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SummaryIn a huge multi‐input multi‐output orthogonal frequency divisions multiplexing (MIMO‐OFDM), an exact Channel State Information (CSI) is required to understand the system performance, which includes high spectrum together with energy efficiency. Using the OFDM, substantial numbers of pilots are distributed over a huge range of time–frequency sources to efficiently assess a vast range of channel coefficients in space along with the frequency domains, forfeiting spectral efficiency. Here, an optimised Channel Estimation (CE) framework aimed at the MU‐MIMO OFDM system is proposed utilising Hybrid Particle Swarm Optimisation–Gray Wolf Optimisation‐Leaky Least‐Mean‐Square (HPG‐LLMS) to attain high accurateness and secure data transmission (DT) with the aid of proposed Affine ECC. Herein, the video is considered as an input in the transmitter side and transformed into data frames and compressed with the help of ASCII‐based Huffman algorithm. Using Affine ECC, the compressed data are encrypted as well as modulated with the help of the MQPSK method. Then, transmute the modulated data into IFFT and incorporate the Guard Interval (GI) to the data. And then, over the Multi‐Path Channel (MPC), the symbols will be passed on to the receiver with the Additives White Gaussian Noise (AWGN). Execute the Inverse operations on the receiver side and centred on fuzzy centred priority scheduling algorithm (FPSA), sent the data to the user. Lastly, utilising HPG‐LLMS, the CE is performed.

Numerous wireless technologies have been integrated to provide 5th generation (5G) communication networks capable of delivering mission-critical applications and services. Despite considerable developments in a variety of supporting technologies, next-generation cellular deployments may still face severe bandwidth constraints as a result of inefficient radio spectrum use. To this end, a variety of appropriate frameworks have recently emerged that all aid mobile network operators (MNOs) in making effective use of the abundant frequency bands that other incumbents reserve for their own use. The proposed COCO model for Dynamic Spectrum Allocation (DSA) has 2 functionalities such as 1. Coherent PU-SU packet acceptance algorithm for Secondary User (SU) in DSA. 2. Consensus Algorithm for PU-SU Channel Reservation in DSA. To enable a 5G service with one-millisecond latency, interconnection ports between operators are expected to be required at every base station, which would have a significant influence on the topological structure of the core network. Additionally, just one radio network infrastructure would need to be created, which all operators would then be able to use. We allow change of PU SU characteristics to satisfy the needs of new services. These modifications are accomplished via the use of Coherent and Consensus Algorithms that regulate PU and SU through negotiation and allocation procedures. Our primary objective was to decrease interference, handoff latency, and the chance of blocking. In this paper, we describe our idea for employing COCO Model to address the issues of spectrum mobility, sharing, and handoff for Cognitive Radio Networks in 5G.