There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Introduction to linear and nonlinear programming

Fast Fourier Transform

The emerging massive/large-scale multiple-input multiple-output (LS-MIMO) systems that rely on very large antenna arrays have become a hot topic of wireless communications. Compared to multi-antenna aided systems being built at the time of this writing, such as the long-term evolution (LTE) based fourth generation (4G) mobile communication system which allows for up to eight antenna elements at the base station (BS), the LS-MIMO system entails an unprecedented number of antennas, say 100 or more, at the BS. The huge leap in the number of BS antennas opens the door to a new research field in communication theory, propagation and electronics, where random matrix theory begins to play a dominant role. Interestingly, LS-MIMOs also constitute a perfect example of one of the key philosophical principles of the Hegelian Dialectics, namely, that “quantitative change leads to qualitative change.” In this treatise, we provide a recital on the historic heritages and novel challenges facing LS-MIMOs from a detection perspective. First, we highlight the fundamentals of MIMO detection, including the nature of co-channel interference (CCI), the generality of the MIMO detection problem, the received signal models of both linear memoryless MIMO channels and dispersive MIMO channels exhibiting memory, as well as the complex-valued versus real-valued MIMO system models. Then, an extensive review of the representative MIMO detection methods conceived during the past 50 years (1965–2015) is presented, and relevant insights as well as lessons are inferred for the sake of designing complexity-scalable MIMO detection algorithms that are potentially applicable to LS-MIMO systems. Furthermore, we divide the LS-MIMO systems into two types, and elaborate on the distinct detection strategies suitable for each of them. The type-I LS-MIMO corresponds to the case where the number of active users is much smaller than the number of BS antennas, which is currently the mainstream definition of LS-MIMO. The type-II LS-MIMO corresponds to the case where the number of active users is comparable to the number of BS antennas. Finally, we discuss the applicability of existing MIMO detection algorithms in LS-MIMO systems, and review some of the recent advances in LS-MIMO detection.

/pdf/fifty-years-of-mimo-detection-the-road-to-large-scale-mimos-44ejto9lpw.pdf

Fifty Years of MIMO Detection: The Road to Large-Scale MIMOs

Suggested by the structure of the visual nervous system, a new algorithm is proposed for pattern recognition. This algorithm can be realized with a multilayered network consisting of neuron-like cells. The network, “neocognitron”, is self-organized by unsupervised learning, and acquires the ability to recognize stimulus patterns according to the differences in their shapes: Any patterns which we human beings judge to be alike are also judged to be of the same category by the neocognitron. The neocognitron recognizes stimulus patterns correctly without being affected by shifts in position or even by considerable distortions in shape of the stimulus patterns.

Neocognitron--A New Algorithm for Pattern Recognition Tolerant of Deformations and Shifts in Position

Wordlength determination is an indispensable task in digital hardware implementations of signal processing algorithms because the wordlength affects power consumption and system performance Actual digital systems add extra bits in circuit design to avoid the worst condition caused by lack of dynamic range However, they still have room to reduce a wordlength during better conditions We present a variable wordlength technique for dynamically controlling the wordlength used in wireless OFDM receivers The key point is that the receiver optimizes the wordlength while operating by sensing current receiver performance The proposed technique can reduce a wordlength compared with use of a fixed wordlength and satisfy the user-required communication quality of PER The results show that the receiver has reduced dissipated energy by 181 to 303% with the PER criterion of 10-2

Use of a Variable Wordlength Technique in an OFDM Receiver to Reduce Energy Dissipation

In this paper, we present an FPGA implementation of low-latency video transmission system. The proposed system is capable of lossless video transmission using line-based compression. Assuming transmission over wireless communication channel where the data throughput dynamically changes, our system supports lossless to near-lossless scalable compression. According to the FPGA implementation result, we confirmed that our system can archive 45% of data reduction in average and can be implemented using 14,777 slice LUTs and 4,343 slice registers.

An FPGA implementation of low-latency video transmission system using lossless and near-lossless line-based compression

This paper presents a VLSI architecture of MMSE detection in a 4×4 MIMO-OFDM receiver. Packet-based MIMO-OFDM imposes a considerable throughput requirement on the matrix inversion because of strict timing in frame structure and subcarrier-by-subcarrier basis processing. Pipeline processing oriented algorithms are preferable to tackle this issue. We propose a pipelined MMSE detector using Strassen's algorithms of matrix inversion and multiplication. This circuit achieves real-time operation which does not depend on numbers of subcarriers. The designed circuit has been implemented to a 90-nm CMOS process and shows a potential for providing a 2.6-Gbps transmission speed in a 160-MHz signal bandwidth.

VLSI Implementation of a Complete Pipeline MMSE Detector for a 4 × 4 MIMO-OFDM Receiver

The paper explores the extraction of speech features aiming at noise robustness for speech recognition and proposes advanced speech analysis techniques named RSF/DRA (running spectrum filtering/dynamic range adjustment). The proposed techniques, DRA and RSF, focus on speech feature adjustment. DRA normalizes cepstral dynamic ranges and RSF eliminates the jitter influences of speech feature parameters. Experiments on isolated word recognition were carried out using 40 male and 40 female speakers for training and 5 male and 5 female speakers for recognition. The results of the recognition rate improving from 17% to 63% versus running car noise at -10 dB SNR show the effectiveness and high noise robustness of the proposed method.

Robust speech recognition with feature extraction using combined method of RSF and DRA

This paper is devoted to autonomous device-to-device (D2D) communication in cellular networks. The aim of each D2D pair is to maximize its throughput subject to the minimum signal-to-interference-plus-noise ratio (SINR) constraints. This problem is represented by a stochastic non-cooperative game where the players (D2D pairs) have no prior information on the availability and quality of selected channels. Therefore, each player in this game becomes a “learner” which explores all of its possible strategies based on the locally-observed throughput and state (defined by the channel quality). Consequently, we propose a multi-agent Q-learning algorithm based on the players' “beliefs” about the strategies of their counterparts and show its implementation in a Long Term Evolution - Advanced (LTE-A) network. As follows from simulations, the algorithm achieves a near-optimal performance after a small number of iterations.

Multi-agent Q-learning for autonomous D2D communication

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