The noise that associated with TV images is considered to be a very important problem that complicates the developments of these systems. Because of that, it makes the interpretation and analysis of informative images a very difficult process, and lessens their advantages. The most common type of these images are TV images transmitted by antenna work with (VHF, UHF) frequency and Satellite Transmission. Because TV images move through a complicated system in generating the TV or video signal, coding them, transmitting them, and receiving them by decoding and passing with different sets until appearing on screen. This will lead to a loose and fraud for a part of the information sent in the wave. As a result, it will be affected by an additive noise (Gaussian noise) which leads to deforming and destroying the quality of these images. This research aimed at studying the effect of the noise influence of this noise on edge as well as study of the relation between the statistical operators that include the mean and standard deviation (µ, σ) of edge’s regions for the components RGB and illumination component L as a function of time and as a function of antenna rotation. As well as we studied the relation between (µ, σ) and signal to noise ratio SNR for the cross correlation of edge's regions and for a homogeneous regions as well as for image as a whole once as a function of time and the other as a function of the angle of antenna rotation as in the first.
In the fifth-generation (5G) era and future, mobile internet and internet of things (IoT) are the driving forces for mobile communications’ development. The three main 5G usage scenarios: enhanced mobile broadband (eMBB), massive machine-type communication (mMTC), and ultra-reliable and low-latency communications (URLLC), require improvement in throughput, reliability, and latency as compared with the previous fourth generation (4G) system. In this paper, an investigation is done on the coding part of the wireless communication systems. Two channel coding types; low-density parity-check (LDPC) code which is used as the coding scheme for data transmission, and Polar code which is utilized for control in 5G are discussed. Moreover, simulations are performed to assess their performance. The simulation results revealed the superiority of polar code for transmitting short information messages and LDPC for transmitting long data messages. The use of LDPC and polar codes in 5G communication systems is justified by their ability to accommodate a wide range of data lengths and code rates, as well as their good bit error rate (BER) performance. Furthermore, the effect of the number of iterations on the BER performance of LDPC code and different decoding algorithms of polar code are considered.
Channel coding technique is a fundamental building block in any modern communication system to realize reliable, fast, and secure data transmission. At the same time, it is a challenging and crucial task, as the data transmission happens in a channel where noise, fading, and other impairments are present. The Low-Density Parity-Check (LDPC) codes give substantial results close to the Shannon limit when the complexity and processing delay time are unlimited. In this paper, the performance of the LDPC decoding with four algorithms was investigated. The investigated four algorithms were Belief Propagation (BP), Layered Belief Propagation (LBP), Normalized min-sum (NMS), and Offset min-sum (OMS). These algorithms were examined for code rates ranging from 1/3 to 9/10 and message block lengths (64, 512, 1024, and 5120) bits. The simulation results revealed the flexibility of these decoders in supporting these code rates and block lengths, which enables their usage in a wide range of applications and scenarios for fifth-generation (5G) wireless communication. In addition, the effect of the maximum number of decoding iterations on the error correction performance was investigated, and a gain of 5.6 dB can be obtained by using 32 decoding iterations at BER=2*10-3 instead of one decoding iteration. The results showed that the decoders performed better for longer message blocks than for short message blocks, and less power was required for transmitting longer messages. Finally, the comparison results of their performance in terms of bit error rate (BER) under the same conditions showed a gain of 0.8 dB using LBP at BER= 10-5 compared with the NMS decoding algorithm.
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