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Register a new userSelecting the Best Signal Amplitude in the Smart Antenna Output by Using Neural Networks
اختيار الإشارة ذات المطال الأفضل على خرج الهوائي الذكي باستخدام الشبكات العصبونية
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Tishreen University ورقة بحثية
Publication date
2014
fields
Communication Engineering
and research's language is
العربية
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Shamra Editor
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طُبق مفهوم إعادة استخدام التردد بشكل ناجح في أنظمة الاتصالات الخليوية الحديثة، من أجل زيادة سعة النظام، من الممكن إحداث تحسُّن آخر في السعة بتطبيق المصفوفات المتكيفة في المحطة الأساسية، يستخدم من أجل ملاحقة المستخدمين المرغوبين خوارزميات إيجاد الاتجاه من أجل تحديد أماكنهم وفقاً لحركتهم ضمن الخلايا أو فيمابينها. اقترح مؤخراً خوارزميات إيجاد الاتجاه المعتمدة على الشبكات العصبونية وذلك لإيجاد اتجاه المنبع عن طريق تقييم أداء الشبكات العصبونية بمقارنة توقعاتها وانحرافها المعياري ومتوسط الخطأ التربيعي بين قيمها المتوقعة وبين ماتم قياسه، هذا البحث يعتمد هذا المنحى حيث يتم مقارنة خرج الهوائيات المصفوفية من حيث المطال، ثم اختيار الإشارة ذات المطال الأفضل وإظهارها على الخرج النهائي للنظام.
The concept of frequency reuse has been successfully implemented in modern cellular communications systems in order to increase the system capacity. Further improvement of capacity can be achieved by employing adaptive arrays at the base station. In order to track the desired users, direction finding algorithms are used to locate the positions of mobile users as they move within or between cells. Recently, neural networks-based direction finding algorithms have been supposed for source direction finding. The performance of neural network is evaluated by comparing their prediction, standard deviation and Mean Square Error (MSE) between their predicted and measurement values. The research depends on this context. So, it has been compared the antenna array output signals according to their amplitude, then selected the signal that has the best amplitude in the system’s final output.
References used
GODARA, L. C. Smart Antenna.CRC Press LLC, United States of America, 2004, 458P
JAIN, R. K. ; KATIYAR, S. ; AGRAWAL, N. Smart Antenna for Cellular Mobile Communications. International Journal of Electrical, Electronics & Communication engineering, VSRD, India,Vol.1(9), 2011, pp.530-541
SAREVSKA, M. ; ABDEL-BADEEH M. S. Antenna Array Beamforming Using Neural Network. World Academy & Science, Engineering And Technology, 2006
MATHUR, S. ; GONGUAR, R. S. A Decision Directed Smart Antenna System With Neural Estimation for M-Quadrature Amplitude Modulated Signal. Indian Journal of Radio & Space Physics, India, Vol.39, 2010, pp.45-52
RAO, p. A.; SARMA, N. V. Adaptive Beamforming Algorithm for Smart Antenna Systems. WSEAS transactions on communications, vol.13, India, 2014, pp.2224-2864
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