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Enhanced C-V2X Mode-4 Subchannel Selection
TLDR
A nonlinear power averaging phase, where the most up-to-date measurements are assigned higher priority via exponential weighting is proposed, and it is shown through simulations that the overall system performance can be leveraged in both urban and freeway scenarios.
A novel fuzzy logic-based metric for audio quality assessment: Objective audio quality assessment
TLDR
A new metric of low computational complexity called FQI (Fuzzy Quality Index) which is based on Fuzzy Logic reasoning and has been incorporated into the existing PEAZ model to improve its overall performance and results show that the modified version slightly outperforms PEAQ.
Graph-based resource allocation with conflict avoidance for V2V broadcast communications
TLDR
This research has envisaged a solution based on a bipartite graph, where vehicles and spectrum resources are represented by vertices whereas the edges represent the achievable rate in each resource based on the signal-to-interference-plus-noise ratio (SINR) that vehicles perceive.
Hybrid Precoding for Multi-Group Multicasting in mmWave Systems
TLDR
This paper investigates the first joint design of hybrid transmit precoders and receive combiners for mmWave multi-group multicasting and demonstrates by means of extensive simulations that the hybrid precoder design performs very close to its fully-digital counterpart even under challenging scenarios.
Subchannel allocation for vehicle-to-vehicle broadcast communications in mode-3
TLDR
Four types of conditions that are of forceful character for attaining QoS-aware conflict-free allocations have been identified and a surrogate relaxation of the problem is proposed that does not affect optimality provided that certain requisites are satisfied.
System Level Simulation of Scheduling Schemes for C-V2X Mode-3
TLDR
Through simulations, it is shown that the proposed schemes outperform C-V2X \textit{mode-4} as the subchannels are assigned in a more efficient manner with mitigated interference.
TDOA-Based Localization via Stochastic Gradient Descent Variants
TLDR
This paper compares the performance of the classical stochastic gradient descent with novel optimization algorithms for signal processing problems and proposes an optimization procedure called RMSProp+AF, which is based onRMSProp algorithm but with the advantage of incorporating adaptation of the decaying factor.