The growing importance of energy efficient networks with high data rate requirements is a major concern for network operators. Services provided by the network operators are required to ensure the consumers’ satisfaction. For the providing of high data rates with good signal quality, small cells are deployed. But these cells can increase energy consumption if not equipped with some intelligent power saving or distribution mechanism. In this paper, a previously tested small cell sleeping mode scheme is compared with the new proposed scheme of reducing power in low or normal traffic hours. This scheme provided 13-15% increase in energy efficiency. The new scheme resulted to beneficial simulated outcomes and can be applied to overcome the energy consumption issue.

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In the current era of exponentially growing demand for user connectivity, spectral efficiency (SE), and high throughput, the performance goals have become even more challenging in ultra-dense 5G networks. The conventional orthogonal frequency division multiple access (OFDMA) tech-niques are mature but have not proven sufficient to address the growing user demand for high data rates and increased capacity. Therefore, to achieve an improved throughput in an ultra-dense 5G network with an expanded network capacity, the unified non-orthogonal multiple access (NOMA) technique is considered to be a more promising and effective solution. Throughput can be im-proved by implementing PD-NOMA, as the interference is managed with the successive inter-ference cancellation (SIC) technique, but the issue of increased complexity and capacity with compromised data rate persists. This study implements the clustered PD-NOMA algorithm to enhance user association and network performance by managing the users in clusters with fewer users per cluster with the implementation of the cooperative PD-NOMA within the clusters. In this study, we enhanced the user association in a network and ultimately improved the throughput, sum rate, and system capacity in an ultra-dense heterogeneous network (HetNet). By imple-menting the proposed clustered PD-NOMA scheme, the system throughput has improved by 23% when compared to the unified PD-NOMA scheme and 65% when compared to the OFDMA scheme with a varied number of randomly deployed users, along with an improvement in system capacity of 8% as compared to the unified PD-NOMA and almost 80% as compared to the conventional OFDMA scheme in a randomly deployed ultra-dense multi-tier heterogeneous network. Thus, we improved the network performance with the proposed algorithm and achieved increased capacity, throughput, and sum rate by outperforming the unified PD-NOMA scheme in an ultra-dense heterogeneous network.

The unprecedented acceleration in wireless industry strongly compels wireless operators to increase their data network throughput, capacity and coverage on emergent basis. In upcoming 5G heterogeneous networks inclusion of low power nodes (LPNs) like pico cells and femto cells for increasing network’s throughput, capacity and coverage are getting momentum. Addition of LPNs in such a massive level will eventually make a network populated in terms of base stations (BSs).The dense deployments of BSs will leads towards high operating expenditures (Op-Ex), capital expenditure (Cap-Ex) and most importantly high energy consumption in future generation networks. Recognizing theses networks issues this research work investigates data throughput and energy efficiency of 5G multi-tier heterogeneous network. The network is modeled using tools from stochastic geometry. Monte Carlo results confirmed that rational deployment of LPNs can contribute towards increased throughput along with better energy efficiency of overall network.

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