Massive multiple-input multiple-output (massive-MIMO) is a promising technology for next generation wireless communications systems due to its capability to increase the data rate and meet the enormous ongoing data traffic explosion. However, in non-reciprocal channels, such as those encountered in frequency division duplex (FDD) systems, channel state information (CSI) estimation using downlink (DL) training sequence is to date very challenging issue, especially when the channel exhibits a shorter coherence time. In particular, the availability of sufficiently accurate CSI at the base transceiver station (BTS) allows an efficient precoding design in the DL transmission to be achieved, and thus, reliable communication systems can be obtaine
... Show MoreIn this work, the performance of the receiver in a quantum cryptography system based on BB84 protocol is scaled by calculating the Quantum Bit Error Rate (QBER) of the receiver. To apply this performance test, an optical setup was arranged and a circuit was designed and implemented to calculate the QBER. This electronic circuit is used to calculate the number of counts per second generated by the avalanche photodiodes set in the receiver. The calculated counts per second are used to calculate the QBER for the receiver that gives an indication for the performance of the receiver. Minimum QBER, 6%, was obtained with avalanche photodiode excess voltage equals to 2V and laser diode power of 3.16 nW at avalanche photodiode temperature of -10
... Show MoreThis paper describes a new proposed structure of the Proportional Integral Derivative (PID) controller based on modified Elman neural network for the DC-DC buck converter system which is used in battery operation of the portable devices. The Dolphin Echolocation Optimization (DEO) algorithm is considered as a perfect on-line tuning technique therefore, it was used for tuning and obtaining the parameters of the modified Elman neural-PID controller to avoid the local minimum problem during learning the proposed controller. Simulation results show that the best weight parameters of the proposed controller, which are taken from the DEO, lead to find the best action and unsaturated state that will stabilize the Buck converter system performan
... Show MoreThe majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value <0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, tempe
n this paper, we formulate three mathematical models using spline functions, such as linear, quadratic and cubic functions to approximate the mathematical model for incoming water to some dams. We will implement this model on dams of both rivers; dams on the Tigris are Mosul and Amara while dams on the Euphrates are Hadetha and Al-Hindya.
The performance of a vapor compression refrigeration system (VCRS)-based residential air conditioner operating in a high-ambient temperature (HAT) country was investigated using six zero-ODP (ozone depletion potential) refrigerants as replacements to R22. The non-flammable alternative refrigerants considered in the present research were R134a, R404A, R407C, R410A, R448A, and R507A. Using the basic conservation laws, the VCRS was modeled during steady-state operation and solved using engineering equation solver (EES) software. Coefficient of performance (COP), pressures and temperatures at compressor suction and discharge, Global Warming Potential (GWP), critical pressure and temperature, compressor