Automatic recognition of the digital modulation types using the artificial neural networks

As digital communication technologies continue to grow and evolve, applications for this steady development are also growing. This growth has generated a growing need to look for automated methods for recognizing and classifying the digital modulation type used in the communication system, which has an important effect on many civil and military applications. This paper suggests a recognizing system capable of classifying multiple and different types of digital modulation methods (64QAM, 2PSK, 4PSK, 8PSK, 4ASK, 2FSK, 4FSK, 8FSK). This paper focuses on trying to recognize the type of digital modulation using the artificial neural network (ANN) with its complex algorithm to boost the performance and increase the noise immunity of the system. This system succeeded in recognizing all the digital modulation types under the current study without any prior information. The proposed system used 8 signal features that were used to classify these 8 modulation methods. The system succeeded in achieving a recognition ratio of at least 68% for experimental signals on a signal to noise ratio (SNR = 5dB) and 89.1% for experimental signals at (SNR = 10dB) and 91% for experimental signals at (SNR = 15dB) for a channel with Additive White Gaussian Noise (AWGN)

Reduce side lobes using linear Antenna Arrays by comparing PSO, GA, and FPA algorithms

ان مصفوفات الهوائي الخطي هي نظام كهرومغناطيسي يستخدم على نطاق واسع في الاتصالات اللاسلكية الحديثة، وقد تم استخدام خوارزميات الميتاهوريستس لتقليل مستوى الفص الجانبي والوصول إلى الحل الأمثل. يستخدم هذه البحث ثلاث خوارزميات: الأولى، تحسين سرب الجسيمات، والثانية، الخوارزمية الجينية، والثالثة، خوارزمية تلقيح الزهور. يتكون كل اختبار من عدد العناصر 8و16و32و64و128و256. عنصرًا من مجموعة عناصر الهوائي. لتقليل مستوى الفص الجانبي وتركيز الطاقة المشعة في الفص الرئيسي، تقارن كل خوارزمية نمط الحزمة بنمط الحزمة النظرية. بالإضافة إلى ذلك، تمت مقارنة الخوارزميات بوجود نمط الحزمة النظرية، وتم اكتشاف وجود خوارزمية فائقة لكل عدد من عناصر الهوائي؛ في ن= 8 عند مقارنة خوارزمية التلقيح بالخوارزميات الأخرى، تم اكتشاف أنها قللت مستوى الفص الجانبي بقيمة 20.8492- ديسبل، والتي كانت متفوقة على الخوارزميات الأخرى. انخفض مستوى الفص الجانبي بمقدار 27.2992- ديسبل، عند مقارنة خوارزمية تحسين سرب الجسيمات مع الخوارزميات الأخرى عند ن=16, عندما ن = 32,64 يمثل خوارزمية تلقيح الجسيمات بشكل أكثر دقة من الخوارزميات الأخرى حيث انخفض الفص الجانبي إلى 28.3071-ديسبل و 28.0148- ديسبل، على التوالي. ان الخوارزمية الجينية متفوقة على الخوارزميات الأخرى عندما ن= 128و256، مما يقلل الفصوص الجانبية بنسبة 28.5568- ديسبل -28.6204- ديسبل، على التوالي.Linear Antenna Arrays (LAAs) are widely used electromagnetic systems in modern wireless communication, and Metaheuristics algorithms have been utilized to reduce side lobe level SLL and reach the optimal solution. This paper employs three algorithms: the first, Particle Swarm Optimization PSO, the second, Genetic Algorithm GA, and the third, Flower Pollination Algorithm FPA. Each test consists of N = 8, 16, 32, 64, 128, and 256 antenna array elements. To reduce SLL and the concentration of radioactive energy in the main lobe, each algorithm compares the beam pattern to the theoretical beam pattern. In addition, the algorithms were compared with the existence of the theoretical beam pattern, and it was discovered that there is a superior algorithm for each number of antenna elements; in N = 8, when comparing FPA to other algorithms, it was discovered that FPA reduced SLL by a value of -20.8492dB, which was superior to the other algorithms. SLL decreased by -27.2992dB when comparing PSO with other algorithms at N = 16. When N = 32,64 represents FPA more accurately than other algorithms where the SLL plummeted to -28.3071dB and -28.0148dB, respectively. GA is superior to other algorithms when N = 128,256, reducing SLL by -28.5568 dB and -28.6204 dB, respectively

Design of Film Bulk Acoustic Wave Sensor for Internet of Things (IoT) Applications

التوسع السريع لإنترنت الاشياء أدى إلى زيادة الطلب على تقنيات الاستشعار المبتكرة التي يمكن أن توفر بيانات في الوقت الفعلي لمختلف التطبيقات. رنانات الموجات الصوتية ذات الاغشية الرقيقة (FBARs) هي رنانات مصغرة تستخدم التأثير الكهرو إجهادي لإنشاء إشارات كهربائية باستخدام الاهتزازات الميكانيكية والعكس صحيح. ظهرت رنانات FBAR كمتحسسات واعدة لتطبيقات الاستشعار في إنترنت الأشياء نظرًا لحجمها الصغير وحساسيتها العالية وتوافقها مع تقنيات التصنيع الدقيق. يقدم هذا البحث تصميم مستشعر FBAR  لتطبيقات انترنت الاشياء التي تتكون من أكسيد الزنك (ZnO) و ليثيوم نيوباتيت(LiNbO3)  كمواد كهروضغطية والالمنيوم كأقطاب كهربائية علوية وسفلية. تظهر النتائج الأداء المتفوق للرنان المقترح. بناءً على نتائج النمذجة ، فإن تردد الرنين هو 12.02 و 10.36 جيجاهرتز مع عامل جودة 936.7 و 941.3 ومعامل الاقتران الفعال 18.35 و 18.27٪ لـ أكسيد الزنك و ليثيوم نيوباتيت على التوالي.The Internet of Things (IoT) is expanding quickly, which has increased demand for innovative sensing technologies that can provide real-time data for various applications. Film Bulk Acoustic Wave Resonators (FBARs) are miniature resonators that utilize the piezoelectric effect to create electrical signals using mechanical vibrations and vice versa. FBAR resonators have emerged as promising candidates for sensor applications in IoT due to their compact size, high sensitivity, and compatibility with microfabrication techniques. This paper presents design of FBAR sensor as gas and pressure sensor for IOT applications consisting of zinc oxide (ZnO) and Lithium niobate (LiNbO3) as piezoelectric film and Aluminum (Al) as top and bottom electrodes. The results show the superior performance of the proposed resonator. Based on the modeling results, the structure's resonance frequency is 12.02 and 10.36 GHz with a quality factor of 936.7 and 941.3 and an effective coupling coefficient of  18.35 and 18.27 % for ZnO and LiNbO3 respectively

Wireless sensor network’s localization based on multiple signal classification algorithm

Wireless sensor networks (WSNs) are a number of sensitive nodes senses a physical phenomenon at the position of their deployment then sends information to the base station to take appropriate operation. (WSNs) are used in many applications such track military targets, discover fires, study natural phenomena such as earthquakes, humidity, heat, etc. The nodes are spread in large areas and it is difficult to locate them manually because they are published randomly by planes or any other method and since the information received from sensitive nodes is useless without knowing their location in this case a problem resulted in the positioning of the nodes. So it unacceptable to equip each sensor node with global position system (GPS) due to various problems such as raises cost and energy consumption. In this paper explained a non-GPS technique to self-positioning of nodes in (WSNs) by using the multiple signal classification (MUSIC) algorithm to determine the position of the active sensor through estimated the direction of arrival (DOA) of the node signal. Then modified MUSIC algorithm (M-MUSIC) to solve the problem of coherent signal. MATLAB program successfully used to simulate the proposed algorithm

Performance Analysis of MEMS Based Oscillator for High Frequency Wireless Communication Systems

The frequency oscillator is a basic component found in many electrical, electronic, and communications circuits and systems. Oscillators come in a variety of shapes and sizes, depending on the frequency range employed in a given application. Some applications need oscillators that generate low frequencies and other applications need oscillators that generate extremely high and high frequencies. As a result of the expansion and speed of modern technologies, new oscillators appeared that operating at extremely high frequencies. Most wireless communication systems are constrained in their performance by the accuracy and stability of the reference frequency. Because of its compatibility with silicon, micro-electro-mechanical system (MEMS) is the preferred technology for circuit integration and power reduction. MEMS are a rapidly evolving area of advanced microelectronics. The integration of electrical and mechanical components at the micro size is referred to as a MEMS. MEMS based oscillators have demonstrated tremendous high frequency application potential in recent years. This is owing to their great characteristics such as small size, integration of CMOS IC technology, high frequency-quality factor product, low power consumption, and cheap batch manufacturing cost. This paper's primary objective is to describe the performance of MEMS oscillator technology in high-frequency applications, as well as to discuss the challenges of developing a new MEMS oscillator capable of operating at gigahertz frequencies