This paper presents ATSC 3.0 physical (PHY) layer modulation and coding performance through computer simulations, laboratory tests, and field trials. Analysis results show that the measured results in laboratory and f...
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ISBN:
(纸本)9781538647295
This paper presents ATSC 3.0 physical (PHY) layer modulation and coding performance through computer simulations, laboratory tests, and field trials. Analysis results show that the measured results in laboratory and field are generally well aligned with computer simulation results. The ATSC 3.0 PHY layer performance covers ultra-robust reception (negative SNR operation with QPSK and 2/15 LDPC code) to very high-throughput (over 50 Mbps with 4096-NUC with 13/15 LDPC code) in real field environment.
A repetition coding can provide coding and diversity gains, however, the transmission rate is severely decreased. Therefore, the repetition diversity scheme has been recognized as an inefficient coding technique. In t...
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ISBN:
(纸本)9781479958665
A repetition coding can provide coding and diversity gains, however, the transmission rate is severely decreased. Therefore, the repetition diversity scheme has been recognized as an inefficient coding technique. In the paper, we present some performance results of LDPC codes with a repetition coding over AWGN and Rayleigh channels for given transmission rates. Simulation results show that the repetition scheme with QPSK modulation always provides a good coding gain over a Rayleigh fading channel due to diversity effect, as compared with the case of BPSK modulation without repetition. Furthermore, we observe the performance of LDPC coded modulation with non-uniform constellation over AWGN and Rayleigh channels. Finally, we present that the best modulation and coding strategy for given channel condition can be determined by adjusting code-rate, modulation and repetition schemes.
Multi-connectivity enables a 5G cellular system to meet the challenging reliability requirements of downlink ultra-reliable low-latency communication (URLLC) data traffic. In it, multiple base stations (BSs) transmit ...
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Multi-connectivity enables a 5G cellular system to meet the challenging reliability requirements of downlink ultra-reliable low-latency communication (URLLC) data traffic. In it, multiple base stations (BSs) transmit to the URLLC user by pre-empting time-frequency resources assigned to enhanced mobile broadband (eMBB) users. We derive insightful expressions for achievability, which is the probability that the URLLC user's block error rate (BLER) requirement is met by multi-connectivity. We do so for both joint transmission (JT) and orthogonal transmission (OT) modes of URLLC for the general case in which the transmissions occur over frequency-selective channels. We then propose a low-complexity algorithm to jointly select the set of cooperating BSs and their modulation and coding schemes (MCSs) to minimize the eMBB throughput loss. For time-varying channels with feedback delays, we present an alternate stochastic reliability requirement for URLLC traffic. The MCS selected on the basis of this requirement has a markedly higher probability of meeting the BLER target over the grid of URLLC user locations. Our results highlight the different trade-offs between URLLC achievability, eMBB throughput loss, and channel state information feedback overhead of OT and JT. They bring out the significant impact of feedback delays even at moderate Doppler spreads.
This article proposes using in-phase and quadrature frequency-shift keying (IQFSK) modulation for low-power optical wireless communications (OWC). IQFSK independently leverages both cosine and sine basis functions to ...
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This article proposes using in-phase and quadrature frequency-shift keying (IQFSK) modulation for low-power optical wireless communications (OWC). IQFSK independently leverages both cosine and sine basis functions to enhance the system's spectral efficiency (SE). It uses only the odd harmonic frequencies for these basis functions, allowing the clipping of negative amplitude excursions without losing information, making the waveform compatible with OWC The work presents optimal maximum likelihood and low-complexity suboptimal detection mechanisms for IQFSK. The proposed scheme is analyzed analytically and with numerical simulations. The simulation and analytical results indicate that the proposed scheme is more energy-efficient, can attain a better energy and SE trade-off by exploiting the frame structure of the waveform, and has a lower minimum squared Euclidean distance relative to other state-of-the-art FSK-based counterparts, thus establishing it as one of the most efficient FSK approaches for low-power OWCs.
With the rapid development of intelligent devices, the fifth-generation (5G) mobile wireless networks are envisioned to support massive connections and higher capacity. To confront challenges on link inefficiency in t...
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ISBN:
(纸本)9781665426718
With the rapid development of intelligent devices, the fifth-generation (5G) mobile wireless networks are envisioned to support massive connections and higher capacity. To confront challenges on link inefficiency in traditional mobile wireless networks, the link adaptation technology is crucial for system capacity improvements and requires coordination with resource allocation strategy. In this paper, we consider a joint adaptive modulation and coding (AMC) and resource allocation (RA) in a wireless network, where multiple users share limited subcarriers and adaptively change modulation levels and transmit power with the target to maximize the long-term system throughput. Instead of using optimization theory-based methods with higher complexity, we propose an intelligent double deep Q-network (DDQN)-based AMC and RA algorithm, which regards users as agents that learn cooperatively from their past experiences and implement their policies distributively. Furthermore, to guarantee fairness among users, we re-design the multi-agent reinforcement learning (MARL) reward function to incorporate the attained proportional fairness of each user at the current cycle into our objective. Simulation results demonstrate that users successfully learn to collaborate in a distributed manner, which leads to improved throughput both of the single link level and the whole system level.
We propose a global bandits (GB) model for rate allocation in cognitive radio networks. Specifically, we focus on an interweave spectrum scenario, where a secondary user (SU) opportunistically access the licensed wire...
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ISBN:
(纸本)9781728172064
We propose a global bandits (GB) model for rate allocation in cognitive radio networks. Specifically, we focus on an interweave spectrum scenario, where a secondary user (SU) opportunistically access the licensed wireless channel of primary users (PU), when PU is not accessing the channel. We propose a learning algorithm that learns the modulation and coding scheme (MCS) with the highest expected reward online over a dynamic wireless channel for an SU, where the reward is taken as the throughput (TP) provided by the system. The expected reward in GB is parameterized by a global parameter, and we show that for most of the existing channel models average signal-to-noise ratio (SNR) serves as the global parameter. We further show that the GB converges much faster to the optimal solution, when compared to the previous state-of-the-art algorithms. We show numerically that the GB yields superior performance, and the regret with respect to an oracle which knows the channel distribution is sub-linear in time.
This paper presents the advanced television systems committee (ATSC) 3.0 physical layer system performances with different modulation and channel coding combinations. Numerous computer simulations, laboratory tests, a...
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This paper presents the advanced television systems committee (ATSC) 3.0 physical layer system performances with different modulation and channel coding combinations. Numerous computer simulations, laboratory tests, and field trials are conducted under additive white Gaussian noise, RC20, and RL20 channels. Analysis of the results shows that the measured values in laboratory and field are less than 1 dB away from computer simulation results. This confirms that the ATSC 3.0 physical layer is capable of providing services ranging from ultra-robust reception (negative SNR operation with QPSK and 2/15 low density parity check (LDPC) code) to very high-throughput (over 50 Mb/s with 4096-non-uniform constellation and 13/15 LDPC code) in real field environments.
A comprehensive review to the theory, application and research of machine learning for future wireless communications In one single volume, Machine Learning for Future Wireless Communications provides a comprehensive ...
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ISBN:
(数字)9781119562306
ISBN:
(纸本)9781119562252
A comprehensive review to the theory, application and research of machine learning for future wireless communications In one single volume, Machine Learning for Future Wireless Communications provides a comprehensive and highly accessible treatment to the theory, applications and current research developments to the technology aspects related to machine learning for wireless communications and networks. The technology development of machine learning for wireless communications has grown explosively and is one of the biggest trends in related academic, research and industry communities. Deep neural networks-based machine learning technology is a promising tool to attack the big challenge in wireless communications and networks imposed by the increasing demands in terms of capacity, coverage, latency, efficiency flexibility, compatibility, quality of experience and silicon convergence. The author – a noted expert on the topic – covers a wide range of topics including system architecture and optimization, physical-layer and cross-layer processing, air interface and protocol design, beamforming and antenna configuration, network coding and slicing, cell acquisition and handover, scheduling and rate adaption, radio access control, smart proactive caching and adaptive resource allocations. Uniquely organized into three categories: Spectrum Intelligence, Transmission Intelligence and Network Intelligence, this important resource: Offers a comprehensive review of the theory, applications and current developments of machine learning for wireless communications and networks Covers a range of topics from architecture and optimization to adaptive resource allocations Reviews state-of-the-art machine learning based solutions for network coverage Includes an overview of the applications of machine learning algorithms in future wireless networks Explores flexible backhaul and front-haul, cross-layer optimization and coding, full-duplex radio, digital front-end (DFE) and radio-freq
Underwater wireless information transfer is of great interest to the military, industry, and the scientific community, as it plays an important role in tactical surveillance, pollution monitoring, oil control and main...
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Underwater wireless information transfer is of great interest to the military, industry, and the scientific community, as it plays an important role in tactical surveillance, pollution monitoring, oil control and maintenance, offshore explorations, climate change monitoring, and oceanography research. In order to facilitate all these activities, there is an increase in the number of unmanned vehicles or devices deployed underwater, which require high bandwidth and high capacity for information transfer underwater. Although tremendous progress has been made in the field of acoustic communication underwater, however, it is limited by bandwidth. All this has led to the proliferation of underwater optical wireless communication (UOWC), as it provides higher data rates than the traditional acoustic communication systems with significantly lower power consumption and simpler computational complexities for short-range wireless links. UOWC has many potential applications ranging from deep oceans to coastal waters. However, the biggest challenge for underwater wireless communication originates from the fundamental characteristics of ocean or sea water;addressing these challenges requires a thorough understanding of complex physio-chemical biological systems. In this paper, the main focus is to understand the feasibility and the reliability of high data rate underwater optical links due to various propagation phenomena that impact the performance of the system. This paper provides an exhaustive overview of recent advances in UOWC. Channel characterization, modulation schemes, coding techniques, and various sources of noise which are specific to UOWC are discussed. This paper not only provides exhaustive research in underwater optical communication but also aims to provide the development of new ideas that would help in the growth of future underwater communication. A hybrid approach to an acousto-optic communication system is presented that complements the existing acoustic s
The accessibility of good smartphones in 4G is encouraging mobile users to use video services. This huge increase in the usage of video communication over wireless networks poses many challenges according to fluctuati...
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ISBN:
(纸本)9788132225171;9788132225164
The accessibility of good smartphones in 4G is encouraging mobile users to use video services. This huge increase in the usage of video communication over wireless networks poses many challenges according to fluctuations of wireless channel conditions along with user mobility. The challenge in providing video multicasting over wireless networks would most likely be the channel condition of each user in the same multicast group which is probably not identical due to location of the user and/or congestion of the network. In this paper, an adapted multicasting scheme has been proposed, which gracefully adapts the video quality to heterogeneous receivers and varying network conditions. Results obtained from simulation indicate that an enhancement of video quality under numerous channel conditions was through graceful degradation of these channels in terms of average throughput and packet loss ratio.
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