| Summary: | 博士 === 國立臺灣大學 === 電子工程學研究所 === 106 === The next generation communication systems (5G) have three directions: enhanced mobile broadband (eMBB), massive machine type communications (mMTC), and ultra-reliable and low latency communications (URLLC). Low latency service delivery is probably one of the most challenging 5G goals, which may imply costly investments. The introduction of low latency applications represents substantial technical challenges but foresee major changes in the way businesses are made. That is, the upcoming 5G wireless communication standard supporting low latency creates new indoor business demands, such as the healthcare industry, transport industry, entertainment industry, and the manufacturing industry
Along with the evolution of wireless technologies, users are expected to have indoor real-time applications. Under tight timing constraints, some applications require ultra-reliable communication, for instance mission-critical controls, while others involve high-throughput transmission, for instance augmented reality (AR). It is very challenging to fulfill the stringent timing requirements of various resource-hungry services. To achieve these goals, many possible solutions are proposed in ultra-dense millimeter-wave (mmWave) networks (UDN). Furthermore, to improve signal quality or reliability in UDN, multi-connectivity techniques emerge, where one device can be simultaneously connected to several small cells (SCs).
Recently, the hybrid beamforming design for mmWave devices, which can simultaneously transmit several data streams, has been considered attractive for high-reliable or high-throughput communications. However, under low-latency criteria, this hybrid design must require instantaneous multi-path channel state information (MP-CSI). That is, an effective multi-beam steering and estimation algorithm are desired.
In this dissertation, we concentrate on such indoor low-latency mmWave scenarios and develop fast mmWave channel estimations under limited training steps. There are two main scenarios. First, for high-throughput and low-latency required devices, we develop a novel ideal about progressive channel estimation at a single transceiver. Our algorithms make multiple coarse beams emerge within a few training steps. Hence, multiplexing gain can occur immediately. On the other side, for ultra-reliable and low-latency communications, our method aims to measure as many links as possible in a limited training time instead of all possible links at an mmWave UDN. Multi-connectivity is rapidly established.
There are three main topics in this work. First, for high-throughput devices, we propose Progressive Multi-Beam Estimation which probes multiple channel gains concurrently instead of sequentially. This algorithm provides a preliminary concurrent multi-beam steering. Based on a DFT-based (Discrete Fourier Transform) codebook, this method is also called DFT-based PMBE. The PMBE takes only 3% training steps of exhaustive search to achieve 85% spectral efficiency of the exhaustive case.
In the second part of this dissertation, we further enhance our multi-beam probing technique by combining a proposed FFT-based (Fast Fourier Transform) codebook with our PMBE. Meanwhile, an FFT-based hybrid beamforming design is proposed with a single-connected architecture, a hardware-efficient, and energy-efficient architecture. This FFT-based codebook can be considered as a DFT codebook (Discrete Fourier Transform) with built-in bit-reversal scrambling mechanism, so as to improve the multiplexing gain.
In the third part of this dissertation, we focus on the ultra-reliable and low-latency devices which achieve high reliability by some multi-connectivity strategies. For low-latency requirements, an efficient multi-connectivity estimation under strict-limited training steps is indeed. We propose down_uplink multi-connectivity measurements using the FFT-based codebook estimating multiple links from different SCs. Simulation results show that our method can take less training steps to access more SCs and it also acquires high multi-link quality.
In summary, for a high-throughput device or for a high-reliable device, the proposed algorithms are quite efficient to address their low-latency estimation problems.
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