This document provides updates to IEEE Std 802.16's MIB for the MAC, PHY and asso- ciated management procedures in order to accommodate recent extensions to the standard.

IEEE Standard for Local and Metropolitan Area Networks Part 16: Air Interface for Fixed Broadband Wireless Access Systems Draft Amendment: Management Information Base Extensions

Large-scale (or massive) multiple-input multiple-out put (MIMO) is expected to be one of the key technologies in next-generation multi-user cellular systems based on the upcoming 3GPP LTE Release 12 standard, for example. In this work, we propose-to the best of our knowledge-the first VLSI design enabling high-throughput data detection in single-carrier frequency-division multiple access (SC-FDMA)-based large-scale MIMO systems. We propose a new approximate matrix inversion algorithm relying on a Neumann series expansion, which substantially reduces the complexity of linear data detection. We analyze the associated error, and we compare its performance and complexity to those of an exact linear detector. We present corresponding VLSI architectures, which perform exact and approximate soft-output detection for large-scale MIMO systems with various antenna/user configurations. Reference implementation results for a Xilinx Virtex-7 XC7VX980T FPGA show that our designs are able to achieve more than 600 Mb/s for a 128 antenna, 8 user 3GPP LTE-based large-scale MIMO system. We finally provide a performance/complexity trade-off comparison using the presented FPGA designs, which reveals that the detector circuit of choice is determined by the ratio between BS antennas and users, as well as the desired error-rate performance.

Large-Scale MIMO Detection for 3GPP LTE: Algorithms and FPGA Implementations

In this article, we introduce MATLAB-based link and system level simulation environments for UMTS Long-Term Evolution (LTE). The source codes of both simulators are available under an academic non-commercial use license, allowing researchers full access to standard-compliant simulation environments. Owing to the open source availability, the simulators enable reproducible research in wireless communications and comparison of novel algorithms. In this study, we explain how link and system level simulations are connected and show how the link level simulator serves as a reference to design the system level simulator. We compare the accuracy of the PHY modeling at system level by means of simulations performed both with bit-accurate link level simulations and PHY-model-based system level simulations. We highlight some of the currently most interesting research questions for LTE, and explain by some research examples how our simulators can be applied.

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The Vienna LTE simulators - Enabling reproducibility in wireless communications research

The Internet of Things (IoT) is transforming the whole of society. It represents the next evolution of the Internet and will significantly improve the ability to gather and analyze data, as well as the ability to control devices remotely. In this respect, the usage of connected devices is continuously growing with the expansion of the applications being offered to individuals and industries. To address IoT market needs, many low-power wide-area (LPWA) technologies have been developed, some operating on licensed frequencies (e.g., narrowband-IoT [NB-IoT] and Long-Term Evolution-M [LTE-M]), and others on unlicensed frequencies (e.g., LoRa, Sigfox, etc.). In this article, we address the Release 13 of the NB-IoT 3rd generation partnership project (3GPP) standardized LPWA technology and provide a tutorial on its physical layer (PHY) design. Specifically, we focus on the characteristics and the scheduling of downlink and uplink physical channels at the NB-IoT base station side and the user equipment (UE) side. The goal is to help readers easily understand the NB-IoT system without having to read all the 3GPP specifications or the state-of-the-art papers that generally describe the system. To this end, each presented concept is followed by examples and concrete use-cases to further aid in the reader’s comprehension. Finally, we briefly describe and highlight the new features added to the NB-IoT system in Releases 14 and 15.

https://hal.archives-ouvertes.fr/hal-02952155/document

A Tutorial on NB-IoT Physical Layer Design

This paper proposes - to the best of our knowledge - the first ASIC design for high-throughput data detection in single carrier frequency division multiple access (SC-FDMA)-based large-scale MIMO systems, such as systems building on future 3GPP LTE-Advanced standards. In order to substantially reduce the complexity of linear soft-output data detection in systems having hundreds of antennas at the base station (BS), the proposed detector builds upon a truncated Neumann series expansion to compute the necessary matrix inverse at low complexity. To achieve high throughput in the 3GPP LTE-A uplink, we develop a systolic VLSI architecture including all necessary processing blocks. We present a corresponding ASIC design that achieves 3.8 Gb/s for a 128 antenna, 8 user 3GPP LTE-A based large-scale MIMO system, while occupying 11.1 mm 2 in a TSMC 45nm CMOS technology.

/pdf/a-3-8gb-s-large-scale-mimo-detector-for-3gpp-lte-advanced-2rs8f534z1.pdf

A 3.8Gb/s large-scale MIMO detector for 3GPP LTE-Advanced

In this paper, hardware implementation aspects of the channel estimator in 3GPP LTE terminals are investigated. A channel estimation ASIC, which handles the real-time channel estimation, is presented. Compared to traditional correlator-based channel estimators, the channel estimator presented boosts the throughput at feasible silicon cost by adopting a recently proposed estimation method named Approximate Linear Minimum Mean Square Error (ALMMSE). In this paper, both the architecture and VLSI implementation of the estimator are elaborated. Implemented using a 65nm CMOS process, the channel estimator supports the full 20MHz bandwidth of 3GPP LTE and consumes only 49 kgates.

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Christian Mehlfuehrer

Papers

Implementation Aspects of Channel Estimation for 3GPP LTE Terminals