http://ir.haramaya.edu.et//hru/handle/123456789/82 Wed, 08 Apr 2026 21:56:18 GMT 2026-04-08T21:56:18Z http://ir.haramaya.edu.et//hru/handle/123456789/8332 COMPARISON OF LINEAR CHANNEL ESTIMATION TECHNIQUES FOR 5G NETWORKS ABDURO GUYE; Ritesh Pratap Singh (Assistant Prof); Asmamaw Getu (Msc) We are observing a revolution in wireless technology, where the society is demanding new services, such as smart cities, autonomous vehicles, augmented reality, etc. These challenging services not only are demanding a vast increase of data rates in the range of 1000 times higher, but also they are real-time applications with an important delay constraint. Furthermore, an extraordinary number of different machine-type devices will be connected to the network, known as Internet of Things (IoT), where they will be transmitting real-time measurements from different sensors. In this context, the Third Generation Partnership Project (3GPP) has already developed the new Fifth Generation (5G) of mobile communication systems, which should be capable of satisfying all the requirements. Hence, 5G will provide three key aspects, such as: enhanced mobile broad-band (eMBB) services, massive Area of interest in this work focus on transmitter and receiver RF propagation Channel estimation best techniques impact analysis with respect to achievable sum rates in Massive MIMO systems. In addition to study the massive MIMO RF propagation channels estimation system, the interested in the Channel estimation among different type techniques: Minimum Mean Square Error (MMSE), Zero Forcing (ZF) and Maximum Ratio Transmission (MRT) precoding. Theoretically, the precoding is known as Space Division Multiple Access. Each linear precoding shows the best performance with each signal power regime. For the comparison between MRT and ZF, MRT gives better performance at low signal to noise ratio (SNR) while ZF performs better at high SNR. MMSE gives the best channel estimation across the entire SNR. 70 Sat, 01 May 2021 00:00:00 GMT http://ir.haramaya.edu.et//hru/handle/123456789/8332 2021-05-01T00:00:00Z http://ir.haramaya.edu.et//hru/handle/123456789/7774 PERFORMANCE EVALUATION OF SPECTRUM SENSING TECHNIQUES USING DEEP LEARNING FOR COGNITIVE RADIO NETWORKS Raey Abebe; Dr. Ritesh Pratap Singh; Mr. Atli Lemma. In recent years, the spectrum demand for wireless communication services and applications has been increasing drastically besides spectrum resource management and allocation have become a hot issue. Cognitive Radio (CR) is designed and implemented to overcome this existing problem by allocating a spectrum band to Primary and Secondary users dynamically. One of the key features to decide over spectrum utilization for a CR is the spectrum sensing (SS) unit which detects and identifies spectral data from the environment. Conventional SS schemes such as Energy detection (ED), Cyclo-stationary and matched filters were first developed and employed on CRs. Their drawbacks such as the inability to exploit both spatial and temporal features of data, high false alarms and less detection probability over noisy data lead to further studies to develop AI, particularly Machine learning (ML) and Deep learning (DL) integrated models. This thesis work is mainly focused on the performance of DL-based models to sense, predict and classify a spectral dataset. Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) and Long-Short Term Memory (LSTM) models are adapted and their performance in spectrum classification has been evaluated. One of the major contributions of this thesis work was to adapt a hybrid Convolutional Recurrent neural network (CRNN) and to compare its performance with the above existing Neural Network models. CNN is a good performing model in extracting spatial features whereas RNN performs well in extracting temporal features of spectral data. The performance of these DL models has been evaluated using metrics such as classification accuracy, probability of detection (Pd), probability of false alarm (Pfa), Sensing error (SE) and confusion matrix metric formulations. The signal samples were generated with GNU for SNRs from -20 dB to 18 dB with step size of 2 dB over flat fading channel and AWGN. This reliable synthetic dataset consists of 11 modulations with varying SNR levels to train, validate and test our DL models. The simulation experiment was carried out in Python Notebook and virtual Google- Colab environment. The results show our proposed hybrid model outperforms the other DL models in terms of high classification accuracy, high probability of detection and less SE. The LSTM model also performed better than CNN and RNN models with its less probability of false alarm in identifying a signal feature. Although all the DL models proved their better performances, CNN was less accurate in identifying the signal feature particularly in low SNR ranges. 101p. Wed, 01 May 2024 00:00:00 GMT http://ir.haramaya.edu.et//hru/handle/123456789/7774 2024-05-01T00:00:00Z http://ir.haramaya.edu.et//hru/handle/123456789/7760 ANALYSIS OF WIDEBAND LOOP ELEMENT ANTENNA ARRAY FOR 5g MM-WAVE DEVICES. Soran Habtamu Eshete In recent years mobile operators have been challenged to deliver multimedia applications with higher data rates, low latency, and better quality of service of mobile communications. This has led to a large number of inventions and technological advancement in past decades which is the prime goals of the upcoming 5th generation (5G) mobile networks, but the challenging issue here is atmospheric conditions and interference by adjacent channels. These limitations can be overcome by designing directive antennas with high gain and stable radiation patterns to be used in a dense network at ultra-high throughputs. In this thesis, a compact, lightweight, low-cost, and easy install and incorporate mm wave printed square loop antenna with a perturbed ground plane is proposed. Firstly I designed a single element consisting of four rectangular square loops on the transmission line is designed. The squared loop antenna elements are arranged on top of each other by inserting of square lot in the ground plane which will achieve wideband resonance response. This design will definitely enable spatial diversity and minimize the effects of interference between adjacent channels. And also, this design will provide a dual beam within the desired or resonant frequency band, as we know there is high interference of adjacent channels at a high-frequency level so that the provided dual beam will minimize this adjacent channel interference. A brief literature review and comparison of this work with other published works is also presented. To evaluate the proposed design and looped array concept, a prototype is simulated for both, a single element, and an array. The simulation results show that the proposed antenna has a maximum gain and directivity of 4 dBi and 6.7 dBi for single element loop antenna, 10.6 dBi and 5.47 dBi for the proposed looped array antenna respectively. The VSWR and return loss values respectively found to be 1.516 and -12.47 dB for single element antenna, and 1.413 and -13.47 dB for looped array element antenna. The radiation efficiency for a single element antenna is -0.3809 and for looped element array antenna is - 0.3884. It is found that the measured results and the computed results are in good agreement. Therefore, we believe that these systems will find their applications within modern [mm] wave communication cellular devices. 84p. Fri, 01 Dec 2023 00:00:00 GMT http://ir.haramaya.edu.et//hru/handle/123456789/7760 2023-12-01T00:00:00Z http://ir.haramaya.edu.et//hru/handle/123456789/7752 PERFORMANCE ANALYSIS OF MULTI ELEMENT SQUARE FRAMED T SHAPE MMWAVE ANTENNA FOR 5G MOBILE DEVICES Anteneh Girma; Dr. Ritesh Pratap Singh; Mr. Uppala Suman Given the limited spectrum bands, mobile operators face challenges in delivering multimedia applications with higher data rates, low latency, and improved quality of service to a growing number of users. However, millimeter waves are susceptible to atmospheric conditions, leading to significant attenuation during adverse weather. Overcoming these challenges involves designing directive antennas with high gain and stable radiation patterns. This thesis aims to design, simulate, and compare single-element, and multi-element square-frame T shape mm-wave antennas operating at 28 GHz simulated using (CST), and their performance is evaluated. The comparison is based on simulated results of gain, efficiency, radiation pattern, directivity, VSWR, and return loss. This thesis aims to develop a better performing antenna operating at 28 GHz frequency. The simulation results show that the proposed antenna has a maximum gain and directivity of 3.15 dBi and 3.53 dBi for the single-element square-frame T-shaped antenna. The proposed 1x4 multi-element antenna achieves 10.5 dBi and 11.2 dBi, while the proposed 1x8 multi element reaches 13.8 dBi and 14 dBi, respectively. The VSWR and return loss values, respectively, were found to be 1.516 and -13.74 dB for a single-element antenna, 1.513 and -13.8 dB for a 1x4 multi-element antenna, and 1.516 and -46.90 dB for a 1x8 multi-element antenna. The radiation efficiency for a single-element antenna is -0.3809, for a 1x4 multi element square-framed T-shaped antenna it is -0.3884, with a compact size of 18.5 x 24 mm2 . And for a 1x8 multi-element square-framed T-shaped antenna is -0.2177 (95.11%) and the antenna size of 18.5 x 50mm2 . In this regard, the analysis shows that the proposed multi-element square frame T-shaped antenna is quite capable of achieving the highest performances and represents an obvious choice for 5G mobile applications. Moreover, to achieve an optimum design parameter, the multi-element antenna is also simulated with varying numbers of elements. The effect of these parameters on antenna performance is analyzed. 93p. Thu, 01 Feb 2024 00:00:00 GMT http://ir.haramaya.edu.et//hru/handle/123456789/7752 2024-02-01T00:00:00Z