhered to. Moreover, 5G latency will have added dimensions of scalability and flexibility compared to prior existing deployed technologies. The scalability dimension caters for meeting rapid demand as new applications evolve. While flexibility complements the scalability dimension by investigating novel non-stacked protocol architecture. The goal of this review paper is to deploy ultra-low latency reduction framework for 5G communications considering flexibility and scalability. The Four (4) C framework consisting of cost, complexity, cross-layer and computing is hereby analyzed and discussed. The Four (4) C framework discusses several emerging new technologies of software defined network (SDN), network function virtualization (NFV) and fog networking. This review paper will contribute significantly towards the future implementation of flexible and high capacity ultra-low latency 5G communications

대규모 다중 안테나 환경에서 낮은 복잡도의 다중 사용자 신호전송에 관한 연구

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 전기·컴퓨터공학부, 2020. 8. 이용환.Advanced wireless communication systems may employ massive multi-input multi-output (m-MIMO) techniques for performance improvement. A base station equipped with an m-MIMO configuration can serve a large number of users by means of beamforming. The m-MIMO channel becomes asymptotically orthogonal to each other as the number of antennas increases to infinity. In this case, we may optimally transmit signal by means of maximum ratio transmission (MRT) with affordable implementation complexity. However, the MRT may suffer from inter-user interference in practical m-MIMO environments mainly due to the presence of insufficient channel orthogonality. The use of zero-forcing beamforming can be a practical choice in m-MIMO environments since it can easily null out inter-user interference. However, it may require huge computational complexity for the generation of beam weight. Moreover, it may suffer from performance loss associated with the interference nulling, referred to transmission performance loss (TPL). The TPL may become serious when the number of users increases or the channel correlation increases in spatial domain. In this dissertation, we consider complexity-reduced multi-user signal transmission in m-MIMO environments. We determine the beam weight to maximize the signal-to-leakage plus noise ratio (SLNR) instead of signal-to-interference plus noise ratio (SINR). We determine the beam direction assuming combined use of MRT and partial ZF that partially nulls out interference. For further reduction of computational complexity, we determine the beam weight based on the approximated SLNR. We consider complexity-reduced ZF beamforming that generates the beam weight in a group-wise manner. We partition users into a number of groups so that users in each group experience low TPL. We approximately estimate the TPL for further reduction of computational complexity. Finally, we determine the beam weight for each user group based on the approximated TPL.차세대 무선 통신 시스템에서 성능 향상을 위해 대규모 다중 안테나 (massive MIMO) 기술들을 사용할 수 있다. 대규모 안테나를 가진 기지국은 많은 수의 사용자들을 빔포밍 (beamforming)으로 서비스해줄 수 있다. 안테나 수가 무한히 증가함에 따라서 채널은 점근적으로 서로 직교 (orthogonal)하게 된다. 이러한 경우, 낮은 실장 복잡도를 가지는 최대 비 전송 (maximum ratio transmission)을 사용함으로써 신호전송을 최적화할 수 있다. 하지만, 현실적인 대규모 다중 안테나 환경에서는 채널 직교성이 충분하지 못하기 때문에 최대 비 전송은 간섭에 의한 성능 저하를 겪을 수 있다. 제로-포싱 (zero-forcing) 빔포밍은 간섭을 쉽게 제거할 수 있기 때문에 대규모 다중 안테나 환경에서 현실적인 선택이 될 수 있다. 하지만, 제로-포싱은 빔 가중치 (beam weight) 생성으로 인해 높은 계산 복잡도를 요구할 수 있다. 뿐만 아니라, 제로-포싱은 간섭 제거에 대한 대가로 심각한 성능 저하 (즉, transmission performance loss; TPL)를 겪을 수 있다. TPL은 사용자 수가 많거나 채널의 공간 상관도가 클 때 더 심각해질 수 있다. 본 논문에서 대규모 다중 안테나 환경에서 낮은 복잡도의 다중 사용자 신호전송을 고려한다. 제안 기법은 신호-대-간섭 및 잡음 비 (signal-to-interference plus noise ratio) 대신 신호-대-유출 및 잡음 비 (signal-to-leakage plus noise ratio)를 최대화하는 빔 가중치를 결정한다. 제안 기법은 최대 비 전송과 간섭을 선택적으로 제거하는 부분 제로-포싱 (partial zero-forcing)의 사용을 기반으로 빔 방향을 결정한다. 계산 복잡도를 더 감소시키기 위해서, 제안 기법은 근사화된 신호-대-유출 및 잡음비를 사용하여 빔 가중치를 결정한다. 본 논문에서 그룹 기반으로 빔 가중치를 생성하는 낮은 복잡도의 제로-포싱 빔포밍 전송을 고려한다. 제안 기법은 사용자들이 낮은 TPL을 갖도록 사용자들을 다수의 그룹으로 분리시킨다. 계산 복잡도를 더 감소시키기 위해서, 제안 기법은 TPL을 근사적으로 추정한다. 마지막으로, 제안 기법은 근사화된 TPL을 기반으로 형성된 각 사용자 그룹에 대하여 빔 가중치를 결정한다.Chapter 1. Introduction 1 Chapter 2. System model 10 Chapter 3. Complexity-reduced multi-user signal transmission 15 3.1. Previous works 15 3.2. Proposed scheme 24 3.3. Performance evaluation 47 Chapter 4. User grouping-based ZF transmission 57 4.1. Spatially correlated channel 57 4.2. Previous works 59 4.3. Proposed scheme 66 4.4. Performance evaluation 87 Chapter 5. Conclusions and further research issues 94 Appendix 97 A. Proof of Lemma 3-4 97 B. Proof of Lemma 3-5 100 C. Proof of strict quasi-concavity of SLNR_(k) 101 References 103 Korean Abstract 115Docto

Channel estimation techniques for next generation mobile communication systems

Mención Internacional en el título de doctorWe are witnessing a revolution in wireless technology, where the society is demanding new services, such as smart cities, autonomous vehicles, augmented reality, etc. These challenging services not only are demanding an enormous increase of data rates in the range of 1000 times higher, but also they are real-time applications with an important delay constraint. Furthermore, an unprecedented number of different machine-type devices will be also connected to the network, known as Internet of Things (IoT), where they will be transmitting real-time measurements from different sensors. In this context, the Third Generation Partnership Project (3GPP) has already developed the new Fifth Generation (5G) of mobile communication systems, which should be capable of satisfying all the requirements. Hence, 5G will provide three key aspects, such as: enhanced mobile broad-band (eMBB) services, massive machine type communications (mMTC) and ultra reliable low latency communications (URLLC). In order to accomplish all the mentioned requirements, it is important to develop new key radio technologies capable of exploiting the wireless environment with a higher efficiency. Orthogonal frequency division multiplexing (OFDM) is the most widely used waveform by the industry, however, it also exhibits high side lobes reducing considerably the spectral efficiency. Therefore, filter-bank multi-carrier combined with offset quadrature amplitude modulation (FBMC-OQAM) is a waveform candidate to replace OFDM due to the fact that it provides extremely low out-ofband emissions (OBE). The traditional spectrum frequencies range is close to saturation, thus, there is a need to exploit higher bands, such as millimeter waves (mm-Wave), making possible the deployment of ultra broad-band services. However, the high path loss in these bands increases the blockage probability of the radio-link, forcing us to use massive multiple-input multiple-output (MIMO) systems in order to increase either the diversity or capacity of the overall link. All these emergent radio technologies can make 5G a reality. However, all their benefits can be only exploited under the knowledge and availability of the channel state information (CSI) in order to compensate the effects produced by the channel. The channel estimation process is a well known procedure in the area of signal processing for communications, where it is a challenging task due to the fact that we have to obtain a good estimator, maintaining at the same time the efficiency and reduced complexity of the system and obtaining the results as fast as possible. In FBMC-OQAM, there are several proposed channel estimation techniques, however, all of them required a high number of operations in order to deal with the self-interference produced by the prototype filter, hence, increasing the complexity. The existing channel estimation and equalization techniques for massive MIMO are in general too complex due to the large number of antennas, where we must estimate the channel response of each antenna of the array and perform some prohibitive matrix inversions to obtain the equalizers. Besides, for the particular case of mm-Wave, the existing techniques either do not adapt well to the dynamic ranges of signal-to-noise ratio (SNR) scenarios or they assume some approximations which reduce the quality of the estimator. In this thesis, we focus on the channel estimation for different emerging techniques that are capable of obtaining a better performance with a lower number of operations, suitable for low complexity devices and for URLLC. Firstly, we proposed new pilot sequences for FBMC-OQAM enabling the use of a simple averaging process in order to obtain the CSI. We show that our technique outperforms the existing ones in terms of complexity and performance. Secondly, we propose an alternative low-complexity way of computing the precoding/postcoding equalizer under the scenario of massive MIMO, keeping the quality of the estimator. Finally, we propose a new channel estimation technique for massive MIMO for mm-Wave, capable of adapting to very variable scenarios in terms of SNR and outperforming the existing techniques. We provide some analysis of the mean squared error (MSE) and complexity of each proposed technique. Furthermore, some numerical results are given in order to provide a better understanding of the problem and solutions.Programa de Doctorado en Multimedia y Comunicaciones por la Universidad Carlos III de Madrid y la Universidad Rey Juan CarlosPresidente: Antonia María Tulino.- Secretario: Máximo Morales Céspedes.- Vocal: Octavia A. Dobr

Review of Recent Trends

This work was partially supported by the European Regional Development Fund (FEDER), through the Regional Operational Programme of Centre (CENTRO 2020) of the Portugal 2020 framework, through projects SOCA (CENTRO-01-0145-FEDER-000010) and ORCIP (CENTRO-01-0145-FEDER-022141). Fernando P. Guiomar acknowledges a fellowship from “la Caixa” Foundation (ID100010434), code LCF/BQ/PR20/11770015. Houda Harkat acknowledges the financial support of the Programmatic Financing of the CTS R&D Unit (UIDP/00066/2020).MIMO-OFDM is a key technology and a strong candidate for 5G telecommunication systems. In the literature, there is no convenient survey study that rounds up all the necessary points to be investigated concerning such systems. The current deeper review paper inspects and interprets the state of the art and addresses several research axes related to MIMO-OFDM systems. Two topics have received special attention: MIMO waveforms and MIMO-OFDM channel estimation. The existing MIMO hardware and software innovations, in addition to the MIMO-OFDM equalization techniques, are discussed concisely. In the literature, only a few authors have discussed the MIMO channel estimation and modeling problems for a variety of MIMO systems. However, to the best of our knowledge, there has been until now no review paper specifically discussing the recent works concerning channel estimation and the equalization process for MIMO-OFDM systems. Hence, the current work focuses on analyzing the recently used algorithms in the field, which could be a rich reference for researchers. Moreover, some research perspectives are identified.publishersversionpublishe

Performance of channel estimation schemes in the presence of gaussian mixture model

Channel estimation (CE) plays a crucial role in establishing a wireless link, specifically at the receiver node. Most of the receivers that estimate the channel is in the presence of AWGN. However, these schemes perform expressively worse when the impulsive noise is added in AWGN which is introduced by manmade sources (pressure cooker, motorbike, electric supply) as well as natural noises (earthquakes and thundering). The major contribution of this research is to analyze the channel estimation schemes in the Gaussian mixture model (GMM) environment. The performance of channel estimation schemes has been compared in terms of mean square error (MSE) and bit error rate (BER). Four channel estimation schemes e.g., MMSE, DFT, correlation- based methods like Gauss-Seidel (GS) and Successive Over- Relaxation (SOR), are studied and analyzed. The study reveals that the correlation scheme based on the method of SOR is more effective as compared to the methods of DFT, MMSE and GS because of faster convergence rate along with the minimum number of iteration. SOR shows sustainable results up to the probability of an impulsive element of 5 Percent.Postprint (published version

5G Outlook – Innovations and Applications

5G Outlook - Innovations and Applications is a collection of the recent research and development in the area of the Fifth Generation Mobile Technology (5G), the future of wireless communications. Plenty of novel ideas and knowledge of the 5G are presented in this book as well as divers applications from health science to business modeling. The authors of different chapters contributed from various countries and organizations. The chapters have also been presented at the 5th IEEE 5G Summit held in Aalborg on July 1, 2016. The book starts with a comprehensive introduction on 5G and its need and requirement. Then millimeter waves as a promising spectrum to 5G technology is discussed. The book continues with the novel and inspiring ideas for the future wireless communication usage and network. Further, some technical issues in signal processing and network design for 5G are presented. Finally, the book ends up with different applications of 5G in distinct areas. Topics widely covered in this book are: • 5G technology from past to present to the future• Millimeter- waves and their characteristics• Signal processing and network design issues for 5G• Applications, business modeling and several novel ideas for the future of 5