Technoeconomic Evaluation of Cell Site Power Consumption Reduction Using Free Cooling Technique

Air Conditioning (AC) is the primary source of cooling in a typical Cell Site (CS) although it consumes a great deal of electricity. Excessive energy consumption due to air conditioning increases the operational expenses of telecommunication companies. Therefore, network operators have attempted a variety of techniques to reduce the exorbitant cost associated with a cell site’s high-power consumption. A Free Cooling System (FCS) is one such approach. Using computer modeling, this paper investigated how the FCS will function at a CS in Ghana. The study was conducted for 12 hours (from 6 pm to 6 am). A shelter with dimensions is 3 m × 2.47 m × 2.45 m (L × B × H) is used in the study, with three window positioning scenarios (different window heights) namely: an inlet window is 0.5 m high, and the outlet window is 1.5 m high, an inlet window and outlet window are both 1.0 m high and an inlet window is 1.5 m high, and the outlet window is 0.5 m high. The analysis revealed that a shelter with inlet and outlet windows at the same height has the most efficient heat dissipation potential. Furthermore, at a set temperature threshold of 25 °C, the annual percentage share for the two operating modes is approximately 67% for Air Conditioning (AC) and 33% for Free Cooling (FC) in 2020,  76% for AC and 24% for FC in 2021, and 61% for AC and 39% for FC in 2022. However, when the set temperature threshold is increased from 25 °Cto 30 °C, the annual percentage share is approximately 0.01% for AC and 99.9% for FC in 2020, 0% for AC and 100% for FC in 2021, and 1% for AC and 99% for FC in 2022, thus the proportion of free cooling increases as the set temperature threshold is raised. An indication of energy savings. It can be determined that when FC is operated at a set temperature threshold of 30 °C or higher, most cell sites in Ghana will save a considerable amount of energy

Adaptive channel estimation for sparse ultra wideband systems

Increased research in ultra wideband (UWB) systems in the last two decades has established it as a technology for high-speed, short-range applications. UWB also offers low power consumption, immunity to multipath fading, increased security, and low interference in multipath environments. Unfortunately, it is a great challenge to obtain accurate channel state information at the receiver side of UWB systems, especially in time-varying applications. Consequently, this research deals with the design of an adaptive channel estimation algorithm for sparse UWB systems. Using measurement data, this thesis considers the estimation of a long sparse multipath channel in a mobile UWB system. Recent advances in Compressive Sensing (CS) applications in signal processing make CS to be a legitimate candidate for processing sparse signals. Among the broad application areas of CS is channel estimation. Based on the objectives of the research, the contributions of this thesis are in three parts. Firstly, channel measurements usually provide accurate Channel Impulse Response (CIR), which helps to accurately model any channel behaviour. Thus, this thesis provides channel measurements in various mobile line-of-sight scenarios to precisely measure the efficacy of the proposed channel estimation algorithm. Secondly, traditional channel estimation algorithms like the Least Mean Square (LMS) and Normalised LMS (NLMS) algorithms do not consider the structural information of the channel. In addition, CS-based LMS and NLMS algorithms do not consider the use of the channel sparsity to control the algorithm performance. Therefore, this thesis also proposes a number of Sparseness-Controlled (SC) LMS and NLMS algorithms for estimating sparse UWB channels. Lastly, the thesis presents an analysis of the performance of the proposed estimators in terms of the Mean Square Error (MSE), steady-state excess MSE, convergence speed, robustness, and computational complexity. Simulation results show that unlike traditional algorithms, the proposed estimators perform better to improve the estimation of the CIR of sparse UWB channels. Even though, for all the scenarios considered, compared to the SC-l0-Norm NLMS (SC-L0-NLMS) algorithm, the SC-reweighted zero-attracting NLMS (SCRZA- NLMS) algorithm provides excellent performance, the SC-ZA-NLMS algorithm is less computationally complex than both and it performs in close proximity to both at higher SNR. For the sparse channel, when SNR is 30 dB, the SC-ZA-NLMS algorithm converges faster with better MSE of -38.2391 dB compared to the SC-RZALMS algorithm, which converges at -33.9805 dB. Therefore, the SC-ZA-NLMS algorithm is the most suitable for accurately estimating the sparse UWB channel

Neural Network-Based Optimisation of Sinusoidal PWM Controller for VSI-Driven BLDC Motor

Although increasing the number of switches increases the switch losses, most designed controllers focus on controlling an inverter circuit with more than six switches. The paper aims to address this issue that arises in implementation of the voltage source inverter (VSI) for brushless DC (BLDC) motors. It optimises the sinusoidal pulse width modulation (PWM) controller, minimising total harmonic distortion (THD) while keeping the VSI’s circuit at six switches to avoid increased switching losses. This was achieved by applying an artificial neural network (ANN) to generate a signal, which combines with the already existing reference and carrier signals. The addition of the new signal to the existing signals contributed to generating more pulses compared with the conventional sinusoidal PWM. Simulink was used to design the system and analyse its performance with the conventional and neutral point clamped (NPC) VSI systems. Results indicated that the proposed system performs better when controlled with an LCC filter. Compared with the control experiments, its output waveform has the lowest THD value, which is 6.04%. The switching losses of all the systems were also computed. Results from the computation indicated that the proposed system is capable of reducing the switching losses by 0.6 kW compared with the NPC VSI brushless DC motor (BLDCM) system. BLDCM speed was tested across various conditions; the results are reported in Section 5

Expressing facial structure and appearance information in frequency domain for face recognition

Beneath the uncertain primitive visual features of face images are the primitive intrinsic structural patterns (PISP) essential for characterizing a sample face discriminative attributes. It is on this basis that this paper presents a simple yet effective facial descriptor formed from derivatives of Gaussian and Gabor Wavelets. The new descriptor is coined local edge gradient Gabor magnitude (LEGGM) pattern. LEGGM first uncovers the PISP locked in every pixel through determining the pixel gradient in relation to its neighbors using the Derivatives of Gaussians. Then, the resulting output is embedded into the global appearance of the face which are further processed using Gabor wavelets in order to express its frequency characteristics. Additionally, we adopted various subspace models for dimensionality reduction in order to ascertain the best fit model for reporting a more effective representation of the LEGGM patterns. The proposed descriptor-based face recognition method is evaluated on three databases: Plastic surgery, LFW, and GT face databases. Through experiments, using a base classifier, the efficacy of the proposed method is demonstrated, especially in the case of plastic surgery database. The heterogeneous database, which we created to typify real-world scenario, show that the proposed method is to an extent insensitive to image formation factors with impressive recognition performances

Variable step-size l0-norm NLMS algorithm for sparse channel estimation

Wireless communication systems often require accurate channel state information (CSI) at the receiver side. Typically, the CSI can be obtained from channel impulse response (CIR). Measurements have shown that the CIR of wideband channels are often sparse. To this end, the least mean square (LMS)-based algorithms have been used to estimate the CIR at the receiver side, which unfortunately is not able to accurately estimate sparse channels. In this paper, we propose a variable step-size l0-norm normalized LMS (NLMS) algorithm. The step-size is varied with respect to changes in the mean square error (MSE), allowing the filter to track changes in the system as well as produce smaller steady-state errors. We present simulation results and compare the performance of the new algorithm with the invariable step-size NLMS (ISS-NLMS), variable step-size NLMS (VSS-NLMS) and the invariable step-size l0-NLMS (ISS-l0-NLMS) algorithms. The results show that the proposed algorithm improves the identification of sparse systems

Experimental characterization of an UWB channel in outdoor environment

An experimental characterization of the ultrawide-band (UWB) channel in an outdoor environment over the frequency range from 3.1 GHz to 5.3 GHz is presented in this paper. The measurements are taken in time domain and line-of-sight (LOS). The statistical model for the delay spread is characterized and there is no correlation between delay spread and transmitter receiver distance. Different statistical distributions for the delay spread are investigated. The reflective nature of this environment is shown in the Ricean K-factor

Characterization and parameterization of dynamic wireless channels over long duration using evolutionary channel parameters

The characterization and parameterization of processes that arise in many fields of science and technology are very crucial. Of particular importance are dynamic processes whose statistics are time-varying and are often modeled as stochastic processes. A typical example of such process is the wireless communication channel. Existing methods that are used to characterize and parameterize the dynamic stochastic wireless channel often consider short-term duration over which the channel statistics are invariant. Conversely, this paper presents the characterization of the dynamic wireless communication channel over a long-term duration where time/frequency channel realizations are obtained at sample intervals. To structure such channel realizations over a long duration, the idea of concatenating the 'instantaneous' channel realizations is presented. The resultant concatenated multivariable process is characterized using the concepts of process non-summability and piecewise separability. Based on these concepts, the second-order statistical parameterization of the concatenated stochastic process in both time and frequency domain is presented. The parameterization approach is based on fitting appropriate set of unit step functions that approximate the raw concatenated data using sets of evolutionary stationarity parameters. To illustrate the concepts developed in this paper, measurement-based experiments and analysis are presented and adaptively applied to improve wideband multicarrier system performance

UWB channel measurement and data transfer analysis for multiuser Infostation applications

In this paper, the results of the time dispersion parameters obtained from a set of channel measurements conducted in various environments that are typical of multiuser Infostation application scenarios are presented. The measurement procedure takes into account the practical scenarios typical of the positions and movements of the users in the particular Infostation network. To provide one with the knowledge of how much data can be downloaded by users over a given time and mobile speed, data transfer analysis for multiband orthogonal frequency division multiplexing (MB-OFDM) is presented. As expected, the rough estimate of simultaneous data transfer in a multiuser Infostation scenario indicates dependency of the percentage of download on the data size, number and speed of the users, and the elapse time

Channel measurement and time dispersion analysis for outdoor mobile ultrawideband environment

Ultrawideband (UWB) technology offers short-range high-data transmission rates. Most researchers in recent times have focused on indoor UWB channel measurements and in instances where outdoor cases were reported, they focused on static scenarios. This paper reports on mobile outdoor channel measurements typical of roadway and recreation park Infostation scenarios. It also chronicles the delay spread as well as channel stationarity analysis of the measurement data. We carried out measurements in the 3.1{5.3 GHz frequency range in various line-of-sight scenarios. The results of this research show that the delay spread values generally decrease with increasing mobile speed. Additionally, the degree of variation in the channel statistics show that systems designed with the obtained reference parameter values will perform well on average, but with low resource utilization