2,842 research outputs found
Adaptive Network Coding Schemes for Satellite Communications
In this paper, we propose two novel physical layer aware adaptive network
coding and coded modulation schemes for time variant channels. The proposed
schemes have been applied to different satellite communications scenarios with
different Round Trip Times (RTT). Compared to adaptive network coding, and
classical non-adaptive network coding schemes for time variant channels, as
benchmarks, the proposed schemes demonstrate that adaptation of packet
transmission based on the channel variation and corresponding erasures allows
for significant gains in terms of throughput, delay and energy efficiency. We
shed light on the trade-off between energy efficiency and delay-throughput
gains, demonstrating that conservative adaptive approaches that favors less
transmission under high erasures, might cause higher delay and less throughput
gains in comparison to non-conservative approaches that favor more transmission
to account for high erasures.Comment: IEEE Advanced Satellite Multimedia Systems Conference and the 14th
Signal Processing for Space Communications Workshop (ASMS/SPSC), 201
Wireless industrial monitoring and control networks: the journey so far and the road ahead
While traditional wired communication technologies have played a crucial role in industrial monitoring and control networks over the past few decades, they are increasingly proving to be inadequate to meet the highly dynamic and stringent demands of today’s industrial applications, primarily due to the very rigid nature of wired infrastructures. Wireless technology, however, through its increased pervasiveness, has the potential to revolutionize the industry, not only by mitigating the problems faced by wired solutions, but also by introducing a completely new class of applications. While present day wireless technologies made some preliminary inroads in the monitoring domain, they still have severe limitations especially when real-time, reliable distributed control operations are concerned. This article provides the reader with an overview of existing wireless technologies commonly used in the monitoring and control industry. It highlights the pros and cons of each technology and assesses the degree to which each technology is able to meet the stringent demands of industrial monitoring and control networks. Additionally, it summarizes mechanisms proposed by academia, especially serving critical applications by addressing the real-time and reliability requirements of industrial process automation. The article also describes certain key research problems from the physical layer communication for sensor networks and the wireless networking perspective that have yet to be addressed to allow the successful use of wireless technologies in industrial monitoring and control networks
Improved Nonlinear Transform Source-Channel Coding to Catalyze Semantic Communications
Recent deep learning methods have led to increased interest in solving
high-efficiency end-to-end transmission problems. These methods, we call
nonlinear transform source-channel coding (NTSCC), extract the semantic latent
features of source signal, and learn entropy model to guide the joint
source-channel coding with variable rate to transmit latent features over
wireless channels. In this paper, we propose a comprehensive framework for
improving NTSCC, thereby higher system coding gain, better model versatility,
and more flexible adaptation strategy aligned with semantic guidance are all
achieved. This new sophisticated NTSCC model is now ready to support large-size
data interaction in emerging XR, which catalyzes the application of semantic
communications. Specifically, we propose three useful improvement approaches.
First, we introduce a contextual entropy model to better capture the spatial
correlations among the semantic latent features, thereby more accurate rate
allocation and contextual joint source-channel coding are developed accordingly
to enable higher coding gain. On that basis, we further propose response
network architectures to formulate versatile NTSCC, i.e., once-trained model
supports various rates and channel states that benefits the practical
deployment. Following this, we propose an online latent feature editing method
to enable more flexible coding rate control aligned with some specific semantic
guidance. By comprehensively applying the above three improvement methods for
NTSCC, a deployment-friendly semantic coded transmission system stands out
finally. Our improved NTSCC system has been experimentally verified to achieve
considerable bandwidth saving versus the state-of-the-art engineered VTM + 5G
LDPC coded transmission system with lower processing latency
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