Power Budget Research Articles

A Low-Profile Circularly Polarized Millimeter-Wave Broadband Antenna Analyzed with a Link Budget for IoT Applications in an Indoor Scenario.

Broadband antennas with a low-profile generating circular polarization are always in demand for handheld/ portable devices as CP antennas counter multipath and misalignment issues. Therefore, a compact millimeter-wave antenna is proposed in this article. The proposed antenna structure comprises two circular rings and a circular patch at the center. This structure is further embedded with four equilateral triangles at a 90° orientation. The current entering the radiator is divided into left and right circular directions. The equilateral triangles provide the return path for current at the differential phase of ±90°, generating circular polarization. Structural development and analysis were initially performed through the characteristic mode theory. It showed that Modes 1 to 4 generated good impedance matching from 20 to 30 GHz and Modes 1 to 5, from 30 to 40 GHz. It also demonstrated the summation of orthogonal modes leading to circular polarization. The antenna-measured reflection coefficient |S11| > 10 dB was 19 GHz (23-42 GHz), and the axial ratio at -3 dB was 4.2 GHz (36-40.2 GHz). The antenna gain ranged from 4 to 6.2 dBi. The proposed antenna was tested for link margin estimation for IoT indoor conditions with line-of-sight (LOS) and non-line-of-sight (NLOS) conditions. The communication reliability with co- and cross-polarization was also studied under these conditions, and the results proved to be satisfactory.

Effects of some weather variables on the signal strength of Maloney FM radio, Nasarawa State, Nigeria

This study aims to assess the effects of atmospheric temperature, relative humidity, and atmospheric pressure on the signal strength of Maloney FM Radio, 95.9 MHz, Keffi, Nasarawa State. It is essential to measure the signal strength of the new radio station in relation with some parameters of weather to provide effective service delivery to the critical sectors and the entire populace. The research was conducted using the data of atmospheric temperature, atmospheric pressure, relative humidity, and the strength of the Maloney radio signal acquired from 6.00 a.m. to 6.00 p.m. daily at a 30 min interval, from January 2023 to June 2023, in Karshi, Abuja, a neighbouring town to Nasarawa state where the radio station is located. The data analysis involving cointegration and descriptive statistics of the effects of atmospheric variables on the radio signal strength was implemented using Eviews and Microsoft Excel Software. The results showed daily and monthly variations of the radio signal strength as well as the atmospheric temperature, atmospheric pressure and relative humidity. The variation is such that the lowest monthly signal strength was in June, probably due to higher rainfall in the area in June being the last month in this work (Jan.–Jun.) compared to other months which are dry season (January–March) or when the rain was just starting (April–May), in the study area. It was observed that atmospheric temperature and pressure negatively correlate with signal strength while relative humidity positively correlates with received signal strength in all the six months under study. The cointegration analysis also showed a long-term relationship between the radio signal strength and the atmospheric components, as the probability on the first row on the tables of both Trace Test and Maximum Eigenvalue methods were 0.0016 and 0.0008, which are less than the 5% (0.05) set critical value. In the same way, the critical value results on the same first row in both methods are smaller than the Trace statistics values. This implies that there is a long-term relationship between the atmospheric variables and the Maloney FM radio signal strength. These results will help mitigate the attenuation effect, and attendant signal loss of the radio station's signal strength. By proxy, the results will support the operations and regulations of spectrum management in the design of satellite communications and satellite microwave band specifications in Nigeria. In addition, the pre-determination of the radio station location will depend on this study's result analyses, considering that the effects of atmospheric temperature, pressure, and humidity conditions are inevitable. Governments, policymakers, stakeholders, and other relevant authorities should ensure the domestication of the study by providing the necessary research materials and facilities for wider studies. As regards the Maloney FM radio station, Keffi, studied in this work, there is no similar or related work done on it before now, hence, providing the detailed relationship between the signal strength of the radio station and some weather variables will go a long way in the improvement of the quality of signal transmission from Maloney radio station. The results when provided to the station, will enable the management to also evaluate if their set target of the station such as the radio horizon, radio signal coverage, and the link budget have been met.

Extrema-Triggered Conversion for Non-Stationary Signal Acquisition in Wireless Sensor Nodes

While wireless sensor node (WSNs) have proliferated with the rise of the Internet of Things (IoT), uniformly sampled analog–digital converters (ADCs) have traditionally reigned paramount in the signal processing pipeline. The large volume of data generated by uniformly sampled ADCs while capturing most real-world signals, which are highly non-stationary and sparse in information content, considerably strains the power budget of WSNs during data transmission. Given the pressing need for intelligent sampling, this work proposes an extrema pulse generator devised to trigger ADCs at significant signal extrema, thereby curbing the volume of data points collected and transmitted, and mitigating transmission power draw. After providing a comprehensive signal-theoretic rationale, we construct and experimentally validate these circuits on a system-on-chip field-programmable analog array in a 350 nm complementary metal-oxide-semiconductor (MOS) process. Operating within a power range of 4.3–12.3 µW (contingent on the input bandwidth requirements), the extrema pulse generator has proven to be capable of effectively sampling both synthetic and natural signals, achieving significant reductions in data volume and signal reconstruction error. Using a nonideality-resilient reconstruction algorithm, that we develop in this work, experimental comparisons between extrema and uniform sampling show that extrema sampling achieves an 18-fold lower normalized root mean square reconstruction error for a quadratic chirp signal, despite requiring 5-fold fewer sample points. Similar improvements in both the reconstruction error and effective sampling rate objectives are found experimentally for an electrocardiogram signal. Using both theoretical and experimental methods, this work demonstrates the potential of extrema-triggered systems for extending Pareto frontiers in modern, resource-constrained sensing scenarios.

H3DM: A High-bandwidth High-capacity Hybrid 3D Memory Design for GPUs

Graphics Processing Units (GPUs) are widely used for modern applications with huge data sizes. However, the performance benefit of GPUs is limited by their memory capacity and bandwidth. Although GPU vendors improve memory capacity and bandwidth using 3D memory technology (HBM), many important workloads with terabytes of data still cannot fit in the provided capacity and are bound by the provided bandwidth. With a limited GPU memory capacity, programmers should handle the data movement between GPU and host memories by themselves, causing a significant programming burden. To improve programming ease, GPUs use a unified address space with the host that allows over-subscribing GPU memory, but this approach is not effective in terms of performance once GPUs encounter memory page faults. Many recent works have tried to remedy capacity and bandwidth bottlenecks using dense non-volatile memories (NVMs) and true-3D stacking. However, these works mainly focus on one bottleneck or do not provide a scalable solution that fits future requirements. In this paper, we investigate true-3D stacking of dense, low-power, and refresh-free non-volatile phase change memory (PCM) on top of state-of-the-art GPU configurations to provide higher capacity and bandwidth within the available area and power budget. The higher density and lower power consumption of PCM provide higher capacity through integrating more cells in each 3D layer and enabling stacking more layers. However, we observe that stacking more than six layers of pure-PCM memory violates the thermal constraint and severely harms the performance and power efficiency due to its higher write latency and energy. Further, it degrades the lifetime of GPU to less than one year. Utilizing a hybrid architecture that leverages the benefits of both DRAM and PCM memories has been widely studied by prior proposals; however, true-3D integration of such a hybrid memory architecture especially on top of state-of-the-art powerful GPU architecture has not been investigated yet. We experimentally demonstrate that by covering 80% of write requests in DRAM and eliminating refresh overhead, true-3D stacking of eight 32GB layers of PCM along with two 8GB layers of DRAM is possible resulting in a total of 272GB memory capacity. Based on the explored design requirements, We propose a 3D high-bandwidth high-capacity hybrid memory (H3DM) system utilizing a hybrid-3D (H3D)-aware remapping scheme to reduce expensive PCM writes to under 20% while avoiding DRAM refresh overhead. H3DM improves the performance up to 291% compared to the baseline GPU architecture while remaining within only 3% of an ideal case with DRAM-like access latency, on average. Moreover, by increasing the dataset size above the baseline GPU memory space, H3DM improves performance and power up to 648% and 87% compared to the baseline GPU architecture since it avoids expensive data transfers through off-chip communication links.

An Analysis of Various Design Pathways Towards Multi-Terabit Photonic On-Interposer Interconnects

In the wake of dwindling Moore’s Law, to address the rapidly increasing complexity and cost of fabricating large-scale, monolithic systems-on-chip (SoCs), the industry has adopted dis-aggregation as a solution, wherein a large monolithic SoC is partitioned into multiple smaller chiplets that are then assembled into a large system-in-package (SiP) using advanced packaging substrates such as silicon interposer. For such interposer-based SiPs, there is a push to realize on-interposer inter-chiplet communication bandwidth of multi-Tb/s and end-to-end communication latency of no more than 10 ns. This push comes as the natural progression from some recent prior works on SiP design, and is driven by the proliferating bandwidth demand of modern data-intensive workloads. To meet this bandwidth and latency goal, prior works have focused on a potential solution of using the silicon photonic interposer (SiPhI) for integrating and interconnecting a large number of chiplets into an SiP. Despite the early promise, the existing designs of on-SiPhI interconnects still have to evolve by leaps and bounds to meet the goal of multi-Tb/s bandwidth. However, the possible design pathways, upon which such an evolution can be achieved, have not been explored in any prior works yet. In this paper, we have identified several design pathways that can help evolve on-SiPhI interconnects to achieve multi-Tb/s aggregate bandwidth. We perform an extensive link-level and system-level analysis in which we explore these design pathways in isolation and in different combinations of each other. From our link-level analysis, we have observed that the design pathways that simultaneously enhance the spectral range and optical power budget available for wavelength multiplexing can render aggregate bandwidth of up to 4 Tb/s per on-SiPhI link. We also show that such high-bandwidth on-SiPhI links can substantially improve the performance and energy-efficiency of the state-of-the-art CPU and GPU chiplets based SiPs.

Energy-efficient routing, power control and energy clustering for energy harvesting-enabled spectrum sharing IoT sensor networks

We investigate a spectrum sharing system that enables energy harvesting from distributed multi-antenna energy transmitter devices for primary dual-band device-to-device networks and secondary dual-band wireless sensor networks (WSNs), incorporating a multi-stage rectenna energy harvesting circuit model. We formulate a new multi-hop routing problem for network energy efficiency maximization of this system, which involves the interconnected tasks of WSN routing, controlling the transmit power of sensor nodes, and energy transmitter clustering, taking into account interference, power budget and rate constraints. To tackle these interconnected tasks effectively, we propose an integrated solution that includes both centralized and distributed routing schemes. Furthermore, the solution incorporates energy transmitter clustering schemes based on harvested power and channel gain. We provide an analysis of the computation complexity and signaling overhead for the proposed solution. Our simulation results demonstrate that the proposed routing and clustering schemes outperform their respective benchmark schemes, achieving significant performance gains.

Eciton: Very Low-power Recurrent Neural Network Accelerator for Real-time Inference at the Edge

This article presents Eciton, a very low-power recurrent neural network accelerator for time series data within low-power edge sensor nodes, achieving real-time inference with a power consumption of 17 mW under load. Eciton reduces memory and chip resource requirements via 8-bit quantization and hard sigmoid activation, allowing the accelerator as well as the recurrent neural network model parameters to fit in a low-cost, low-power Lattice iCE40 UP5K FPGA. We evaluate Eciton on multiple, established time-series classification applications including predictive maintenance of mechanical systems, sound classification, and intrusion detection for IoT nodes. Binary and multi-class classification edge models are explored, demonstrating that Eciton can adapt to a variety of deployable environments and remote use cases. Eciton demonstrates real-time processing at a very low power consumption with minimal loss of accuracy on multiple inference scenarios with differing characteristics, while achieving competitive power efficiency against the state-of-the-art of similar scale. We show that the addition of this accelerator actually reduces the power budget of the sensor node by reducing power-hungry wireless transmission. The resulting power budget of the sensor node is small enough to be powered by a power harvester, potentially allowing it to run indefinitely without a battery or periodic maintenance.

Optimizing throughput value through re-examining of 4G LTE infrastructure link budgets: A Case Study in Lubuk Kilangan

Broadband wireless access technology has taken the lead in communication technology development, enabling users to communicate with fast data speeds and extensive coverage.. Problems that frequently arise in mobile communication systems are the wide range of services and the level of network service quality. Thus, optimization is carried out to improve network quality in the Lubuk Kilangan area by using the drive test method to determine the quality of the network and bad spot areas and analyzed using terms discovery software. The reason behind the findings of this study is that the optimal link budget value for 4G LTE infrastructure in Lubuk Kilangan is higher than the current industry standard due to the unique characteristics of the area. According to the analysis and calculation of the link budget, power additions, and antenna tilting alterations were carried out for optimization. The power quality of the RSRP parameter increased from the fair (orange) area of 2.58 to 0.29. For the SINR parameter, For the SINR parameter, there was also an increase in quality at poor category locations in the KPI parameters (Range RSRP) locations from 0.08% to 0.05%, resulting in SINR bad spots decreasing. The proportion for Throughput after optimization remains the same, at 100%. Indicating that there had been a good increase in the coverage area, making the coverage in the Lubuk Kilangan area good. It is necessary to conduct a deeper study by comparing several types of antenna orientation, including tilt, depending on various factors such as the deployment scenario, coverage requirements, interference considerations, and the specific characteristics of picocells, femtocells, and repeaters. Future research could explore the impact of other factors, such as network topology and user behavior, on link budget optimization of 4G LTE infrastructure in different contexts

Explainable Machine Learning for LoRaWAN Link Budget Analysis and Modeling

This article explores the convergence of artificial intelligence and its challenges for precise planning of LoRa networks. It examines machine learning algorithms in conjunction with empirically collected data to develop an effective propagation model for LoRaWAN. We propose decoupling feature extraction and regression analysis, which facilitates training data requirements. In our comparative analysis, decision-tree-based gradient boosting achieved the lowest root-mean-squared error of 5.53 dBm. Another advantage of this model is its interpretability, which is exploited to qualitatively observe the governing propagation mechanisms. This approach provides a unique opportunity to practically understand the dependence of signal strength on other variables. The analysis revealed a 1.5 dBm sensitivity improvement as the LoR’s spreading factor changed from 7 to 12. The impact of clutter was revealed to be highly non-linear, with high attenuations as clutter increased until a certain point, after which it became ineffective. The outcome of this work leads to a more accurate estimation and a better understanding of the LoRa’s propagation. Consequently, mitigating the challenges associated with large-scale and dense LoRaWAN deployments, enabling improved link budget analysis, interference management, quality of service, scalability, and energy efficiency of Internet of Things networks.

Perancangan Jaringan Fiber To The Home Berbasis Gigabit Passive Optical Network Di Citra Garden Puri Cluste Denza

This research aims to design a GPON-based Fiber to The Home (FTTH) line in the Citra Garden Puri cluster Denza . The method used is to carry out field observations, by conducting surveys to determine the need for equipment that will be used in designing the route. After the survey is conducted, this project requires Google Earth Pro software to do the mapping of the spot that is used for the ODP and to create passages for the fiber. To make sure that all planning already meets the requirement, there are several calculationdone in this research such as; link loss budget, power link budget, power margin and risetime budget. The distance that were used in the calculation are calculated from the STO Cengkareng until the ONT on each customer. Based on the calculation, the result of the biggest loss for link loss budget are obtained from the upstream, in the amount of 22,0456 dB and the loss from downstream are equals to 21,5721 dB. The result that obtained for the upstream loss of power link budget are equals to -17,0456 dBm and -16,5172 dBm for downstream. The next calculation is power margin, from this project we obtained the lowest power margin for the upstream 6,9544 dB and 7,4288 dB for downstream. The last calculation obtained for this project is rise time budget, from the calculation the shortest data for the rise time budget upstream is 0,1001 ns and for the downstream is 0,1019 ns. Based on all the calculation, this project can be concluded as a success because all the calculation are between the boundary that is tolerated by PT Telkom.

Joint Trajectory Design and Resource Optimization in UAV-Assisted Caching-Enabled Networks with Finite Blocklength Transmissions

In this study, we design and analyze a reliability-oriented downlink wireless network assisted by unmanned aerial vehicles (UAVs). This network employs non-orthogonal multiple access (NOMA) transmission and finite blocklength (FBL) codes. In the network, ground user equipments (GUEs) request content from a remote base station (BS), and there are no direct connections between the BS and the GUEs. To address this, we employ a UAV with a limited caching capacity to assist the BS in completing the communication. The UAV can either request uncached content from the BS and then serve the GUEs or directly transmit cached content to the GUEs. In this paper, we first introduce the decoding error rate within the FBL regime and explore caching policies for the UAV. Subsequently, we formulate an optimization problem aimed at minimizing the average maximum end-to-end decoding error rate across all GUEs while considering the coding length and maximum UAV transmission power constraints. We propose a two-step alternating optimization scheme embedded within a deep deterministic policy gradient (DDPG) algorithm to jointly determine the UAV trajectory and transmission power allocations, as well as blocklength of downloading phase, and our numerical results show that the combined learning-optimization algorithm efficiently addresses the considered problem. In particular, it is shown that a well-designed UAV trajectory, relaxing the FBL constraint, increasing the cache size, and providing a higher UAV transmission power budget all lead to improved performance.

Multi-Ported GC-eDRAM Bitcell with Dynamic Port Configuration and Refresh Mechanism

Embedded memories occupy an increasingly dominant part of the area and power budgets of modern systems-on-chips (SoCs). Multi-ported embedded memories, commonly used by media SoCs and graphical processing units, occupy even more area and consume higher power due to larger memory bitcells. Gain-cell eDRAM is a high-density alternative for multi-ported operation with a small silicon footprint. However, conventional gain-cell memories have limited data availability, as they require periodic refresh operations to maintain their data. In this paper, we propose a novel multi-ported gain-cell design, which provides up-to N read ports and M independent write ports (NRMW). In addition, the proposed design features a configurable mode of operation, supporting a hidden refresh mechanism for improved memory availability, as well as a novel opportunistic refresh port approach. An 8kbit memory macro was implemented using a four-transistor bitcell with four ports (2R2W) in a 28 nm FD-SOI technology, offering up-to a 3× reduction in bitcell area compared to other dual-ported SRAM memory options, while also providing 100% memory availability, as opposed to conventional dynamic memories, which are hindered by limited availability.

Neighbor-based joint spatial division and multiplexing in massive MIMO: user scheduling and dynamic beam allocation

AbstractTwo-stage precoding schemes have been developed to reduce the channel estimation overhead in FDD systems. By integrating user scheduling into these schemes, it becomes possible to meet the quality-of-service requirements of high-density wireless communication systems, despite the limitations on spatial resources and transmit power budget. In this paper, we propose a user scheduling and dynamic beam allocation method for neighbor-based joint spatial division multiplexing (N-JSDM) transmission. The user scheduling problem is formulated as a 0–1 quadratic programming problem to maximize effective spectral efficiency (ESE) using directional channel properties. To address the complexity issue, convex relaxation and linearization methods are employed to transform the problem into a 0–1 mixed integer linear programming, and a dimensionality reduction method is introduced. The proposed user scheduling-aided N-JSDM scheme reduces downlink training length and feedback of channel state information. Additionally, a dynamic configuration form is used for pre-beamforming matrix design based on user distribution, outperforming conventional approaches. Simulation results demonstrate higher ESE achieved by the proposed scheme compared to previous methods.

A development of mobile application satellite link budget calculator – SATELEC

Link Budget is a calculation of gains and losses during transmission from transmitter to receiver in each communication system. In satellite communication, the main purpose of calculating link budget is to analyse the satellite system performance. One of the parameters to measure the satellite link performance is the Carrier to Noise ratio (C/N). There are a few satellite link calculators were developed using MATLAB/GUI and website. However, there are no available apps to help student to compare the calculated satellite link budget calculator for self-study. Therefore, a mobile apps called SATELEC was developed to calculate satellite link budget parameters. By using this satellite link budget calculator apps, all parameters such as Effective Isotropic Radiated Power (EIRP), Power Flux Density, Path Loss, Antenna Gain and Power Received can be calculated. After the value of power received is obtained, the value of Carrier to Noise ratio (C/N) can be determined by taking into account the noise in the communication. Results shows values obtained from the mobile is reliable after comparison with calculated value.

Glucose Fuel Cells: Electricity from Blood Sugar.

Harvesting energy from the human body is an area of growing interest. While several techniques have been explored, the focus in the field is converging on using Glucose Fuel Cells (GFCs) that use glucose oxidation reactions at an anode and oxygen reduction reactions (ORRs) at a cathode to create a voltage gradient that can be stored as power. To facilitate these reactions, catalysts are immobilized at an anode and cathode that result in electrochemistry that typically produces two electrons, a water molecule, and gluconic acid. There are two competing classes of these catalysts: enzymes, which use organic proteins, and abiotic options, which use reactive metals. Enzymatic catalysts show better specificity towards glucose, whereas abiotic options show superior operational stability. The most advanced enzymatic test showed a maximum power density of 119 μW/cm2 and an efficiency loss of 4% over 15 hours of operation. The best abiotic experiment resulted in 43 μW/cm2 and exhibited no signs of performance loss after 140 hours. Given the range of existing implantable devices' power budget from 10μW to 100mW and expected operational duration of 10 years or more, GFCs hold promise, but considerable advances need to be made to translate this technology to practical applications.

Modeling UAV swarm flight trajectories using Rapidly-exploring Random Tree algorithm

The paper presents the concept of determining the flight trajectory of an unmanned aerial vehicle (UAV) swarm that forms a flying ad-hoc network (FANET) for communication with each other. The FANET allows the swarm to follow a predetermined route between the starting and ending areas performing the reconnaissance task of the most significant area during the flight. The primary limitations of the FANET, which is used by the UAV swarm, are discussed. The radio link range between FANET nodes is based on a power budget and various propagation models. Whereas, for determining the UAV flight trajectories, we propose to use a heuristic algorithm based on the modified Rapidly-exploring Random Tree (RRT). This modification of the base RRT algorithm allows for planning the flight of several UAVs with meeting indicated restrictions, e.g., the minimum distance between individual UAVs ensuring communication between them at any time of the flight. Simulation tests are carried out for a swarm composed of several UAVs in environments with a random number of obstacles, corresponding to a real scenario for search and rescue operations.

Emulation and Testbed Prototyping of Laser Beam Propagation Characteristics through Atmospheric Turbulence for Optical Satellite Feeder Links

Two classical scenarios in space communications can be examined to evaluate the link performance of free space optical communications (FSO). These scenarios include the downlink and uplink between earth ground stations and near earth geostationary (GEO) satellites, as well as between the earth and spacecraft that are located a significant distance from the earth (i.e., one or more astronomical units (AU) away). Deep space is often defined as being more than 0.01 AU, or around 1,500,000 km, from Earth. In the first part of this analytical research, various practical system characteristics for optical lasers, telescopes, transmitters, receivers, and atmospheric disturbances, including absorption and scintillation, are taken into consideration. The simulation outcomes were compared to significant experimental data from DLR & JAXA’s OICETS/Kirari-Japan to validate the extended simulation model. Additionally, this work will propose a synthetic effects-based optical turbulence generator in order to deeply investigate atmospheric turbulence disturbances in free-space optical communication systems and support the advancement of artificial intelligence processing-based mitigation solutions. Worth mentioning, the initial outcomes and analytical comparisons demonstrate the preliminary viability of the simulation model for the link budget and scintillation estimation for FSO investigations, which can give deep insight into the development of the proposed testbed prototyping, machine learning-based laboratory measurement system, and enhancement possibility for FSO project design and execution for longand medium-term space mission planning.

BER comparisons of MIMO radar with uniform linear arrays

A smart antenna, which consists of several antenna elements makes a gain at the desired direction, makes nulls at the direction of interferers. In this article, the bit error rate is measured in different directions and distances, and the method of the minimum variance is used with the concept of the link budget when the weights of the multiple input multiple output (MIMO) radar are calculated with the number of N receiver elements and with the number of M transmitter elements. The less the number of interferers is, or using MIMO, the better the system is.

Datacenter Peak Power Management with Energy Storage Devices

Datacenters are warehouse-scale computing buildings that require high amounts of power. This results in prohibitively high electricity costs, increasing operational costs. Recently, researchers proposed using energy storage devices (ESDs) in datacenters to reduce their maximum power demand. ESDs enable datacenters to set smaller power budgets because they can provide additional energy when the demand is expected to be higher than this budget. This paper leverages a detailed survey of previous studies and analyzes the economical feasibility of this methodology from three different perspectives. We first compare different ESDs based on their ability to manage datacenter peak power. Then, we demonstrate that peak shaving benefits might differ due to datacenter usage and ownership. Finally, we analyze the option where datacenters participate in electric utility programs with their ESDs to obtain additional savings.

DEVELOPMENT OF PARAMETERIZED MODEL OF LOGIC ELEMENTS AT CLOCK TREE SYNTHESIS

Clock synthesis, routing optimization, placement and logic optimization are the three primary phases of physical design implementation. Since clock network synthesis uses at least 30% of the entire power budget, it is one of the crucial steps. Power consumption for high-performance blocks can reach 50% of the entire power. Not only would a high-quality clock tree will fix timing violations, but it will also minimize power usage and routing resource use. A new neural network based parameterized model is proposed in this paper, which can be used to obtain not only the list of logic elements, but it also can predict the circuits timing behaviour. Different ICs using SAED 14 and 32 nm technologies are designed using the proposed method.