Massive Multiple-Input Multiple-Output (MIMO) answers the exponentially increasing demand for comprehensive fixed broadband and broadcast wireless communication services. Massive MIMO is a pivotal technology in the 5G...
Massive Multiple-Input Multiple-Output (MIMO) answers the exponentially increasing demand for comprehensive fixed broadband and broadcast wireless communication services. Massive MIMO is a pivotal technology in the 5G and beyond (5GaB) wireless communication systems. This paper compares linear precoding algorithms such as Minimum Mean Square Error (MMSE), Neumann Series Approximation (NSA) with nonlinear precoders such as Tomlinson-Harashima Precoder (THP), and Lattice Reduction (LR) algorithm, the Lenstra-Lenstra-Lov'asz (LLL) precoder. The comparison was conducted using Bit-Error Rate (BER) and signal-to-noise ratio (SNR) performance measures. Simulated results prove that nonlinear precoders outperform linear precoding in high SNR regions.
The proposed project uses a Raspberry Pi microcontroller to prevent crop losses caused by animals like dog, wild pigs, and monkeys. These animals pose a significant threat to farmers, leading to financial losses. This...
详细信息
Frequency response services have become more important than ever in an increasingly inertia-less power system. A promising way to provide such services in a photovoltaic (PV) system is by hybridizing with supercapacit...
详细信息
As fundamental components of programmable logic circuits, Lookup Table (LUT) circuits enable the implementation of arbitrary combinational logic. The volatility, standby power dissipation, and propagation delay of LUT...
详细信息
A large volume of image data has been increasingly generated in every area, and it is necessary to keep confidential. Multiple image encryption is a promising solution for massive image data. Existing algorithms allow...
详细信息
With the modernization of cities, the concept of the Internet of Things (IoT) is gaining popularity and becoming a vital source of smart developments. An added advantage of solar energy systems, IoT applications enabl...
详细信息
In this paper, we investigate the issues of real-time sensor scheduling and state estimator design within large-scale sensor network systems. Specifically, data redundancy sometimes occurs in large-scale sensor arrays...
详细信息
Throughput analysis for successive interference cancellation-based two-device slotted ALOHA with feedback is studied over Nakagami-m fading channels. Explicit expressions for the state transition probabilities are der...
详细信息
An efficient caching can be achieved by predicting the popularity of the files accurately. It is well known that the popularity of a file can be nudged by using recommendation, and hence it can be estimated accurately...
详细信息
The Industrial Internet of Things has emerged as an essential tool for building Industry 4.0 and Industry 5.0 where timely information can be retrieved from different scenarios. These devices are highly vulnerable to ...
详细信息
ISBN:
(数字)9798350372816
ISBN:
(纸本)9798350372823
The Industrial Internet of Things has emerged as an essential tool for building Industry 4.0 and Industry 5.0 where timely information can be retrieved from different scenarios. These devices are highly vulnerable to cyberattacks as heterogeneous types of devices can be used in the infrastructure that may or may not be equipped with standardized security protocols. Artificial intelligence-based methodologies can effectively identify these types of attacks on a prior basis for taking mitigation action. This method raises concerns about data privacy as building a machine learning-based method requires the sharing of network data that can reveal the actual information of industries. The proposed Federated Learning based framework handles this concern by preserving each device’s critical data by utilizing the benefits of the decentralized model aggregation. This research work presents the comparison of the proposed framework on the CICIoT2023 dataset with federated averaging and federated proximal techniques for achieving a global model. The performance evaluation of these two aggregation techniques is performed based on metrics of accuracy, loss, precision and recall. The results prove that the federated proximal method achieves higher accuracy in comparison to the federated averaging method.
暂无评论