Anti-interference Algorithm of Broadband Wireless Communication Based on Embedded Single Chip Microcomputer

Modified Packet Combining (MPC) scheme is an error correction scheme, which can correct double or, higher bit errors. In some earlier work, a scheme known as Packet Reversed Packet Combining (PRPC) scheme that will correct error if occurs at same bit location of erroneous copies, was studied. Both PRPC and MPC scheme are believed to offer higher throughput and better error correction capability at high bit error rate (BER) and large packet size only. Exact analysis was performed to substantiate this claim of higher throughput and better error correction capability in high as well as in low bit error rate (BER) for large and medium packet size. To combat high bit error rate some researches proposed to use Error Correction Code (ECC) in place of Error Detection Code (EDC) in ARQ scheme. But no conclusive result is found to justify the idea in terms of throughput. The current investigation is an attempt to explore the basic gap. In this paper, we investigate the exact analysis of both PRPC and MPC in a Modified way over Conventional PRPC, and report the findings thereof. We propose a combined protocol of Modified PRPC and MPC, and find that it will offer higher throughput and better error correction capability at high and low BER with medium and large packet size as we have used MPC (Modified Packet Combining) scheme with PRPC (Packet Reverse Packet Combining) scheme in a Modified way by combining BEC (Backward Error Correction) with FEC (Forward Error Correction) Codes for Mobile Communication and Networks.

Near-threshold voltage (NTV) operation is expected to enable up to 10× energy-efficiency for future processors. However, reliable operation below a minimum voltage (Vccmin) cannot be guaranteed. Specifically, SRAM bit-cell error rates are expected to rise steeply since their margins can easily be violated at near-threshold voltages. Multicore processors rely on fast private L1 caches to exploit data locality and achieve high performance. In the presence of high bit-cell error rates, an L1 cache can either sacrifice capacity or incur additional latency to correct the errors. We observe that L1 cache sensitivity to hit latency offers a design tradeoff between capacity and latency. When error rate is high at extreme Vccmin, it is worthwhile incurring additional latency to recover and utilize the additional L1 cache capacity. However, at low error rates, the additional constant latency to recover cache capacity degrades performance. With this tradeoff in mind, we propose a novel private L1 cache architecture that dynamically learns and adapts by either recovering cache capacity at the cost of additional latency overhead, or operate at lower capacity while utilizing the benefits of optimal hit latency. Using simulations of a 64-core multicore, we demonstrate that our adaptive L1 cache architecture performs better than both individual schemes at low and high error rates (i.e., various NTV conditions).

Currently there is no control for real-time traffic sources in IP networks. This is a serious problem because real-time traffic can not only congest the network but can also cause unfairness and starvation of TCP traffic. A new rate control scheme, RCS, is introduced for real-time traffic in networks with high bandwidth-delay products and high bit error rates. RCS is based on the concept of using dummy packets to probe the availability of network resources. Dummy packets are treated as low priority packets and consequently they do not affect the throughput of actual data traffic. Therefore, RCS requires all the routers in the connection path to support some priority policy. Simulation experiments show that in environments with high bandwidth-delay products and high bit error rates, RCS achieves good throughput performance without penalizing TCP connections.

The way through which change of weather parameters is measured can be called as weather forecasting. Weather forecast plays important role in predicting natural calamities, agricultural sectors, some industrial sectors, etc. Heat index is a vital part of weather which depends on some weather parameters. Human body temperature, evaporation, etc. depends on heat index. Previously, several researchers worked on this issue to determine whether it rains or not for two to three days. Some of them worked just to determine the effect of change of heat index in different regions. A number of works were based on machine learning algorithms and most of them had either low accuracy or high error rate. But in this paper, we proposed a combined deep learning model. It can predict five most important weather parameters up to 30 days with very low error rate by using single cell long short term memory (LSTM). Along with this, the output from LSTM was further used to predict heat index using artificial neural network (ANN) which also gave a very high accuracy. The dataset provided to the model was pre-processed properly by using Gaussian filter, Median filter and scaling. It increased the sensitivity and performance of the model. We got the mean absolute percentage error rate (MAPE) ranging from 0.02%-8.53% with LSTM model and 94.68% of accuracy from ANN model. Further judging parameters of ANN are precision (94.57%), recall (94.57%), f1 score (94.57%), loss (12.75%). The other error rates of LSTM model are MSE (1%-16%), RMSE (10.72%-39.44%), R2 (99%-100%), MAE (8.17%-34.59%).

While Transmission Control Protocol (TCP) works well with a low bit error rate (BER), the performance of TCP degrades significantly if the BER rises above a certain level. A study of the performance of TCP with high BER is required for the efficient design and deployment of such systems. In this paper, we address the problem of TCP performance in high BERs and analyze the issues by investigating the effect of BERs on system performance. We consider TCP Reno in our study to explore the system performance using extensive analysis of simulation and modeling. In the analysis, we consider the amount of datagram sent and retransmitted, mean throughput, link-layer overhead, TCP window size, FTP download response time, packet dropping and retransmission, and the TCP congestion avoidance mechanism. We validate simulation results by setting up a virtualized testbed using Linux hosts and a Linux router. The results obtained show that TCP throughput degrades significantly and eventually collapses at the packet drop probability of 10% (BER = 10−5). The FTP download response time is about 32 times longer than that of a perfect channel (no packet dropping). We found that TCP Reno cannot handle such a high BER to operate in wireless environments effectively. Finally, we provide recommendations for network researchers and engineers confronted with the challenge of operating TCP over noisy channels.

In this study, we aim to further advance solutions to critical challenges in physical layer secure key generation and distribution (PLSKGD) for optical fiber communication, particularly the limitations of traditional information reconciliation (IR) protocols in mitigating initial key inconsistencies caused by noise and interference. We introduce two innovative approaches: a check node correlation coefficient-based early termination (CNCC-ET) scheme and an elastic reconfigurable (ER) scheme to enhance error correction performance and accelerate IR. The CNCC-ET scheme dynamically monitors the correlation coefficient of messages between check and variable nodes, enabling early termination of iterations when decoding is likely to fail, thus significantly reducing decoding complexity. In high bit error rate (BER) regions, this scheme achieves up to a 51.8% reduction in average iteration counts while maintaining low frame error rates (FER). Concurrently, our ER scheme adapts to varying BER conditions by dynamically adjusting the ratio of information to check bits, achieving a remarkable 90.26% FER reduction in high-BER scenarios. Hardware implementation on a Xilinx Virtex-7 FPGA validates the feasibility of these methods, demonstrating a 47.2% reduction in IR time overhead and significantly improved error correction capability. This study advances the development of more secure and efficient optical fiber communication systems, with potential applications extending to other physical layer security contexts.

Satellite edge computing (SEC) extends the capabilities of task offloading from the ground to near-Earth space by leveraging the wide coverage of satellites. However, the high-speed movement and long-range communication of satellites lead to Doppler shifts and signal loss, which can result in a high bit error rate (BER) and degrade communication link quality. As a result of the high BER, error correction is required, inevitably incurring additional delay during task offloading. Therefore, in this paper, we focus on the problem of <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">E</u>rror <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</u>orrection aware <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</u>ependency <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</u>ask <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O</u>ffloading (EC-DTO) in satellite environments. By jointly considering task dependencies and BER-induced error correction delays, we formulate the EC-DTO problem as a constrained optimization problem with the objective of minimizing the makespan of users' tasks. To solve this problem, we propose APOS, which is an event-driven offloading framework based on task-<underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">A</u>daptive <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P</u>rioritization and <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O</u>ptimistic-finish-time-based node <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</u>election. Specifically, APOS adopts an online offloading framework that triggers scheduling upon task arrivals and completions with task dependency awareness. It iteratively updates task readiness and performs offloading decisions to reduce the overall makespan in the SEC environment. Simulation results show that APOS outperforms the representative methods, lowering the average makespan by 20.7% and the deadline violation ratio by 84.5% on average across all cases.

Crosstalk noise and insertion loss are important factors influencing the performance of optical networks-on-chip (ONoCs), especially in wavelength division multiplexing (WDM) based ONoCs. These factors lead to a high bit error rate (BER) of the communication system, thereby reducing the reliability of the communication in ONoCs. All-optical coding on chip is one of the important methods to solve this problem, so a high-reliability communication scheme that utilizes all-optical coding in ONoCs is implemented in this paper. The scheme mainly exploits the characteristics of linear block codes to implement the function of checking and correcting bit errors. As a core part of implementing this scheme, a micro-resonators (MRs)-based all-optical linear block codes encoder is designed to encode the information sequence before transmission. When the encoded data arrive at the receiving end, an error detection and correction (EDC) module can detect and correct the bit errors according to certain rules. In addition, for bit errors that exceed the error correction range, a retransmission mechanism (RT) is activated in communication system to denoise and retransmit the uncorrectable data group. In order to verify the validity of the proposed approach, a case study is conducted in mesh-based ONoCs with WDM. The simulation results manifest that the information transmission quality can be effectively optimized by applying the reliable communication scheme to the ONoCs. This approach reduces the BER and improves the optical signal-to-noise ratio (OSNR) of optical signals. Under the same condition that the scale of network reaches the maximum, the OSNR is increased by 9.8301 dB and the BER is reduced by 12.4499 dB compared with the traditional mesh-based ONoCs. Therefore, this work has a great impact on improving the reliability of communication systems.

The purpose of genome sequencing is to determine the DNA sequence of a given organism. Current sequencing technologies can be classified by the type of output data. Whereas Nanopore technology generates long reads with high error rates, short read technologies - such as Illumina sequencing - generate shorter reads but with low error rate. Since de novo genome assembly of sequencing reads is defined as a NP-hard problem, it remains as one of the major challenges for defining reference genomes of different species. This paper aims to improve the quality of reads obtained through Oxford Nanopore Technologies (ONT). We developed an algorithm to associate the reads obtained from Illumina with the ones obtained with Nanopore. Low accuracy ONT reads were corrected with the high quality Illumina reads to achieve an improved sequencing data. The inclusion of this algorithm as a preprocessing step resulted in improved coverage, contig length, and mismatch rate when performing de novo genome assembly of a bacterial genome with well known tools.

The harsh environment in the water has imposed challenges for underwater sensor networks (USNs), which collect the sensed data from the underwater sensors to the sink on land. The time-varying underwater acoustic channel has low band-width and high bit error rate, which leads to low data collection efficiency. Furthermore, the heterogeneous model of USNs that uses acoustic communications under the water and wireless communication above the water makes it difficult in efficient routing and forwarding for data collection. To this end, we propose a novel on-surface wireless-assisted opportunistic routing (SurOpp) for USNs. SurOpp deploys multiple buoy nodes on surface and includes all of them in the forwarding candidates to form a receive diversity. The opportunities of reception and forwarding in buoy nodes are exploited to improve the end-to-end transmissions. SurOpp also adopts rateless codes in the source to achieve opportunistic reception in the sink. The cooperation of both opportunistic reception in the buoys and the sink further decreases the messages of control overhead. The wireless interface in the buoy undertakes all the message exchanges in forwarding coordination to compensate the bandwidth limit of the acoustic channel. Simulations in NS3 show that SurOpp outperforms the traditional routing and existing opportunistic routing in terms of packet delivery ratio, end-to-end delay and energy consumption.

Wireless communication is the fastest growing segment of the communication industry. New services are being added and data is provided at higher bit rates to the end users. With these advancements any communication system has to critically consider data integrity. This requires, maintaining a lower bit error rate. Present work focuses on the Broadcast Wireless Access standard named WiMax (Worldwide Interoperability for Microwave Access). Possible options for maintaining a lower bit error rate in WiMax System are worked out. In particular a Novel Approach which uses a concatenation of RS (Reed-Solomon) and Turbo Codes for the Codec design in The WiMax Communication System is presented. The paper also discusses use of OQPSK Modulation Technique in place of the conventional QPSK system, for performance improvement. The comparative simulation results of existing WiMax System and the system using the novel approach are also provided. These results are used to draw useful conclusions for reducing the bit error rate in the WiMax System.

With the increasing bit density and adoption of 3D NAND, flash memory suffers from increased errors. To address the issue, flash devices adopt error correction codes (ECC) with strong error correction capability, like low-density parity-check (LDPC) code, to correct errors. The drawback of LDPC is that, to correct data with a high raw bit error rate (RBER), read latency will be amplified. This work proposes to address this issue with the assistance of approximate data. First, studies have been conducted and show there are ample amount of approximate data available in flash storage. Second, a novel data organization is proposed to fortify the reliability of regular data by leaving approximate data unprotected. Finally, a new data allocation strategy and modified garbage collection scheme are presented to complete the design. The experimental results show that the proposed approach can improve read performance by 30% on average comparing to current techniques.

이 논문에서는 계층변조를 적용하는 AT-DMB (advanced terrestrial digital multimedia broadcasting) 시스템에 적용할 수 있는 블라인드등화 기법을 제시하고 그 성능을 살펴본다. AT-DMB 시스템은 기존 T-DMB의 DQPSK (differential quadrature phase-shift keying) 신호와 역방향 호환성을 보장하고 더 높은 데이터 전송률을 지원하기 위해 16-QAM (quadrature amplitude modulation) 계층변조 방식을 적용한다. 이 결과 SNR (signal to noise ratio)에 따라 기존 T-DMB 심볼과 추가된 심볼은 서로 다른 판정오율 (decision error rate)을 가진다. 따라서 판정한 신호로부터 채널을 추정할 때 판정오율이 낮은 선순위 심볼과 판정오율이 높은 후순위 심볼의 신뢰도에 따라 다른 가중치를 줌으로써 판정치의 전체적인 신뢰도를 향상시킬 수 있다. 이 논문에서는 계층변조에 따른 비트 오율(bit error rate) 성능의 악화정도를 분석하고, 모의실험을 통해 판정신호의 신뢰도에 따라 가중치를 주는 제안방식이 가중치를 주지 않은 경우에 비해 비트 오율 성능이 향상됨을 확인하였다. In this paper, we propose a blind equalization method for advanced terrestrial digital multimedia broadcasting (AT-DMB) systems which use hierarchical modulation. The AT-DMB system adopts hierarchical 16-ary quadrature amplitude modulation (16-QAM) to ensure backward-compatibly with the differential quadrature phase shift keying (DQPSK) signal of the legacy terrestrial digital multimedia broadcasting (T-DMB) systems and to support higher transmission rate. Due to the hierarchical modulation, the conventional T-DMB signal and the additional signal have different error rate at same signal to noise ratio (SNR). By weighting the decided symbols differently according to the reliability of the symbols, i.e., high priority symbol with low error rate and low priority symbol with high error rate, we can improve the channel estimation accuracy. In this paper, we analyze SNR loss by hierarchical modulation and confirm it through simulations. Moreover, through simulations, we verify that the proposed weighting method improve BER compared to the no-weighting method.

In coherent optical communication, the Doppler frequency offset reaches several GHz, which seriously affects the performance of the coherent demodulation system and increases the bit error rate. In this paper, a novel carrier acquisition and tracking algorithm for spatial coherent optical communication is proposed. The algorithm adopts the dual-locked frequency loop that the CPAFC tracking algorithm is effectively combined with the ODAFC tracking algorithm. The CPAFC tracking algorithm can be used for frequency offset gradually change capture and tracking, and the ODAFC tracking algorithm can capture large frequency offset, and according to the locked state control the working state of the two FLL loops. In the condition of stable locked, use only the CPAFC tracking algorithm to capture the gradually changing frequency offset; in the other condition, use two FLL loops together. The experimental results show that the 5Gbps BPSK laser communication performance loss is less than 1.5 dB when the Doppler frequency offset is 2.5 GHz, and the carrier frequency offset change rate is 20 MHz/s.

Tag signal detection is one of the key tasks in ambient backscatter communication (AmBC) systems. However, obtaining perfect channel state information (CSI) is challenging and costly, which makes AmBC systems suffer from a high bit error rate (BER). To eliminate the requirement of channel estimation and to improve the system performance, in this paper, we adopt a deep transfer learning (DTL) approach to implicitly extract the features of channel and directly recover tag symbols. To this end, we develop a DTL detection framework which consists of offline learning, transfer learning, and online detection. Specifically, a DTL-based likelihood ratio test (DTL-LRT) is derived based on the minimum error probability (MEP) criterion. As a realization of the developed framework, we then apply convolutional neural networks (CNN) to intelligently explore the features of the sample covariance matrix, which facilitates the design of a CNN-based algorithm for tag signal detection. Exploiting the powerful capability of CNN in extracting features of data in the matrix formation, the proposed method is able to further improve the system performance. In addition, an asymptotic explicit expression is also derived to characterize the properties of the proposed CNN-based method when the number of samples is sufficiently large. Finally, extensive simulation results demonstrate that the BER performance of the proposed method is comparable to that of the optimal detection method with perfect CSI.