[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Massive multiple-input multiple-output (MIMO) wireless communications refers to the idea equipping cellular base stations (BSs) with a very large number of antennas, and has been shown to potentially allow for orders of magnitude improvement in spectral and energy efficiency using relatively simple (linear) processing. In this paper, we present a comprehensive overview of state-of-the-art research on the topic, which has recently attracted considerable attention. We begin with an information theoretic analysis to illustrate the conjectured advantages of massive MIMO, and then we address implementation issues related to channel estimation, detection and precoding schemes. We particularly focus on the potential impact of pilot contamination caused by the use of non-orthogonal pilot sequences by users in adjacent cells. We also analyze the energy efficiency achieved by massive MIMO systems, and demonstrate how the degrees of freedom provided by massive MIMO systems enable efficient single-carrier transmission. Finally, the challenges and opportunities associated with implementing massive MIMO in future wireless communications systems are discussed.

/pdf/an-overview-of-massive-mimo-benefits-and-challenges-5e3yrz2gcj.pdf

An Overview of Massive MIMO: Benefits and Challenges

In the near future, i.e., beyond 4G, some of the prime objectives or demands that need to be addressed are increased capacity, improved data rate, decreased latency, and better quality of service. To meet these demands, drastic improvements need to be made in cellular network architecture. This paper presents the results of a detailed survey on the fifth generation (5G) cellular network architecture and some of the key emerging technologies that are helpful in improving the architecture and meeting the demands of users. In this detailed survey, the prime focus is on the 5G cellular network architecture, massive multiple input multiple output technology, and device-to-device communication (D2D). Along with this, some of the emerging technologies that are addressed in this paper include interference management, spectrum sharing with cognitive radio, ultra-dense networks, multi-radio access technology association, full duplex radios, millimeter wave solutions for 5G cellular networks, and cloud technologies for 5G radio access networks and software defined networks. In this paper, a general probable 5G cellular network architecture is proposed, which shows that D2D, small cell access points, network cloud, and the Internet of Things can be a part of 5G cellular network architecture. A detailed survey is included regarding current research projects being conducted in different countries by research groups and institutions that are working on 5G technologies.

A Survey of 5G Network: Architecture and Emerging Technologies

The fourth generation wireless communication systems have been deployed or are soon to be deployed in many countries. However, with an explosion of wireless mobile devices and services, there are still some challenges that cannot be accommodated even by 4G, such as the spectrum crisis and high energy consumption. Wireless system designers have been facing the continuously increasing demand for high data rates and mobility required by new wireless applications and therefore have started research on fifth generation wireless systems that are expected to be deployed beyond 2020. In this article, we propose a potential cellular architecture that separates indoor and outdoor scenarios, and discuss various promising technologies for 5G wireless communication systems, such as massive MIMO, energy-efficient communications, cognitive radio networks, and visible light communications. Future challenges facing these potential technologies are also discussed.

/pdf/cellular-architecture-and-key-technologies-for-5g-wireless-f1phgmmodu.pdf

Cellular architecture and key technologies for 5G wireless communication networks

In this paper, we analyze the frequency domain linear equalization (FDLE) of single carrier block transmission (SCBT) systems under fast fading channel. First, we propose a new approximating model in which the channel is assumed to be static in sub-blocks vary each other. Based on this model, we derive a new 2-orthogonal-sub-blocked frequency domain equalization method. Then, we derive the conditions of the channel under which the equalization method can be applied to the 2-orthogonal-sub-blocked systems. Simulation demonstrates that the proposed method can improve the anti-Doppler ability of SC-FDLE and at the same time keep its high efficiency and low complexity.

A sub-block orthogonal single carrier frequency domain equalization system in fast Rayleigh fading channel

User Scheduling Algorithms for Downlink MU-MIMO System Based on the SCSI

In this paper, we consider the user positioning problem in the massive multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) system with a uniform planner antenna (UPA) array. Taking advantage of the UPA array geometry and wide bandwidth, we advocate the use of the angle-delay channel power matrix (ADCPM) as a new type of fingerprint to replace the traditional ones. The ADCPM embeds the stable and stationary multipath characteristics, e.g. delay, power, and angle in the vertical and horizontal directions, which are beneficial to positioning. Taking ADCPM fingerprints as the inputs, we propose a novel three-dimensional (3D) convolution neural network (CNN) enabled learning method to localize users' 3D positions. In particular, such a 3D CNN model consists of a convolution refinement module to refine the elementary feature maps from the ADCPM fingerprints, three extended Inception modules to extract the advanced feature maps, and a regression module to estimate the 3D positions. By intensive simulations, the proposed 3D CNN-enabled positioning method is demonstrated to achieve higher positioning accuracy than the traditional searching-based ones, with reduced computational complexity and storage overhead, and the ADCPM fingerprints are more robust to noise contamination.

Learning to Localize: A 3D CNN Approach to User Positioning in Massive MIMO-OFDM Systems

The ergodic capacity of a multiple antenna system in Rician fading is considered under the assumption that channel state information (CSI) is available only at the receiver and the transmitter has no knowledge of the CSI. Using complex non-central Wishart distribution and Bartlett's decomposition, we derive a tight closed-form upper bound on the ergodic capacity of such channels. We show that our bound is tighter than previously reported analytical bound. Moreover, we provide an approximation of ergodic capacity in high-SNR regime. Numerical results also show that our results closely match the actual ergodic capacity of Rician fading MIMO channels.

Tight upper bound on the ergodic capacity of the Rician fading MIMO channels

In this paper, we investigate maximum-distance separable (MDS) codes and cluster based coded caching in fog radio access networks (F-RANs). In order to minimize the fronthaul rate, multicast opportunities need to be constructed at the cloud server. Firstly, a redundant MDS codes based coded placement scheme is proposed to provide redundant coded packets and symmetrical cache contents. The redundant coded packets can be used to construct multicast opportunities for requests on the same file. Furthermore, based on the symmetrical cache contents, we propose a cluster cooperation based coded delivery scheme, which can induce considerable multicast opportunities between any two clusters regardless of whether the requests are on the same file or not. Finally, by utilizing the redundant coded packets and the symmetry of cache contents, a joint redundant MDS codes and cluster cooperation based coded caching policy is proposed to minimize the fronthaul rate. Simulation results show that our proposed policy can provide 30% savings of the fronthaul rate compared to the MDS-based uncoded delivery policy.

/pdf/joint-redundant-mds-codes-and-cluster-cooperation-based-57qtr0dhku.pdf

Joint Redundant MDS Codes and Cluster Cooperation Based Coded Caching in Fog Radio Access Networks

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