Abstract-The ever-growing need for high data rate, bandwidth efficiency, reliability, less complexity and less power consumption in our communication systems is on the increase. Modern techniques have to be developed and put in place to meet these requirements. Research has shown, that compared to conventional Single Input Single Output (SISO) systems, MultipleInput Single Output (MISO), and Multiple-Input MultipleOutput (MIMO) can actually increase the data rate of a communication system, without actually requiring more transmit power or bandwidth. This paper aims at the investigation of the existing channel estimation techniques. Based on the pilot arrangement, the block type and comb type are compared, employing the Least Square estimation (L.S) and Minimum Mean Squared Error (MMSE) estimators. Pilots occupy bandwidth, minimizing the number of pilots used to estimate the channel, in order to allow for more bandwidth utilization for data transmission, without compromising the accuracy of the estimates is taken into consideration. Various channel interpolation techniques and pilot-data insertion ratio are investigated, simulated and compared, to determine the best performance technique with less complexity and minimum power consumption. As performance measures, the Mean Squared Error (MSE) and Bit Error Rate (BER) as a function of Signal to Noise power Ratio (SNR) of the different channel estimation techniques are plotted, in order to identify the technique with the most optimal performance. The complexity and energy efficiency of the techniques are also investigated. The system modelling and simulations are carried out using Matlab simulation package. The MIMO gives the optimum performance, followed by the MISO and SISO. This is as a result of the diversity and multiplexing gain experienced in the multiple antenna techniques using the STBC.Keywords-Multiple-input multiple-output (MIMO), Multipleinput Single output (MISO), Single input Single output (SISO), Least Square estimation (L.S), Minimum Mean Squared Error (MMSE) estimators, Mean squared error (MSE) and Bit error rate (BER)

<p>Increasing requirements for scalability and elasticity of data storage for web applications has made Not Structured Query Language NoSQL databases more invaluable to web developers. One of such NoSQL Database solutions is Redis. A budding alternative to Redis database is the SSDB database, which is also a key-value store but is disk-based. The aim of this research work is to benchmark both databases (Redis and SSDB) using the Yahoo Cloud Serving Benchmark (YCSB). YCSB is a platform that has been used to compare and benchmark similar NoSQL database systems. Both databases were given variable workloads to identify the throughput of all given operations. The results obtained shows that SSDB gives a better throughput for majority of operations to Redis’s performance.</p>

This study shows how the network performance of a flat switch network in the main library complex of Ambrose Ali University (AAU), Ekpoma can greatly be improved by logical segmentation. A survey of the flat switch network of the library complex was carried out to ascertain the physical and logical topology of the network and the number of hosts and network devices available. The kind of traffic transmitted over the network was also considered. Riverbed Modeler Academic Edition was used to simulate two replicas of the library network. One of the simulated networks was logically segmented by implementing Virtual Local Area Network (VLAN). Statistics like traffic dropped, traffic forwarded, traffic received, broadcast traffic dropped and traffic sent in bits/sec or packets/sec were collected from both simulations and the results were analyzed and compared. The results from the simulations showed that the application of VLAN immensely enhanced the network performance by about 75%(depending on the size of the network) because the logical segmentation increased the number of broadcast domain while reducing each of the broadcast size. This further implied that poor network design and large broadcast domain in a network, gravely affect the performance of a network.

The two main aims of deploying multiple input multiple out (MIMO) are to achieve spatial diversity (improves channel reliability) and spatial multiplexing (increase data throughput). Achieving both in a given system is impossible for now, and a trade-off has to be reached as they may be conflicting objectives. The basic concept of multiplexing: divide (multiplex) transmit a data stream several branches and transmit via several (independent) channels. In this paper, we focused mainly on achieving spatial multiplexing by modeling the channel using the diagonal Bell Labs space time scheme (D-BLAST) and the vertical Bell Labs space time architecture (V-BLAST) Matlab simulations results were a lso given to further compare the advantages of spatial multiplexing.

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