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Journal articles on the topic 'Adaptive Frequency Hopping (AFH)'

Author: Grafiati

Published: 4 June 2021

Last updated: 11 February 2022

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1

Lee, Janggoon, Chanhee Park, and Heejun Roh. "Revisiting Adaptive Frequency Hopping Map Prediction in Bluetooth with Machine Learning Classifiers." Energies 14, no. 4 (February 10, 2021): 928. http://dx.doi.org/10.3390/en14040928.

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Thanks to the frequency hopping nature of Bluetooth, sniffing Bluetooth traffic with low-cost devices has been considered as a challenging problem. To this end, BlueEar, a state-of-the-art low-cost sniffing system with two Bluetooth radios proposes a set of novel machine learning-based subchannel classification techniques for adaptive frequency hopping (AFH) map prediction by collecting packet statistics and spectrum sensing. However, there is no explicit evaluation results on the accuracy of BlueEar’s AFH map prediction. To this end, in this paper, we revisit the spectrum sensing-based classifier, one of the subchannel classification techniques in BlueEar. At first, we build an independent implementation of the spectrum sensing-based classifier with one Ubertooth sniffing radio. Using the implementation, we conduct a subchannel classification experiment with several machine learning classifiers where spectrum features are utilized. Our results show that higher accuracy can be achieved by choosing an appropriate machine learning classifier and training the classifier with actual AFH maps.Our results show that higher accuracy can be achieved by choosing an appropriate machine learning classifier and training the classifier with actual AFH maps.

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2

Wang, Fang, and Xu He. "Simulation and Analysis of SNR Estimation Algorithm Based on Observation Vector Covariance Matrix." Advanced Materials Research 403-408 (November 2011): 2168–71. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.2168.

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AFH (adaptive frequency hopping) is the key technology of modern military tactics anti-interference, and channel quality evaluation is the core technology of AFH system. This paper describes the SNR estimation algorithm based on observation vector covariance matrix, and analyzes the mean and MMSE (minimum mean square error) of the SNR estimation algorithm based on autocorrelation and covariance matrix in the condition of AWGN and Rayleigh fading channels. The result shows that the SNR estimation algorithm based on covariance matrix has a smaller estimation error and more timely, which can be applied by AFH communication system.

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3

Zander, J. "Adaptive frequency hopping in HF communications." IEE Proceedings - Communications 142, no. 2 (1995): 99. http://dx.doi.org/10.1049/ip-com:19951650.

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4

Nemsick, L. W., and E. Geraniotis. "Adaptive multichannel detection of frequency-hopping signals." IEEE Transactions on Communications 40, no. 9 (1992): 1502–11. http://dx.doi.org/10.1109/26.163571.

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5

Torrieri, D., and K. Bakhru. "An anticipative adaptive array for frequency-hopping communications." IEEE Transactions on Aerospace and Electronic Systems 24, no. 4 (July 1988): 449–56. http://dx.doi.org/10.1109/7.7187.

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6

Liang, Xiao Hu, and Lei Cheng. "On the Research of Adaptive Frequency Hopping in the Wireless Communication." Applied Mechanics and Materials 347-350 (August 2013): 2033–37. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.2033.

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The multipath fading and interference problems in the wireless communication lead to the link quality decrease severely. However, the conventional frequency hopping scheme cannot solve the problems in an effective way. Adaptive frequency hopping scheme, which is based on the automatically link quality analysis, can avoid the bad frequencies and guarantee the desired level of channel quality. The system is analyzed based on the adaptive frequency hopping model equipped with link quality analyzer which is different from the traditional one. In the paper, some newly proposed adaptive frequency hopping schemes have been summarized, which provide an important reference for the practical application.

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7

Ruan, Jin Xin, Yan Xu, and Miao Cui. "Frequency-Hopping Communication Technology Based on Self-Adaptive MIMO-OFDM System." Advanced Materials Research 945-949 (June 2014): 2230–36. http://dx.doi.org/10.4028/www.scientific.net/amr.945-949.2230.

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Along with the gradual increase of intelligent and information equipment on the battlefield, the fierce electronic warfare between the enemy and us makes the electromagnetic environment of the battlefield more and more severe. The anti-jamming capability of conventional frequency-hopping communication system is inadequate such as anti-dynamic interference, anti-intercept, etc., thus posing a serious threat to normal military communication. Moreover, currently the data transmission rate of frequency-hopping system is fairly lower, and cannot meet the increasing large-capacity real-time data transmission requirements. This article deeply researches self-adaptive MIMO-OFDM technology and frequency-hopping communication technology, and introduces the research on frequency-hopping communication technology based on self-adaptive MIMO-OFDM system. The research shows that self-adaptive MIMO-OFDM-based technology can effectively enhance the frequency-hopping communication system’s anti-jamming and anti-intercepting capability, and improve the data transmission rate.

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8

Torrieri, Don, and Kesh Bakhru. "Frequency Compensation in an Adaptive Antenna System for Frequency-Hopping Communications." IEEE Transactions on Aerospace and Electronic Systems AES-23, no. 4 (July 1987): 448–67. http://dx.doi.org/10.1109/taes.1987.310878.

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9

Seung-Hwan Lee and Yong-Hwan Lee. "Adaptive frequency hopping for bluetooth robust to WLAN interference." IEEE Communications Letters 13, no. 9 (September 2009): 628–30. http://dx.doi.org/10.1109/lcomm.2009.090115.

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10

Sabbagh, I., and D. G. Appleby. "Adaptive slow frequency-hopping system for land mobile radio." IEE Proceedings F Communications, Radar and Signal Processing 132, no. 5 (1985): 375. http://dx.doi.org/10.1049/ip-f-1.1985.0076.

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11

You, Y. H., C. H. Park, M. C. Ju, K. W. Kwon, and J. W. Cho. "Adaptive frequency hopping scheme for interference-limited WPAN applications." Electronics Letters 37, no. 15 (2001): 976. http://dx.doi.org/10.1049/el:20010637.

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12

Popovski, Petar, Hiroyuki Yomo, and Ramjee Prasad. "Strategies for adaptive frequency hopping in the unlicensed bands." IEEE Wireless Communications 13, no. 6 (December 2006): 60–67. http://dx.doi.org/10.1109/mwc.2006.275200.

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13

Liu, Qidi, and Mable P. Fok. "Ultrafast and Wideband Microwave Photonic Frequency-Hopping Systems: A Review." Applied Sciences 10, no. 2 (January 10, 2020): 521. http://dx.doi.org/10.3390/app10020521.

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The increasing demands to enhance information security in data transmission, providing countermeasures against jamming in military applications, as well as boosting data capacity in mobile and satellite communication, have led to a critical need for high-speed frequency-hopping systems. Conventional electronics-based frequency-hopping systems suffer from low data rate, low hopping speed, and narrow hopping-frequency bandwidth. Unfortunately, those are important aspects to facilitate frequency-hopping in emerging microwave systems. The recent advancement of microwave photonics—the use of light to process microwave signals—provides promising solutions to tackle the challenges faced by electronic frequency-hopping systems. In this paper, the challenges of achieving real-time frequency-hopping systems are examined. The operation principles and results of various microwave photonics-enabled frequency-hopping systems are comprehensively discussed, which have wide hopping-frequency bandwidth and frequency-hopping speed from nanoseconds to tens of picoseconds. Lastly, a bio-inspired jamming-avoidance system that could potentially be used for adaptive frequency-hopping is also introduced.

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14

Cho, Hyun-Seob. "A Study on Interference Cancellation of Adaptive Frequency Hopping System." Journal of Korea Institute of Information, Electronics, and Communication Technology 10, no. 5 (October 30, 2017): 396–401. http://dx.doi.org/10.17661/jkiiect.2017.10.5.396.

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15

Wong, S. W., and G. F. Gott. "Performance of adaptive frequency hopping modem on an HF link." IEE Proceedings I Communications, Speech and Vision 137, no. 6 (1990): 371. http://dx.doi.org/10.1049/ip-i-2.1990.0050.

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16

Doany, P., and G. F. Gott. "Theoretical performance of an adaptive frequency-hopping modem at HF." IEE Proceedings F Communications, Radar and Signal Processing 133, no. 5 (1986): 470. http://dx.doi.org/10.1049/ip-f-1.1986.0073.

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17

Qingxin Chen, E. S. Sousa, and S. Pasupathy. "Multicarrier CDMA with adaptive frequency hopping for mobile radio systems." IEEE Journal on Selected Areas in Communications 14, no. 9 (1996): 1852–58. http://dx.doi.org/10.1109/49.545707.

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18

Popovski, P., H. Yomo, and R. Prasad. "Dynamic adaptive frequency hopping for mutually interfering wireless personal area networks." IEEE Transactions on Mobile Computing 5, no. 8 (August 2006): 991–1003. http://dx.doi.org/10.1109/tmc.2006.114.

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19

Aykin, Irmak, Marwan Krunz, and Yong Xiao. "Adaptive frequency-hopping schemes for CR-based multi-link satellite networks." International Journal of Satellite Communications and Networking 36, no. 4 (March 25, 2018): 315–31. http://dx.doi.org/10.1002/sat.1235.

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20

Lie-Liang Yang and L. Hanzo. "Software-defined-radio-assisted adaptive broadband frequency hopping multicarrier DS-CDMA." IEEE Communications Magazine 40, no. 3 (March 2002): 174–83. http://dx.doi.org/10.1109/35.989783.

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21

Park, K. J., T. R. Park, C. D. Schmitz, and L. Sha. "Design of robust adaptive frequency hopping for wireless medical telemetry systems." IET Communications 4, no. 2 (2010): 178. http://dx.doi.org/10.1049/iet-com.2008.0693.

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22

Sun, Bingcheng, JinFeng Li, and Hongfeng Cui. "Adaptive Asymmetric Frequency Hopping Communication Scheme Based on Spectrum Hole Detection." Journal of Physics: Conference Series 1865, no. 2 (April 1, 2021): 022042. http://dx.doi.org/10.1088/1742-6596/1865/2/022042.

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23

Kang, Kyeongwon, and Sangseol Lee. "Linear transmitter for a frequency-hopping system using an adaptive predistortion linearizer." Microwave and Optical Technology Letters 31, no. 6 (2001): 457–60. http://dx.doi.org/10.1002/mop.10062.

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24

Stojan, Ivo. "A Dynamic Interference-Avoidance Algorithm for Frequency Hopping Systems." Journal of Communications Software and Systems 5, no. 2 (June 22, 2009): 74. http://dx.doi.org/10.24138/jcomss.v5i2.208.

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In this paper we investigate an algorithm for the Adaptive Frequency Hopping mechanism that is used by frequency dynamic systems to mitigate interference from othersystems. With this algorithm we introduce several improvements in relation to the existing algorithms that are based on the approach of using Packet Error Rate as the means for channel classification. One is the use of a single criterion for channel classification regardless of the dynamics of interfering systems, which adds more flexibility and reduces the risk of erroneous channel classification. The second is the introduction of the concept of channel probing which ensures that channels that areexcluded from the hopset are not used until they are clear from interference. The third improvement is the parameterization of the algorithm, which enables the control of the trade off between the main achievements of the algorithm: throughput and quickness of adaptation to changing interference. We show these achievements of the proposed algorithm through simulation.

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25

Qiao, Cheng Lin, Hou De Quan, and Pei Zhang Cui. "Research of Frequency-Hopping Communication for Arbitrary Array Based on Adaptive Beam-Forming." Advanced Materials Research 989-994 (July 2014): 3693–97. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.3693.

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Aiming at the problem of poor performance of suppressing the wide band jamming and fast following jamming in Frequency-Hopping (FH) communication system, a communication scheme by combination of the complementally transformed minimum variance with FH technique for arbitrary array (CTMV-FH) is proposed, based on the purpose to maximize the output Signal to Interference and Noise Ratio (SINR). Basic theory of CTMV is introduced. The algorithm is used to suppress the wide band jamming and fast following jamming. Simulation results show that the scheme can suppress the wide band jamming and fast following jamming effectively in FH communication system.

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26

KWON, J. M., Y. H. LEE, N. S. KIM, and H. LEE. "Adaptive Adjustment of Integration Time for BPSK Based Ultra-Wideband Frequency Hopping Receiver." IEICE Transactions on Communications E90-B, no. 7 (July 1, 2007): 1848–51. http://dx.doi.org/10.1093/ietcom/e90-b.7.1848.

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27

Jia, T., and Alexandra Duel-Hallen. "Improved channel allocation for multicarrier CDMA with adaptive frequency hopping and multiuser detection." IEEE Transactions on Communications 57, no. 11 (November 2009): 3389–96. http://dx.doi.org/10.1109/tcomm.2009.11.070575.

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28

Ming Lei, A. Duel-Hallen, and H. Hallen. "Reliable adaptive modulation and interference mitigation for mobile radio slow frequency hopping channels." IEEE Transactions on Communications 56, no. 3 (March 2008): 352–55. http://dx.doi.org/10.1109/tcomm.2008.040662.

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29

Tanbourgi, Ralph, Jens P. Elsner, Holger Jakel, and Friedrich K. Jondral. "Adaptive Frequency Hopping in Ad Hoc Networks with Rayleigh Fading and Imperfect Sensing." IEEE Wireless Communications Letters 1, no. 3 (June 2012): 185–88. http://dx.doi.org/10.1109/wcl.2012.031512.120034.

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30

Xu, Xiaoyu, Hao Hu, Yuling Liu, Hongqi Zhang, and Dexian Chang. "An Adaptive IP Hopping Approach for Moving Target Defense Using a Light-Weight CNN Detector." Security and Communication Networks 2021 (August 10, 2021): 1–17. http://dx.doi.org/10.1155/2021/8848473.

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Scanning attack is normally the first step of many other network attacks such as DDoS and propagation worm. Because of easy implementation and high returns, scanning attack especially cooperative scanning attack is widely used by hackers, which has become a serious threat to network security. In order to defend against scanning attack, this paper proposes an adaptive IP hopping in software defined network for moving target defense (MTD). In order to accurately respond to attacker’s behavior in real time, a light-weight convolutional neural network (CNN) detector composed of three convolutional modules and a judgment module is proposed to sense scanning attack. Input data of the detector is generated via designed packets sampling and data preprocess. The detection result of the detector is used to trigger IP hopping. In order to provide some fault tolerance for the CNN detector, IP hopping can also be triggered by a preset timer. The CNN driving adaptability is applied to a three-level hopping strategy to make the MTD system optimize its behavior according to real time attack. Experiments show that compared with existing technologies, our proposed method can significantly improve the defense effect to mitigate scanning attack and its subsequent attacks which are based on hit list. Hopping frequency of the proposed method is also lower than that of other methods, so the proposed method shows lower system overhead.

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31

Takakusaki, Keiji, and Masao Nakagawa. "A coherent demodulator for fast frequency-hopping spread-spectrum signal employing an adaptive algorithm." Electronics and Communications in Japan (Part I: Communications) 78, no. 3 (March 1995): 55–64. http://dx.doi.org/10.1002/ecja.4410780306.

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32

Kim, Jin Young. "Throughput enhancement of frequency-hopping spread-spectrum network with adaptive antenna array and packet combining." Electronics Letters 35, no. 4 (1999): 280. http://dx.doi.org/10.1049/el:19990093.

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33

Cormio, Claudia, and Kaushik R. Chowdhury. "Common control channel design for cognitive radio wireless ad hoc networks using adaptive frequency hopping." Ad Hoc Networks 8, no. 4 (June 2010): 430–38. http://dx.doi.org/10.1016/j.adhoc.2009.10.004.

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34

Linde, L. P. "AGC strategy for adaptive digital modems employing cyclic channel estimation in an HF frequency hopping scenario." IEE Proceedings I Communications, Speech and Vision 138, no. 3 (1991): 185. http://dx.doi.org/10.1049/ip-i-2.1991.0025.

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35

Lee, Seung-Hwan, and Yong-Hwan Lee. "Adaptive frequency hopping and power control based on spectrum characteristic of error sources in Bluetooth systems." Computers & Electrical Engineering 36, no. 2 (March 2010): 341–51. http://dx.doi.org/10.1016/j.compeleceng.2009.03.011.

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36

Cho, Namjun, Long Yan, Joonsung Bae, and Hoi-Jun Yoo. "A 60 kb/s–10 Mb/s Adaptive Frequency Hopping Transceiver for Interference-Resilient Body Channel Communication." IEEE Journal of Solid-State Circuits 44, no. 3 (March 2009): 708–17. http://dx.doi.org/10.1109/jssc.2008.2012328.

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37

Wu, Wei-Chiang. "Direct Blind Adaptive MOE Receiver for PAM Modulated Time-Hopping UWB System Over Frequency-Selective Fading Channel." Circuits, Systems & Signal Processing 27, no. 1 (February 2008): 65–80. http://dx.doi.org/10.1007/s00034-008-9016-0.

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38

He, Yishan, Yufan Cheng, Gang Wu, Binhong Dong, and Shaoqian Li. "Adaptive Jamming Suppression in Coherent FFH System Using Weighted Equal Gain Combining Receiver over Fading Channels with Imperfect CSI." Journal of Electrical and Computer Engineering 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/687874.

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Fast frequency hopping (FFH) is commonly used as an antijamming communication method. In this paper, we propose efficient adaptive jamming suppression schemes for binary phase shift keying (BPSK) based coherent FFH system, namely, weighted equal gain combining (W-EGC) with the optimum and suboptimum weighting coefficient. We analyze the bit error ratio (BER) of EGC and W-EGC receivers with partial band noise jamming (PBNJ), frequency selective Rayleigh fading, and channel estimation errors. Particularly, closed-form BER expressions are presented with diversity order two. Our analysis is verified by simulations. It is shown that W-EGC receivers significantly outperform EGC. As compared to the maximum likelihood (ML) receiver in conventional noncoherent frequency shift keying (FSK) based FFH, coherent FFH/BPSK W-EGC receivers also show significant advantages in terms of BER. Moreover, W-EGC receivers greatly reduce the hostile jammers’ jamming efficiency.

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39

ALgalbi, Wamidh. "Solving the Near-Far Problem in Dynamic Frequency Hopping-Optical Code Division Multiple Access using Power Control." Iraqi Journal for Electrical and Electronic Engineering 7, no. 2 (December 1, 2011): 88–93. http://dx.doi.org/10.37917/ijeee.7.2.1.

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In this study, a distributed power control algorithm is proposed for Dynamic Frequency Hopping Optical-CDMA (DFH-OCDMA) system. In general, the DFH-OCDMA can support higher number of simultaneous users compared to other OCDMA techniques. However, the performance of such system degrades significantly as the received power does lower than its minimum threshold. This may obviously occur in a DFH-OCDMA network with near-far problem which consist of different fiber lengths among the users, that resulting to unequal power attenuation. The power misdistribution among simultaneous active users at the star coupler would degrade the Bit Error Rate (BER) performance for users whose transmitting signals with longer fiber lengths. In order to solve these problems, we propose an adaptive distributed power control technique for DFH-OCDMA to satisfy the target Signal to oise Ratio (S R) for all users. Taking into account the noise effects of Multiple Access Interference (MAI), Phase Induced Intensity oise (PII ) and shot noise, the system can support 100% of users with power control as compared to 33% without power control when the initial transmitted power was -1dBm with 30 simultaneous users.

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40

Xiong, Xing-Ting, Xing-Hua Qu, and Fu-Min Zhang. "Error Correction for FSI-Based System without Cooperative Target Using an Adaptive Filtering Method and a Phase-Matching Mosaic Algorithm." Applied Sciences 8, no. 10 (October 17, 2018): 1954. http://dx.doi.org/10.3390/app8101954.

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In our frequency scanning interferometry-based (FSI-based) absolute distance measurement system, a frequency sampling method is used to eliminate the influence of laser tuning nonlinearity. However, because the external cavity laser (ECL) has been used for five years, factors such as the mode hopping of the ECL and the low signal-to-noise ratio (SNR) in a non-cooperative target measurement bring new problems, including erroneous sampling points, phase jumps, and interfering signals. This article analyzes the impacts of the erroneous sampling points and interfering signals on the accuracy of measurement, and then proposes an adaptive filtering method to eliminate the influence. In addition, a phase-matching mosaic algorithm is used to eliminate the phase jump, and a segmentation mosaic algorithm is used to improve the data processing speed. The result of the simulation proves the efficiency of our method. In experiments, the measured target was located at eight different positions on a precise guide rail, and the incident angle was 12 degrees. The maximum deviation of the measured results between the FSI-based system and the He-Ne interferometer was 9.6 μm, and the maximum mean square error of our method was 2.4 μm, which approached the Cramer-Rao lower bound (CRLB) of 0.8 μm.

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41

Same, Mohammad Hossein, Gabriel Gleeton, Gabriel Gandubert, Preslav Ivanov, and Rene Jr Landry. "Multiple Narrowband Interferences Characterization, Detection and Mitigation Using Simplified Welch Algorithm and Notch Filtering." Applied Sciences 11, no. 3 (February 2, 2021): 1331. http://dx.doi.org/10.3390/app11031331.

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By increasing the demand for radio frequency (RF) and access of hackers and spoofers to low price hardware and software defined radios (SDR), radio frequency interference (RFI) became a more frequent and serious problem. In order to increase the security of satellite communication (Satcom) and guarantee the quality of service (QoS) of end users, it is crucial to detect the RFI in the desired bandwidth and protect the receiver with a proper mitigation mechanism. Digital narrowband signals are so sensitive into the interference and because of their special power spectrum shape, it is hard to detect and eliminate the RFI from their bandwidth. Thus, a proper detector requires a high precision and smooth estimation of input signal power spectral density (PSD). By utilizing the presented power spectrum by the simplified Welch method, this article proposes a solid and effective algorithm that can find all necessary interference parameters in the frequency domain while targeting practical implantation for the embedded system with minimum complexity. The proposed detector can detect several multi narrowband interferences and estimate their center frequency, bandwidth, power, start, and end of each interference individually. To remove multiple interferences, a chain of several infinite impulse response (IIR) notch filters with multiplexers is proposed. To minimize damage to the original signal, the bandwidth of each notch is adjusted in a way that maximizes the received signal to noise ratio (SNR) by the receiver. Multiple carrier wave interferences (MCWI) is utilized as a jamming attack to the Digital Video Broadcasting-Satellite-Second Generation (DVB-S2) receiver and performance of a new detector and mitigation system is investigated and validated in both simulation and practical tests. Based on the obtained results, the proposed detector can detect a weak power interference down to −25 dB and track a hopping frequency interference with center frequency variation speed up to 3 kHz. Bit error ratio (BER) performance shows 3 dB improvement by utilizing new adaptive mitigation scenario compared to non-adaptive one. Finally, the protected DVB-S2 can receive the data with SNR close to the normal situation while it is under the attack of the MCWI jammer.

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42

Migabo, Emmanuel, Karim Djouani, and Anish Kurien. "A Novel Spread Spectrum and Clustering Mixed Approach with Network Coding for Enhanced Narrowband IoT (NB-IoT) Scalability." Sensors 20, no. 18 (September 13, 2020): 5219. http://dx.doi.org/10.3390/s20185219.

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The Narrowband Internet of Things (NB-IoT) is a very promising licensed Internet of things (IoT) technology for accommodating massive device connections in 5G and beyond. To enable network scalability, this study proposes a two-layers novel mixed approach that aims not only to create an efficient spectrum sharing among the many NB-IoT devices but also provides an energy-efficient network. On one layer, the approach uses an Adaptive Frequency Hopping Spread Spectrum (AFHSS) technique that uses a lightweight and secure pseudo-random sequence to exploit the channel diversity, to mitigate inter-link and cross-technology interference. On the second layer, the approach consists of a clustering and network coding (data aggregation) approach based on an energy-signal strength mixed gradient. The second layer contributes to offload the BS, allows for energy-efficient network scalability, helps balance the energy consumption of the network, and enhances the overall network lifetime. The proposed mixed strategy algorithm is modelled and simulated using the Matrix Laboratory (MATLAB) Long Term Evolution (LTE) toolbox. The obtained results reveal that the proposed mixed approach enhances network scalability while improving energy efficiency, transmission reliability, and network lifetime when compared to the existing spread spectrum only, nodes clustering only, and mixed approach with no network coding approaches.

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43

Mohammed, Bassim Sayed, and Dalya Khalid Hasan. "Estimating Angle of Arrival (AOA) for Wideband Signal by Sensor Delay Line (SDL) and Tapped Delay Line (TDL) Processors." Journal of Engineering 24, no. 4 (March 31, 2018): 96. http://dx.doi.org/10.31026/j.eng.2018.04.07.

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Angle of arrival (AOA) estimation for wideband signal becomes more necessary for modern communication systems like Global System for Mobile (GSM), satellite, military applications and spread spectrum (frequency hopping and direct sequence). Most of the researchers are focusing on how to cancel the effects of signal bandwidth on AOA estimation performance by using a transversal filter (tap delay line) (TDL). Most of the researchers were using two elements array antenna to study these effects. In this research, a general case of proposed (M) array elements is used. A transversal filter (TDL) in phase adaptive array antenna system is used to calculate the optimum number of taps required to compensate these effect. The proposed system uses a phase adaptive array antenna in conjunction with LMS algorithm to work an angle of arrival (AOA) estimator for wideband signals rather than interference canceller. An alternative solution to compensate for the effect of signal bandwidth is proposed by using sensor delay line (SDL) instead of fixed delay unit since it has variable time sampling in the time domain and not fixed time delay, depending on the angle of arrival of received signals. The proposed system has the ability to estimate two parameters for received signals simultaneously (the output Signal to Noise Ratio (SNR) and AOA), unlike others systems which estimate AOA only. The comparison of the simulation results with Multiple Signal Classification (MUSIC) technique showed that the proposed system gives good results for estimating AOA and the output SNR for wideband signals. (SDL) processor shows better performance result than (TDL) processor. MUSIC technique with both (SDL) and (TDL) processors shows unacceptable results for estimating (AOA) for the wideband signal.

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44

"5539769 Adaptive fuzzy frequency hopping system." Journal of Cleaner Production 4, no. 3-4 (January 1996): 263. http://dx.doi.org/10.1016/s0959-6526(97)88912-3.

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45

YU, Xin-yong, Ying GUO, Yang XUE, Kun-feng ZHANG, Lei LI, and Hong-guang LI. "Network Sorting Algorithm for Multi-frequency Hopping Signals with Adaptive SNR." DEStech Transactions on Computer Science and Engineering, ameit (July 27, 2017). http://dx.doi.org/10.12783/dtcse/ameit2017/12302.

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46

Kongtep, Jutamas. "Adaptive Frequency Hopping Scheme for Wireless Distribution System (WDS) in WLAN." International Journal of Computer and Communication Engineering, 2012, 486–89. http://dx.doi.org/10.7763/ijcce.2012.v1.119.

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47

"Adaptive Band Jamming in Wireless Networks using Fast Frequency Hopping and Non-Coherent Detection." International Journal of Recent Trends in Engineering and Research 3, no. 12 (December 20, 2017): 89–97. http://dx.doi.org/10.23883/ijrter.2017.3541.ll2p1.

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Sohn, Sung Hwan. "HMM-based Adaptive Frequency-Hopping Cognitive Radio System to Reduce Interference Time and to Improve Throughput." KSII Transactions on Internet and Information Systems, 2010. http://dx.doi.org/10.3837/tiis.2010.08.002.

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Ghanem, Sameh. "Decoding and measurement of frequency‐hopping spread spectrum signals using an adaptive algorithm‐based compressive sensing." International Journal of Communication Systems 34, no. 3 (November 3, 2020). http://dx.doi.org/10.1002/dac.4675.

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