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The dramatically growing mobile communication industry necessitates the demand for the speedy and error-free connectivity at considerably low cost for the billions of users. This is made possible only through the technological advancements that replace the current 4G wireless systems by 5G. Massive MIMO is the key technology used in 5G that offers spectral efficiency of up to 3 times and throughput of up to 10 times the current 4G. The additional antennas used in massive MIMO systems help in many ways but lack in complexity. Hence, in this paper, we propose two design methodologies to reduce the complexity of massive MIMO systems. The first one is the design of low-complexity hybrid precoder based on Zero-Forcing (ZF) precoding algorithm and Neumann series approximation. The second one is the design of flexible, environment friendly, simple 128-element antenna array at the frequency of 2.4 GHz using inkjet printing technology. The substrate used for printing is the “glossy paper” with dielectric constant of 2.31, and the ink used is silver nanoparticle ink with conductivity of 35,700,000 s/m. The element used for the formation of array is the z-shaped coplanar waveguide (CPW) monopole antenna. The performance of the proposed designs is evaluated in terms of probability of error for the hybrid precoding algorithm and radiation characteristics like gain, directivity, and return loss for the printed antenna design.

Wireless Sensor Network (WSN) encompasses several tiny devices termed as Sensor Nodes (SN) that have restriction in resources with lower energy, memory, together with computation. Data Aggregation (DA) is required to optimize WSN for secured data transmission at Cluster Head (CH) together with Base Station (BS). With regard to the Energy Efficiency (EE) along with the privacy conservation requirements of WSN in big-data processing and aggregation, this paper proposed Diversity centered Adaptive Moth-Flame Optimization (DAMFO) for Optimal Path Selection (OPS) and DA in WSN. In the proposed work, initially, the Trust Evaluation (TE) process is performed. The Pompeiu Distance- centered Fuzzy C-Means (PDFCM) is employed for Cluster Formation (CF) in addition to Cluster Head Selection (CHS) and then DAMFO algorithm chooses the optimal path to gather the data together with cluster centroids. The DHECC algorithm then generates keys and encrypts the aggregated data. The encrypted data is finally passed on to the BS. The experimentation outcomes exhibited that the proposed algorithm outweighs the traditional methods with respect to Energy Consumption (EC) 6.35 J, Packet Delivery Ratio (PDR) of 93%, Throughput of 0.956 bps, end-to-end delay 6.547 s, together with a lifetime of networks. Additionally, the proposed system exhibits the best Security Level (SL) of 94.2% amid the transmission. [ABSTRACT FROM AUTHOR]

The design of cluster-based routing protocols is necessary for Wireless Sensor Networks (WSN). But, due to the lack of features, the traditional methods face issues, especially on unbalanced energy consumption of routing protocol. This work focuses on enhancing the security and energy efficiency of the system by proposing Energy Efficient Based Secure Routing Protocol (EESRP) which integrates trust management, optimization algorithm and key management. Initially, the locations of the deployed nodes are calculated along with their trust values. Here, packet transfer is maintained securely by compiling a Digital Signature Algorithm (DSA) and Elliptic Curve Cryptography (ECC) approach. Finally, trust, key, location and energy parameters are incorporated in Particle Swarm Optimization (PSO) and meta-heuristic based Harmony Search (HS) method to find the secure shortest path. Our results show that the energy consumption of the proposed approach is 1.06mJ during the transmission mode, and 8.69 mJ during the receive mode which is lower than the existing approaches. The average throughput and the average PDR for the attacks are also high with 72 and 62.5 respectively. The significance of the research is its ability to improve the performance metrics of existing work by combining the advantages of different approaches. After simulating the model, the results have been validated with conventional methods with respect to the number of live nodes, energy efficiency, network lifetime, packet loss rate, scalability, and energy consumption of routing protocol. [ABSTRACT FROM AUTHOR]