Channel Estimation for MIMO Systems

A combination of multiple-input multiple-output (MIMO) systems and orthogonal frequency division multiplexing (OFDM) technologies can be employed in modern wireless communication systems to achieve high data rates and improved spectrum efficiency. For multiple input multiple output (MIMO) systems, this paper provides a Rayleigh fading channel estimation technique based on pilot carriers. The channel is estimated using traditional Least Square (LS) and Minimum Mean Square (MMSE) estimation techniques. The MIMO-OFDM system's performance is measured using the Bit Error Rate (BER) and Mean Square Error (MSE) levels. Keywords: MIMO, MMSE, Channel estimation, BER, OFDM

Self-Interference Cancellation: A Comprehensive Review from Circuits and Fields Perspectives

Increased demand for higher spectrum efficiency, especially in the space-limited chip, base station, and vehicle environments, has spawned the development of full-duplex communications, which enable the transmitting and receiving to occur simultaneously at the same frequency. The key challenge in this full-duplex communication paradigm is to reduce the self-interference as much as possible, ideally, down to the noise floor. This paper provides a comprehensive review of the self-interference cancellation (SIC) techniques for co-located communication systems from a circuits and fields perspective. The self-interference occurs when the transmitting antenna and the receiving antenna are co-located, which significantly degrade the system performance of the receiver, in terms of the receiver desensitization, signal masking, or even damage of hardwares. By introducing the SIC techniques, the self-interference can be suppressed and the weak desired signal from the remote transmitter can be recovered. This, therefore, enables the full-duplex communications to come into the picture. The SIC techniques are classified into two main categories: the traditional circuit-domain SICs and the novel field-domain SICs, according to the method of how to rebuild and subtract the self-interference signal. In this review paper, the field-domain SIC method is systematically summarized for the first time, including the theoretical analysis and the application remarks. Some typical SIC approaches are presented and the future works are outlooked.

Ergodic Capacity of NOMA-Based Multi-Antenna LMS Systems with Imperfect Limitations

With the rapid development of land mobile satellite (LMS) systems, large scale sensors and devices are willing to request wireless services, which is a challenge to the quality of service requirement and spectrum resources utilization on onboard LMS systems. Under this situation, the non-orthogonal multiple access (NOMA) is regarded as a promising technology for improving spectrum efficiency of LMS systems. In this paper, we analyze the ergodic capacity (EC) of NOMA-based multi-antenna LMS systems in the presence of imperfect limitations, i.e., channel estimation errors, imperfect successive interference cancellation, and co-channel interference. By considering multiple antennas at the satellite and terrestrial sensor users, the closed-form expression for EC of the NOMA-based LMS systems with imperfect limitations is obtained. Monte Carlo simulations are provided to verify theoretical results and reveal the influence of key parameters on system performance.

Device to Device Hybridization in 5G and Beyond: A Literature Review

Abstract- Device-to-Device (D2D) communication is one of the most promising technologies to enhance user experience in 5G and beyond. Despite the huge benefit anticipated, enabling D2D in cellular network has encounter some challenges, these challenges include peer discovery and synchronization, mode selection and interference management. However, resolving these challenges promises improved service delivery, spectrum efficiency and reduced latency amongst other gains. Attempts to enable D2D in both microwave and millimeter wave network gained some traction in recent years in a bid to enable wider coverage and utilization of the technology. Some of the research attempts, challenges and prosects are discussed in this paper.Keywords- Device-to-Device, Microwave, millimeter wave, Inter-cell Interference

Data-Driven and Model-Driven Joint Detection Algorithm for Faster-Than-Nyquist Signaling in Multipath Channels

In recent years, Faster-than-Nyquist (FTN) transmission has been regarded as one of the key technologies for future 6G due to its advantages in high spectrum efficiency. However, as a price to improve the spectrum efficiency, the FTN system introduces inter-symbol interference (ISI) at the transmitting end, whicheads to a serious deterioration in the performance of traditional receiving algorithms under high compression rates and harsh channel environments. The data-driven detection algorithm has performance advantages for the detection of high compression rate FTN signaling, but the current related work is mainly focused on the application in the Additive White Gaussian Noise (AWGN) channel. In this article, for FTN signaling in multipath channels, a data and model-driven joint detection algorithm, i.e., DMD-JD algorithm is proposed. This algorithm first uses the traditional MMSE or ZFinear equalizer to complete the channel equalization, and then processes the serious ISI introduced by FTN through the deepearning network based on CNN or LSTM, thereby effectively avoiding the problem of insufficient generalization of the deepearning algorithm in different channel scenarios. The simulation results show that in multipath channels, the performance of the proposed DMD-JD algorithm is better than that of purely model-based or data-driven algorithms; in addition, the deepearning network trained based on a single channel model can be well adapted to FTN signal detection under other channel models, thereby improving the engineering practicability of the FTN signal detection algorithm based on deepearning.

5G F-OFDM Waveform Based Software-Defined Radio Technology

Filtered-orthogonal frequency division multiplexing (F-OFDM) is a quasi-orthogonal waveform candidate for the applications of the fifth generation (5G) communication system. In this study, an F-OFDM waveform with unequal sub-band sizes is proposed to improve the spectrum efficiency (SE) of the 5G system. The proposed waveform is modeled with the Blackman window-sinc filter and is developed based on the software-defined radio (SDR) technology for practical implementation. The result shows that the F-OFDM performance of the simulation and hardware implementation is approximately the same. The SE using the proposed F-OFDM waveform is 6% and 5.8% higher than the SE using the conventional OFDM waveform under the simulation in the LabVIEW NXG simulator and under the practical use in the universal software radio peripheral (USRP) platform, respectively.

Optimization of The Energy Efficiency in Smart Internet of Vehicles Assisted By MEC

Smart Internet of Vehicles (IoV) as a promising application in Internet of Things (IoT) emerges with the development of the fifth generation mobile communication (5G). Nevertheless, the heterogeneous requirements of sufficient battery capacity, powerful computing ability and energy efficiency for electric vehicles face great challenges due to the explosive data growth in 5G and the sixth generation of mobile communication (6G) networks. In order to alleviate the deficiencies mentioned above, this paper proposes a mobile edge computing (MEC) enabled IoV system, in which electric vehicle nodes (eVNs) upload and download data through an anchor node (AN) which is integrated with a MEC server. Meanwhile, the anchor node transmitters radio signal to electric vehicles with simultaneous wireless information and power transfer (SWIPT) technology so as to compensate the battery limitation of eletric vehicles. Moreover, the anchor node equips with full-duplex (FD) and multi-input and multi-output (MIMO) technologies for futher improve the spectrum efficiency. Taking into account the issues above, we maximize the average energy efficiency of electric vehicles by jointly optimize the CPU frequency, vehicle transmitting power, computing tasks and uplink rate. In order to solve this nonconvex problem, we propose a novel alternate interior-point iterative scheme (AIIS) under the constraints of computing tasks, energy consumption and time latency. Numerical simulations demonstrate the effectiveness of the proposed scheme comparing with the benchmark schemes.

On the Design of Rate Adaptation for Relay-Assisted Satellite Hybrid FSO/RF Systems

<p>This paper addresses the design of hybrid free-space optical/radio frequency (FSO/RF) systems for a high-altitude platform (HAP)-aided relaying satellite communication for mobile networks supported by unmanned aerial vehicle (UAV). While prior work primarily focused on fixed-rate design, which frequently switches between FSO and RF lead to reduce the system performance, we propose a rate adaptation design that gradually adjusts the data rate in each link when its channel state fluctuates. The proposed design's downlink performance is analyzed, taking into account many challenging issues, including beam spreading loss, cloud attenuation, statistical behaviors of the atmospheric turbulence in the dual-hop channel, and pointing misalignment due to the UAV hovering. Different performance metrics are analytically derived based on channel modelings, such as outage probability, average transmission rate, achievable spectrum efficiency, and average transmission rate. The numerical results quantitatively confirm the effectiveness of our proposed system under the impact of UAV hovering misalignment and atmospheric-related issues like clouds and turbulence. Finally, Monte-Carlo simulations validate the accuracy of theoretical results.</p>

Protection against Failure of Machine Learning-based QoT Prediction

Machine learning (ML)-based methods are widely explored to predict the quality of transmission (QoT) of a lightpath, which is expected to reduce optical signal to noise ratio (OSNR) margin reserved for the lightpath and therefore improve the spectrum efficiency of an optical network. However, many studies conducting this prediction are often based on synthetic datasets or datasets obtained from laboratory. As such, these datasets may not be amply representative to cover the entire status space of a real optical network, which is often exposed in harsh environment. There are risks of failure when using these ML-based QoT prediction models. It is necessary to develop a mechanism that can guarantee the reliability of a lightpath service even if the prediction models fail. For this, we propose to take advantage of the conventional network protection techniques that are popularly implemented in an optical network and reuse their protection resources to also protect against such a type of failure. Based on the two representative protection techniques, i.e., 1+1 dedicated path protection and shared backup path protection (SBPP), the performance of the proposed protection mechanism is evaluated by reserving different margins for the working and protection lightpaths. For 1+1 path protection, we find that the proposed mechanism can achieve a zero design-margin (D-margin) for a working lightpath thereby significantly improving network spectrum efficiency, while not scarifying the availability of lightpath services. For SBPP, we find that an optimal D-margin should be identified to balance the spectrum efficiency and service availability, and although not significant, the proposed mechanism can save an up to 0.5-dB D-margin for a working lightpath, while guaranteeing the service availability.