Naitong Zhang

Broadband Hybrid Satellite-Terrestrial Communication Systems Based on Cognitive Radio toward 5G

The development of 5G terrestrial mobile communications technology has been a driving force for revolutionizing satellite mobile communications. Satellite mobile communications, which carry many unique features, such as large coverage and support for reliable emergency communications, should satisfy the requirements for convergence between terrestrial mobile communications and satellite mobile communications for future broadband hybrid S-T communications. On the other hand, CR is an attractive technique to support dynamic single-user or multi-user access in hybrid S-T communications. This article first discusses several key issues in applying cognitive radio to future broadband satellite communications toward 5G. Then we present an overview of future broadband hybrid S-T communications systems, followed by an introduction to a typical application scenario of futuristic CR-broadband hybrid S-T communication systems toward 5G. Moreover, we propose a space segment design based on a spectrum-sensing-based cooperative framework, in consideration of the presence of MUs. An experiment platform for the proposed CR-based hybrid S-T communications system is also demonstrated.

On exploiting polarization for energy-harvesting enabled cooperative cognitive radio networking

Radio spectrum underutilization and energy inefficiency become urgent bottleneck problems to the sustainable development of wireless technologies. The research philosophies of wireless communications have been shifted from balancing reliability-efficiency tradeoff in the link level to seeking spectrum-energy efficiency in the network level. Global spectrum-energy efficient designs attract significant attention to improving utilization and efficiency, wherein cognitive radio networks and energy scavenging related techniques are of particular interests. In this article, we first provide a systematic study on cooperative cognitive radio networking (CCRN), followed by the discussions on research issues and challenges in designing spectrum-energy complexity efficient CCRN. As an effort to shed light on addressing spectrum-energy inefficiency at a low complexity, a novel CCRN paradigm exploiting polarization and energy harvesting capabilities is elaborated. Specifically, we present a novel polarization and energy harvesting based framework for achieving size-cost effective CCRN. We introduce polarization signal processing to avoid interference between secondary users and primary users in cooperation. We propose a weighted sum spectrum efficiency based problem formulation and multi-timescale dynamic programming based energy/power allocation policy to evaluate the cooperation performance, subject to energy levels, power, and throughput constraints.

On uncertainty principle for signal concentrations with fractional Fourier transform

The fractional Fourier transform (FRFT) - a generalized form of the classical Fourier transform - has been shown to be a powerful analyzing tool in signal processing. This paper investigates the uncertainty principle for signal concentrations associated with the FRFT. It is shown that if the fraction of a nonzero signals energy on a finite interval in one fractional domain with a certain angle @a is specified, then the fraction of its energy on a finite interval in other fractional domain with any angle @b(@b @a) must remain below a certain maximum. This is a generalization of the fact that any nonzero signal cannot have arbitrarily large proportions of energy in both a finite time duration and a finite frequency bandwidth. The signals which are the best in achieving simultaneous concentration in two arbitrary fractional domains are derived. Moreover, some applications of the derived theory are presented.

Polarization filtering technique based on oblique projections

Based on the theory of polarization filtering and the merits of interference suppressions when adopting oblique projections, a novel polarization filtering algorithm is proposed in this paper. The proposed method can effectively separate the target signal and interference without additional transformation and compensation processing, and the target does not suffer distortions after separation. The suggested scheme is still valid when the target and interference hold the same polarized angle but different phase difference in polarized angle. We extend the application to the scope of known target polarization but unknown interference polarization, finding that the interference is restrained and the amplitude/phase of the target are both totally kept. Theoretic analysis and mathematical deduction show that the proposed scheme is a valid and simple implementation. Simulation results also demonstrate that the suggested method can obtain better filtering performance than the conventional polarization filtering (CPF) and the null-phase-shift polarization filtering (NPSPF). It is proved that the proposed OPPF is an extension to the CPF and the NPSPF, and it develops the theory of polarization filtering effectively.

A sampling theorem for the fractional Fourier transform without band-limiting constraints

The fractional Fourier transform (FRFT), a generalization of the Fourier transform, has proven to be a powerful tool in optics and signal processing. Most existing sampling theories of the FRFT consider the class of band-limited signals. However, in the real world, many analog signals encountered in practical engineering applications are non-bandlimited. The purpose of this paper is to propose a sampling theorem for the FRFT, which can provide a suitable and realistic model of sampling and reconstruction for real applications. First, we construct a class of function spaces and derive basic properties of their basis functions. Then, we establish a sampling theorem without band-limiting constraints for the FRFT in the function spaces. The truncation error of sampling is also analyzed. The validity of the theoretical derivations is demonstrated via simulations.

Sampling and Reconstruction in Arbitrary Measurement and Approximation Spaces Associated With Linear Canonical Transform

The linear canonical transform (LCT), which generalizes many classical transforms, has been shown to be a powerful tool for signal processing and optics. Sampling theory of the LCT for bandlimited signals has blossomed in recent years. However, in practice signals are never perfectly bandlimited, and in many cases measurement devices are nonideal. The objective of this paper is to develop a sampling theorem for the LCT from general measurements, which can provide a suitable and realistic model of sampling and approximation for real-world applications. We first describe a general class of approximation spaces for the LCT and provide a full characterization of their basis functions. Then, we propose a generalized sampling theorem for arbitrary measurement and approximation spaces associated with the LCT. Several properties of the proposed sampling theorem are also discussed. Furthermore, the approximation error is estimated. Finally, numerical results and several applications of the derived results are presented.

Sampling expansion for irregularly sampled signals in fractional Fourier transform domain

Real-world signals are often not band-limited, and in many cases of practical interest sampling points are not always measured regularly. The purpose of this paper is to propose an irregular sampling theorem for the fractional Fourier transform (FRFT), which places no restrictions on the input signal. First, we construct frames for function spaces associated with the FRFT. Then, we introduce a unified framework for sampling and reconstruction in the function spaces. Based upon the proposed framework, an FRFT-based irregular sampling theorem without band-limiting constraints is established. The theoretical derivations are validated via numerical results.

Resource allocation based on subcarrier exchange in multiuser OFDM system

Multi-user orthogonal frequency division multiplexing (OFDM) is one of the most important techniques for next-generation wireless communication systems. The sum capacity and proportional fairness index are two important metrics in OFDM adaptive resource allocation. In existing researches, the two metrics have individually yielded approximately optimal solutions. However, as the two goals seem to contradict each other, it means that they cannot achieve optima simultaneously. This paper presents a resource allocation algorithm based on subcarrier exchange. By relaxing the fairness index, the proposed algorithm can dynamically adjust the fairness requirements. Furthermore, By considering a criterion that minimizes the loss of sum capacity, the proposed algorithm can balance the tradeoff between fairness and sum capacity. In contrast to existing algorithms, our proposal improves performance by approximately 30% in terms of sum capacity, at the expense of approximately 10% reduction in proportional fairness. Moreover, if a malicious user exists, each user in the system can obtain higher ergodic capacity compared with the conventional algorithms. To decrease the complexity, a low-complexity simplified alternative is presented, which outperforms the conventional algorithm with an increase in the number of users. Four numerical simulations are carried out to verify the efficiency and effectiveness. Finally, we discuss in detail the computational complexity of the proposed algorithm.

The performance of ultra wideband acquisition system based on energy detection over IEEE 802.15.3a channel

In this paper, we propose a theoretical framework to analyze the performance of ultra wideband acquisition (UWB) system based on energy detection (ED) over IEEE 802.15.3a channel. The proposed framework enables to calculate probability density function (PDF) of square-sum of multipath components (MPCs) gain collected by receiver, and the averaged criteria. In particular, the expectation and variance of the sum variant characterized approximately by log-normal distribution are expressed in a closed form based on cluster point process. Moreover, the calculating methods of averaged criteria, through Markov chain model and signal flow graph, are clearly demonstrated for different applicable scenarios. The proposed framework is well consistent with simulation results with respect to each calculation method.

Peak to average power ratio suppression method joint orthogonal and non-orthogonal scheme

With the rapid development of wireless communication, the spectrum resources are increasingly scarce, and the limited utilization of spectrum resources has become a popular research, especially in the 5G mobile communication system. Some efficient frequency division multiplexing systems, such as SEFDM (Spectrally Efficient Frequency Division Multiplexing) system, can improve spectrum utilization by the further compression of the distance between sub-carriers based on OFDM carrier structure. This idea of further compression bands will largely solve the problem of scarce spectrum resources in the future. However, due to the further compression of the sub-carrier spacing, the PAPR (peak to average power ratio) is larger than that of traditional OFDM system. In this paper, a method of PAPR suppression for joint orthogonal and non orthogonal spectrally efficient frequency division multiplexing based on SEFDM in the transmitter is proposed, which can restrain the PAPR (peak-to-average ratio) of the transmission system under the condition of spectrally efficient spectrum utilization so as to improve the system performance. The simulation result shows that the PAPR of the system presented in this paper is 2 to 3 dB lower than that under the traditional scheme in a certain interval.