半導体光増幅器を用いた光デジタル・アナログ相互変換

　デジタル・アナログ変換(D/A変換)とアナログ・デジタル変換(A/D変換)は，電子デバイスや光学システム内でデジタル信号とアナログ信号を接続するための重要な機能であり，通信ネットワークを含む幅広い分野で利用されている．近年，デジタル信号処理技術の発達に伴い，より高性能なD/A変換器やA/D変換器の需要が高まっている．しかし，電気的なD/A変換器やA/D変換器は，ジッタ制限，電磁干渉，RC遅延などの高速動作における固有のボトルネックを有している．よって，コストや複雑さを犠牲とし，1つのシステムに複数の電気的なD/A変換器やA/D変換器を様々な手法で統合し，高速な変換を実現している．一方，光信号処理は電気信号処理の限界を克服できるため，光D/A変換器や光A/D変換器の実現が注目されている．主に特殊な光ファイバ内で発生する非線形光学効果を用いた光D/A変換器や光A/D変換器が報告されているが，構成が複雑であり，高いパワーが必要といった課題がある．　半導体光増幅器(SOA)は，小型かつ低消費電力であり，高い非線形性を有していることから，波長変換などの光信号処理デバイスとしても利用されている．SOAを用いた光D/A変換や光A/D変換は，相互利得変調を用いた手法がそれぞれ1件ずつ報告されており，2 bitの変換を実証しているが，高分解能化には多数のSOAが必要となる等の課題が存在する．　周波数チャープは，SOAで発生する特異な現象であり，デバイスの屈折率変化に基づいて周波数変動を誘導する．これまでに，SOAのチャープ特性が，長波長側への周波数シフトであるレッドチャープと短波長側への周波数シフトであるブルーチャープが異なる特性を有することを示されている．このレッドチャープを活用した光A/D変換器が提案されており，構成な構成かつ低入力パワーで8レベルの光量子化に成功している．　本論文では，SOAのブルーチャープを用いた光D/A変換の検討を行い，2 bitの光D/A変換を実証した．そして，その変換性能を微分非線形性(DNL)，積分非線形性(INL)，有効ビット数(ENOB)を用いて評価した．さらに，ブルーチャープを用いた光D/A変換とレッドチャープを用いた光A/D変換を組み合わせた，2 bitの光デジタル・アナログ相互変換を実証した．周波数チャープを用いた光D/A変換と光A/D変換は，単一のSOAを用いた簡素な構成とモノリシック集積の可能性を有している．得られた結果は，アナログ信号とデジタル信号を光領域で相互接続する手法として，提案方式の有用性を示した．電気通信大学201

A Programmable ROADM System for SDM/WDM Networks

This paper proposed and evaluated a programmable ROADM system for MCF-based SDM/WDM networks. The proposed ROADM system employing both bypass connection and Route-and-Select wavelength switching enables adaptable virtual topology in optical networks by dynamically configuring bypass connection cores. The simulation results confirmed this ROADM system could provide acceptable performance with an around 10–20% reduction in the total cost including the number of ports and WSSs by comparing with a fully flexible SDM/WDM ROADM system, which cannot be implemented due to the required extremely high-port-count WSSs

Sixth Generation (6G)Wireless Networks: Vision, Research Activities, Challenges and Potential Solutions

The standardization activities of the fifth generation communications are clearly over and deployment has commenced globally. To sustain the competitive edge of wireless networks, industrial and academia synergy have begun to conceptualize the next generation of wireless communication systems (namely, sixth generation, (6G)) aimed at laying the foundation for the stratification of the communication needs of the 2030s. In support of this vision, this study highlights the most promising lines of research from the recent literature in common directions for the 6G project. Its core contribution involves exploring the critical issues and key potential features of 6G communications, including: (i) vision and key features; (ii) challenges and potential solutions; and (iii) research activities. These controversial research topics were profoundly examined in relation to the motivation of their various sub-domains to achieve a precise, concrete, and concise conclusion. Thus, this article will contribute significantly to opening new horizons for future research direction

Detection and Tracking of Pedestrians Using Doppler LiDAR

Pedestrian detection and tracking is necessary for autonomous vehicles and traffic manage- ment. This paper presents a novel solution to pedestrian detection and tracking for urban scenarios based on Doppler LiDAR that records both the position and velocity of the targets. The workflow consists of two stages. In the detection stage, the input point cloud is first segmented to form clus- ters, frame by frame. A subsequent multiple pedestrian separation process is introduced to further segment pedestrians close to each other. While a simple speed classifier is capable of extracting most of the moving pedestrians, a supervised machine learning-based classifier is adopted to detect pedestrians with insignificant radial velocity. In the tracking stage, the pedestrian’s state is estimated by a Kalman filter, which uses the speed information to estimate the pedestrian’s dynamics. Based on the similarity between the predicted and detected states of pedestrians, a greedy algorithm is adopted to associate the trajectories with the detection results. The presented detection and tracking methods are tested on two data sets collected in San Francisco, California by a mobile Doppler LiDAR system. The results of the pedestrian detection demonstrate that the proposed two-step classifier can improve the detection performance, particularly for detecting pedestrians far from the sensor. For both data sets, the use of Doppler speed information improves the F1-score and the recall by 15% to 20%. The subsequent tracking from the Kalman filter can achieve 83.9–55.3% for the multiple object tracking accuracy (MOTA), where the contribution of the speed measurements is secondary and insignificant

Low complexity DSP for high speed optical access networking

A novel low-cost and energy-efficient approach for reaching 40 Gb/s signals is proposed for cost-sensitive optical access networks. Our proposed design is constituted of an innovative low-complex high-performance digital signal processing (DSP) architecture for pulse amplitude modulation (PAM-4), reuses existing commercial cost-effective 10-G components and eliminates the need of a power-hungry radio frequency (RF) component in the transmitter. Using a multi-functional 17-tap reconfigurable adaptive Volterra-based nonlinear equalizer with noise suppression, significant improvement in receiver optical power sensitivity is achieved. Results show that over 30 km of single-mode fiber (SMF) a link power budget of 33 dB is feasible at a bit-error-rate (BER) threshold of 10−3.</jats:p

Overview of high-speed TDM-PON beyond 50 Gbps per wavelength using digital signal processing [Invited Tutorial]

The recent evolution of passive optical network standards and related research activities for physical layer solutions that achieve bit rates well above 10 Gbps per wavelength (lambda) is discussed. We show that the advancement toward 50, 100, and 200 Gbps/lambda will certainly require a strong introduction of advanced digital signal processing (DSP) technologies for linear, and maybe nonlinear, equalization and for forward error correction. We start by reviewing in detail the current standardization activities in the International Telecommunication Union and the Institute of Electrical and Electronics Engineers, and then we present a comparison of the DSP approaches for traditional direct detection solutions and for future coherent detection approaches. (c) 2022 Optica Publishing Grou

Post-FEC BER Benchmarking for Bit-Interleaved Coded Modulation with Probabilistic Shaping

Accurate performance benchmarking after forward error correction (FEC) decoding is essential for system design in optical fiber communications. Generalized mutual information (GMI) has been shown to be successful at benchmarking the bit-error rate (BER) after FEC decoding (post-FEC BER) for systems with soft-decision (SD) FEC without probabilistic shaping (PS). However, GMI is not relevant to benchmark post-FEC BER for systems with SD-FEC and PS. For such systems, normalized GMI (NGMI), asymmetric information (ASI), and achievable FEC rate have been proposed instead. They are good at benchmarking post-FEC BER or to give an FEC limit in bit-interleaved coded modulation (BICM) with PS, but their relation has not been clearly explained so far. In this paper, we define generalized L-values under mismatched decoding, which are connected to the GMI and ASI. We then show that NGMI, ASI, and achievable FEC rate are theoretically equal under matched decoding but not under mismatched decoding. We also examine BER before FEC decoding (pre-FEC BER) and ASI over Gaussian and nonlinear fiber-optic channels with approximately matched decoding. ASI always shows better correlation with post-FEC BER than pre-FEC BER for BICM with PS. On the other hand, post-FEC BER can differ at a given ASI when we change the bit mapping, which describes how each bit in a codeword is assigned to a bit tributary.Comment: 14 pages, 8 figure

A Survey of Blind Modulation Classification Techniques for OFDM Signals

Blind modulation classification (MC) is an integral part of designing an adaptive or intelligent transceiver for future wireless communications. Blind MC has several applications in the adaptive and automated systems of sixth generation (6G) communications to improve spectral efficiency and power efficiency, and reduce latency. It will become a integral part of intelligent software-defined radios (SDR) for future communication. In this paper, we provide various MC techniques for orthogonal frequency division multiplexing (OFDM) signals in a systematic way. We focus on the most widely used statistical and machine learning (ML) models and emphasize their advantages and limitations. The statistical-based blind MC includes likelihood-based (LB), maximum a posteriori (MAP) and feature-based methods (FB). The ML-based automated MC includes k-nearest neighbors (KNN), support vector machine (SVM), decision trees (DTs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) based MC methods. This survey will help the reader to understand the main characteristics of each technique, their advantages and disadvantages. We have also simulated some primary methods, i.e., statistical- and ML-based algorithms, under various constraints, which allows a fair comparison among different methodologies. The overall system performance in terms bit error rate (BER) in the presence of MC is also provided. We also provide a survey of some practical experiment works carried out through National Instrument hardware over an indoor propagation environment. In the end, open problems and possible directions for blind MC research are briefly discussed