Channel Measurement and Noise Estimation in FBMC/OQAM-Based IoT Networks

Channel measurement plays an important role in the emerging 5G-enabled Internet of Things (IoT) networks, which reflects the channel quality and link reliability. In this paper, we address the channel measurement for link reliability evaluation in filter-bank multicarrier with offset quadrature amplitude modulation- (FBMC/OQAM-) based IoT network, which is considered as a promising technique for future wireless communications. However, resulting from the imaginary interference and the noise correlation among subcarriers in FBMC/OQAM, the existing frequency correlation method cannot be directly applied in the FBMC/OQAM-based IoT network. In this study, the concept of the block repetition is applied in FBMC/OQAM. It is demonstrated that the noises among subcarriers are independent by the block repetition and linear combination, instead of correlated. On this basis, the classical frequency correlation method can be applied to achieve the channel measurement. Then, we also propose an advanced frequency correlation method to improve the accuracy of the channel measurement, by assuming channel frequency responses to be quasi-invariant for several successive subcarriers. Simulations are conducted to validate the proposed schemes.

An Improved Vanet Clustering and Channel Quality using Movc and Weighted Probability

VANET offers a vast range of application which will make travel experience safe. The concept behind VANET is quite simple which incorporates wireless communication and capable of sharing data; the vehicles are turned for offering network to provide services which can be used in the home or office networks. VANET network nodes are move in-network with higher velocity in the network. This higher mobility of vehicles causes increased resource and energy utilization which causes failure of nodes. Resource and energy consumption is higher for inefficient constructed clustering for VANET. Also, vehicle mobility causes several obstacles in data transmission this causes degraded channel quality. data transmission this causes degraded channel quality. In this paper concentrated on improving channel quality and energy efficiency in the network. Initially, performed efficient clustering through middle-order based cluster head (CH) election (MOVC) mechanism. Through effective CH election resource and energy utilization is limited. In the next stage, channel quality is improved by the proposed weighted probability approach for effective data transmission between vehicles in the VANET network. The weighted probability approach estimates the path for data transmission to destination vehicle. Through the selection of CHs using the middle-order approach, the network exhibits an effective maintenance phase here, the weighted probability is applied for the estimation of the path for effective data transmission in the VANET. The comparative analysis of the proposed approach exhibits significant performance rather than conventional technique. The estimated residual energy of the proposed approach is almost 20% higher than ACO, PSO, and KH. The packet delivery rate is observed around 80% and delay is minimal as of 2.5sec.

Multi-User Scheduling for 6G V2X Ultra-Massive MIMO System

6G vehicle-to-everything (V2X) communication will be combined with vehicle automatic driving technology and play an important role in automatic driving. However, in 6G V2X systems, vehicle users have the characteristics of high-speed movement. Therefore, how to provide stable and reliable wireless link quality and improve channel gain has become a problem that must be solved. To solve this problem, a new multi-user scheduling algorithm based on block diagonalization (BD) precoding for 6G ultra-massive multiple-input multiple-output (MIMO) systems is proposed in this paper. The algorithm takes advantage of the sensitive nature of BD precoding to channel correlation, uses the Pearson coefficient after matrix vectorization to measure the channel correlation between users, defines the scheduling factor to measure the channel quality according to the user noise enhancement factor, and jointly considers the influence of the correlation between user channels and channel quality, ensuring the selection of high-quality channels while minimizing channel correlation. Simulation results show that compared with the multi-user scheduling algorithm based on subspace correlation, condition number, and geometric angle, the proposed algorithm can obtain higher user channel gain, effectively reduce the system bit error rate, and can be applied to 6G V2X communication.