Though belief propagation bit-flip(BPBF)decoding improves the error correction performance of polar codes,it uses the exhaustive flips method to achieve the error correction performance of CA-SCL decoding,thus resulti...
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Though belief propagation bit-flip(BPBF)decoding improves the error correction performance of polar codes,it uses the exhaustive flips method to achieve the error correction performance of CA-SCL decoding,thus resulting in high decoding complexity and *** alleviate this issue,we incorporate the LDPC-CRC-Polar coding scheme with BPBF and propose an improved belief propagation decoder for LDPC-CRC-Polar codes with bit-freezing(LDPCCRC-Polar codes BPBFz).The proposed LDPCCRC-Polar codes BPBFz employs the LDPC code to ensure the reliability of the flipping set,i.e.,critical set(CS),and dynamically update *** modified CS is further utilized for the identification of error-prone *** proposed LDPC-CRC-Polar codes BPBFz obtains remarkable error correction performance and is comparable to that of the CA-SCL(L=16)decoder under medium-to-high signal-to-noise ratio(SNR)*** gains up to 1.2dB and 0.9dB at a fixed BLER=10-4compared with BP and BPBF(CS-1),*** addition,the proposed LDPC-CRC-Polar codes BPBFz has lower decoding latency compared with CA-SCL and BPBF,i.e.,it is 15 times faster than CA-SCL(L=16)at high SNR regions.
Unmanned aerial vehicles(UAVs) with limited energy resources, severe path loss, and shadowing to the ground base stations are vulnerable to smart jammers that aim to degrade the UAV communication performance and exhau...
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Unmanned aerial vehicles(UAVs) with limited energy resources, severe path loss, and shadowing to the ground base stations are vulnerable to smart jammers that aim to degrade the UAV communication performance and exhaust the UAV energy. The UAV anti-jamming communication performance, such as the outage probability, degrades if the robot relay is not aware of the jamming policies and the UAV network topology. In this paper, we propose a robot relay scheme for UAVs against smart jamming, which combines reinforcement learning with a function approximation approach named tile coding, to jointly optimize the robot moving distance and relay power with the unknown jamming channel states and locations. The robot mobility and relay policy are chosen based on the received jamming power, the robot received signal quality,location and energy consumption, and the bit error rate of the UAV messages. We also present a deep reinforcement learning version for the robot with sufficient computing resources. It uses three deep neural networks to choose the robot mobility and relay policy with reduced sample complexity, so as to avoid exploring dangerous policies that lead to the high outage probability of the UAV messages. The network architecture of the three networks is designed with fully connected layers instead of convolutional layers to reduce the computational complexity, which is analyzed by theoretical analyses. We provide the performance bound of the proposed schemes in terms of the bit error rate, robot energy consumption and utility based on a game-theoretic study. Simulation results show that the performance of our proposed relay schemes,including the bit error rate, the outage probability, and the robot energy consumption outperforms the existing schemes.
Incomplete multi-view clustering has gained considerable attention in recent years due to the prevalence of incomplete multi-view data in real-world applications. However, existing methods often struggle to effectivel...
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This paper addresses the limitations of the Contrastive Language-Image Pre-training (CLIP) model's image encoder and proposes a segmentation model WSSS-ECFE with enhanced CLIP feature extraction, aiming to improve...
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Real-world regular expressions (regexes for short) have a wide range of applications in software. However, the support for regexes in test generation is insufficient. For example, existing works lack support for some ...
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The recently synthesized SrH22, with a rich amount of H2 units, is predicted with low superconductivity, since two hydrogen (H) atoms in H2 units are inclined to stay together by forming a well-known sigma bond, where...
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The recently synthesized SrH22, with a rich amount of H2 units, is predicted with low superconductivity, since two hydrogen (H) atoms in H2 units are inclined to stay together by forming a well-known sigma bond, where H electrons tend to occupy the low-lying energy level far below the Fermi energy, resulting in a less H populated Fermi surface. Of particular interest, for SrH22 or other similar H2-rich hydrides, is to optimize the H electron density of states in the search for high superconductivity. Here, via the strategy of bringing an additional metal element into the binary hydride, in combination with our developed global structure-searching method, we predict a ternary hydride of YSrH22. Compared with the parent hydride of SrH22, the H electron density of states at the Fermi level of YSrH22 is significantly enhanced, due to the favorable charge transfer from metal elements, such as Y, to the antibonding state of the sigma bond of H2, where such a bond is broken and H electrons come back to the Fermi surface. Our in-depth analysis indicates that this hydride could be viewed as a substitutional alloy superhydride of (Y,Sr)H11 with an estimated superconducting critical temperature Tc of 240 K at 175 GPa, which is much higher than that of SrH22 (Tc=21K) and LaH11 (Tc=13K) both at 200 GPa. Our current findings not only offer a platform to tune the superconductivity of binary superhydrides SrH22 and LaH11, via the strategy of metal element doping, but also provide a roadmap in the search for high superconductivity, even toward room-temperature superconductivity, in the family of ternary alloy superhydrides.
Load forecasting is essential for the efficient operation and planning of power systems. Accurate load prediction enables utility companies to ensure reliable electricity supply, optimize generation and distribution r...
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Offline Reinforcement Learning (RL) is an important research domain for real-world applications because it can avert expensive and dangerous online exploration. Offline RL is prone to extrapolation errors caused by th...
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Deploying the Internet of Things (IoT) in the transfer of enormous medical data often promotes challenges with the security, confidentiality, and privacy of the user’s sensitive data. In addition, the access control ...
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With the scaling up of high-performance computing systems in recent years,their reliability has been descending ***,system resilience has been regarded as one of the critical challenges for large-scale HPC *** techniq...
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With the scaling up of high-performance computing systems in recent years,their reliability has been descending ***,system resilience has been regarded as one of the critical challenges for large-scale HPC *** techniques and systems have been proposed to ensure the correct execution and completion of parallel *** paper provides a comprehensive survey of existing software resilience ***,a classification of software resilience approaches is presented;then we introduce major approaches and techniques,including checkpointing,replication,soft error resilience,algorithmbased fault tolerance,fault detection and *** addition,challenges exposed by system-scale and heterogeneous architecture are also discussed.
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