Due to the huge surge in the traffic of IoT devices and applications, mobile networks require a new paradigm shift to handle such demand roll out. With the 5G economics, those networks should provide virtualized multi-vendor and intelligent systems that can scale and efficiently optimize the investment of the underlying infrastructure. Therefore, the market stakeholders have proposed the Open Radio Access Network (O-RAN) as one of the solutions to improve the network performance, agility, and time-to-market of new applications. O-RAN harnesses the power of artificial intelligence, cloud computing, and new network technologies (NFV and SDN) to allow operators to manage their infrastructure in a cost-efficient manner. Therefore, it is necessary to address the O-RAN performance and availability challenges autonomously while maintaining the quality of service. In this work, we propose an optimized deployment strategy for the virtualized O-RAN units in the O-Cloud to minimize the network's outage while complying with the performance and operational requirements. The model's evaluation provides an optimal deployment strategy that maximizes the network's overall availability and adheres to the O-RAN-specific requirements.

This work introduces a novel blind channel estimation technique for orthogonal frequency division multiplexing (OFDM) systems over time- varying mobile channels. The proposed estimator exploits the channel correlation over consecutive OFDM symbols to estimate the channel parameters blindly. In the new estimator, particular subcarriers are modulated usingM-ary phase shift keying (MPSK), and subcarriers with the same indices in the consecutive OFDM symbol are modulated usingM-ary amplitude shift keying (MASK), replacing the pilots in pilot-aided systems. Consequently, all subcarriers are data-bearing, which leads to spectral efficiency improvement. The proposed estimator uses the feature that MPSK and MASK modulated symbols have sufficient channel state information (CSI) that enable them to cooperate in order to detect the MPSK symbols coherently and blindly. Then, the CSI at the corresponding MPSK symbols can be acquired in a decision-directed (DD) fashion. The performance of the proposed estimator is evaluated in terms of symbol error rate (SER) and mean-squared error (MSE), where an exact analytical formula is obtained for the SER of binary phase shift keying (BPSK) symbols in mobile radio channels with various time-varying rates. The obtained results show that the proposed estimator produces accurate channel estimates as compared to pilot-aided and state-of-the-art systems without additional complexity.

In the literature, the spectral efficiency is considered a key performance indicator that is used to classify various communications systems, algorithms, and techniques. However, the classification is typically performed while assuming that all systems have a static structure, and without considering the quality of service (QoS) requirements or the constraints imposed by the system design. Therefore, this work presents a new reliable and accurate approach to evaluate the spectral efficiency of communications systems while considering the system dynamics, QoS requirements and design constraints. To demonstrate its effectiveness, the proposed approach is used to evaluate the spectral efficiency of various blind and pilot-aided channel estimation and synchronization algorithms. The obtained results reveal that the spectral efficiency depends on several system variables such the signal-to-noise ratio (SNR), QoS requirements, system constraints, and the channel characteristics. Contrary to what is usually believed, the obtained results show that pilot-aided systems can be more spectrally efficient than blind systems for several cases of interest.

This paper presents a blind channel estimation (BCE) technique for orthogonal frequency division multiplexing communications systems. The proposed system is based on modulating particular pairs of subcarriers using amplitude shift keying and phase shift keying, which enables the realization of a decision-directed one-shot BCE (OSBCE), with complexity and accuracy that are comparable to pilot-based channel estimation techniques. The performance of the proposed estimator is evaluated in terms of the mean squared error (MSE), where an accurate analytical expression is derived and verified using Monte Carlo simulation under various channel conditions. The obtained results show that the MSE of the proposed OSBCE is comparable to pilot-based estimators, which confirms the efficiency of the proposed OSBCE.