A Review on Cell Edge Interference Mitigation Techniques in 5G New Radio
Keywords:
Adjacent channel interference, Cell edge, Co-channel interference, Inter-symbol interference, 5G new radioAbstract
The overlapping of signals from neighboring edge towers is known as cell edge interference. Cell edge interference can be seen when a particular Base Transceiver Station (BTS) tries to hand over a mobile that it previously served to another BTS when the mobile tends to move out of its footprint. In 5G New Radio (NR), cell edge interference is a major challenge in terms of connectivity, due to poor signal quality, low network capacity and efficiency, network instability, and an increase in drop calls. The proposed algorithm, channel quality indicator-maximum likelihood detection, shows how to evaluate interference on tough channel error conditions concerning Channel State Information (CSI) error variance. The implementation of the algorithm gives an improved spectral efficiency in 5G NR as BER is kept to the barest minimum in the Rayleigh fading channel. In addition, the proposed algorithm, Channel Quality Indicator-Maximum Likelihood Detection (CQI-MLD) was used to decode information at both transmitter and receiver by selecting the best channel condition compared to other works which only concentrate on either transmitter or receiver. The existing maximum likelihood detection algorithm and other algorithms have the problem of high computational complexity and do not include adaptive modulation and channel parameters when handling interference problems in 5G NR. To overcome these challenges, we have to introduce a novel CQI-MLD algorithm that uses a channel quality indicator jointly with a maximum likelihood detection algorithm to mitigate interference at the cell edge of 5G NR. The research objectives focus on: Measuring and analyzing some metrics/study variables such as BER, SNR, and Throughput/Bandwidth and establishing their relationships using the Rayleigh fading model. To develop a channel quality indicator maximum likelihood detection algorithm based on channel state information for adaptive modulation on 5G new radio. To establish a mathematical relationship between cell interference and spectral efficiency in 5G new radio. To model and simulate discrete event systems using MATLAB.
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