Fifth generation (5G) is a recent wireless communication technology in mobile networks. The key parameters of 5G are enhanced coverage, ultra reliable low latency, high data rates, massive connectivity and better support to mobility. Enhanced coverage is one of the major issues in the 5G and beyond 5G networks, which will be affecting the overall system performance and end user experience. The increasing number of base stations may increase the coverage but it leads to interference between the cell edge users, which in turn impacts the coverage. Therefore, enhanced coverage is one of the future challenging issues in cellular networks. In this survey, coverage enhancement techniques are explored to improve the overall system performance, throughput, coverage capacity, spectral efficiency, outage probability, data rates, and latency. The main aim of this article is to highlight the recent developments and deployments made towards the enhanced network coverage and to discuss its future research challenges.

Cooperative spectrum sensing in cognitive radio network consumes a large amount of energy during spectrum sensing and reporting. An energy‐efficient reporting scheme called the reduced energy consumption scheme for reporting has been proposed to reduce energy consumption. In this scheme, all secondary users will sense the channel and make a local decision about the spectrum. All these local decisions are forwarded to a common node known as the fusion centre. This counts the presence or absence of the primary user based on the secondary user's local decisions. Whenever the counters count is greater than or equal to the threshold then the fusion centre sends a stop reporting feedback signal to the secondary users. In this way the energy consumption is reduced by diminishing the reporting secondary users and the energy efficiency is improved. The simulation and numerical results show a notable improvement in the energy efficiency of a reduced spectrum sensing scheme compared to the conventional spectrum sensing method.

The signal strength in 5G mobile communication systems is significantly influenced by the surroundings, with key factors including the path difference, operating frequency, and obstructions at specific locations. Consequently, planning a communication system that can deliver improved signal strength becomes highly challenging. To address this issue, indoor path loss models are employed to estimate signal loss in different environments, frequencies, and distances. This paper introduces an intelligent multi-objective genetic algorithm aimed at enhancing path loss and received signal power. A comparative analysis is conducted to evaluate the performance of the proposed intelligent optimization algorithm against the traditional approach. The path loss and received power of various scenarios are estimated using various path loss models. The 5GCM indoor officce, 5GCM InH shopping mall, 3GPP TR 38.91 InH office, mmMAGIC InH office, METIS InH shopping mall, and IEEE 802.11 ad InH office indoor path loss models estimates the path loss of 62.37 dB, 62.15 dB, 63.12 dB, 50 dB, 55.18 dB, and 52.89 dB in traditional approach and 36.87 dB, 35.86 dB, 36.84 dB, 68.80 dB, 36.23 dB and 33.94 dB using GA approach and received powers of \(-12.17~dBm, -11.37~dBm, -12.17~dBm, -5.80~dBm,\) \(-12.24~dBm\) and \(-8.68~dBm\) in traditional approach and 26.13 dBm, 27.14 dBm, 26.15 dBm, \(-5.80~dBm\), 26.75 dBm and 29.05 dBm using GA approach repectively. The 5GCM and 3GPP models produces the path loss difference above 25 dB and mmMAGIC, METIS and IEEE models produces a path loss below 19 dB. Except mmMAGIC model, all models produces the recceiver power difference above 37 dBm. Therefore, the highest path loss difference of 26 dB is observed in 5GCM InH shopping mall model and the highest reccieved power difference of 39.01 dBm is observed in METIS InH shopping mall model. The results clearly demonstrate that the proposed intelligent optimization approach outperforms the traditional approach across various indoor scenarios.

Background: In cognitive radio networks, spectrum sensing plays an important role in identifying the underutilized spectrum bands. Conventional spectrum sensing using energy detection method uses single detection threshold, which degrades the detection performance. Method: Therefore double detection threshold has been proposed for spectrum sensing in the literature to improve the detection performance, but the performance depends on the region between two thresholds termed as confusion state. Hence to improve the overall detection performance new re-sensing scheme has been proposed in this paper by varying the difference between thresholds by an improvement factor K. Results: The proposed method improves the detection performance compared to the single threshold method and double threshold method. Conclusion: Simulation results show that the proposed method operates better than the single threshold energy detection method and improves the detection performance at low signal to noise ratios.

In cognitive radio networks spectrum sensing plays a vital role to identify the presence or absence of the primary user. In conventional spectrum sensing one secondary user will make a final decision regarding the availability of licensed spectrum. But Secondary user fail to make a correct detection about the presence of the primary user if he is in fading environment and it causes interference to the licensed users. Therefore to avoid interference to the licensed users and to make correct detection, number of samples is increased, Which increases the probability of detection. In this paper the optimization of samples is proposed to reduce the system overhead and also to increase the propagation time. Simulation results show the optimized value of samples for a given probability of false alarm and also the variation of probability of detection with optimized samples and false alarm is shown in the results. ABSTRAK: Dalam rangkaian radio kognitif, penginderaan spektrum memainkan peranan penting untuk mengenal pasti kehadiran atau ketiadaan pengguna utama. Dalam penginderaan spektrum konvensional, seorang pengguna sekunder akan membuat keputusan akhir mengenai ketersediaan spektrum berlesen. Tetapi pengguna Sekunder gagal membuat pengesanan yang betul mengenai kehadiran pengguna utama jika dia berada dalam persekitaran yang pudar dan menyebabkan gangguan kepada pengguna yang berlesen. Oleh itu untuk mengelakkan gangguan kepada pengguna berlesen dan membuat pengesanan yang betul, jumlah sampel meningkat, yang meningkatkan kemungkinan pengesanan. Dalam makalah ini pengoptimuman sampel dicadangkan untuk mengurangi overhead sistem dan juga untuk meningkatkan waktu penyebaran. Hasil simulasi menunjukkan nilai sampel yang dioptimumkan untuk kebarangkalian penggera palsu dan juga variasi kebarangkalian pengesanan dengan sampel yang dioptimumkan dan penggera palsu ditunjukkan dalam hasil.