Shrinkage widely linear recursive least squares (SWL-RLS) and its improved version called structured shrinkage widely linear recursive least squares (SSWL-RLS) algorithms are proposed in this paper. By using the relationship between the noise-free a posterior and a priori error signals, the optimal forgetting factor can be obtained at each snapshot. In the implementation of algorithms, due to the a priori error signal known, we still need the information about the noise-free a priori error which can be estimated with a known formula. Simulation results illustrate that the proposed algorithms have faster convergence and better tracking capability than augmented RLS (A-RLS), augmented least mean square (A-LMS) and SWL-LMS algorithms.

In this paper, we consider a two-way multi-relay scenario and analyze the bit error rate (BER) and outage performance of an amplify-and-forward (AF) relaying protocol. We first investigate the bit error probability by considering channel estimation error. With the derivation of effective signal-to-noise ratio (SNR) at the transceiver and its probability density function (PDF), we can obtain a closed form formulation of the total average error probability of two-way multi-relay system. Furthermore, we also derive exact expressions of the outage probability for two-way relay through the aid of a modified Bessel function. Finally, numerical experiments are performed to verify the analytical results and show that our theoretical derivations are exactly matched with simulations.

This paper proposes a novel scheme called as“frequency domain imbalance estimation” that estimates the imbalance of the Hilbert transformer in heterodyne multimode/band receivers with baseband automatic gain control (AGC). The proposed scheme uses correlation matrices in the frequency domain. This enables the receivers to keep high transmission performance in spite of the imbalance of the analog Hilbert transformer, by offsetting the imbalance. Moreover, the baseband AGC relaxes the requirement of the baseband A/D converter. The performance of imbalance estimation and imbalance cancellation is verified by computer simulation. As a result, it is shown that the proposed scheme not only estimates the imbalance of Hilbert transformer with extremely high precision, but also cancels the image-band interference such that it achieves the theoretical performance.

Controlled optimization of phases (COP) is a core implementation in the future intelligent traffic signal system (I-SIG), which has been deployed and tested in countries including the U.S. and China. In such a system design, optimal signal control depends on dynamic traffic situation awareness via connected vehicles. Unfortunately, I-SIG suffers data spoofing from any hacked vehicle; in particular, the spoofing of the last vehicle can break the system and cause severe traffic congestion. Specifically, coordinated attacks on multiple intersections may even bring cascading failure of the road traffic network. To mitigate this security issue, a blockchain-based multi-intersection joint defense mechanism upon COP planning is designed. The major contributions of this paper are the following. 1) A blockchain network constituted by road-side units at multiple intersections, which are originally distributed and decentralized, is proposed to obtain accurate and reliable spoofing detection. 2) COP-oriented smart contract is implemented and utilized to ensure the credibility of spoofing vehicle detection. Thus, an I-SIG can automatically execute a signal planning scheme according to traffic information without spoofing data. Security analysis for the data spoofing attack is carried out to demonstrate the security. Meanwhile, experiments on the simulation platform VISSIM and Hyperledger Fabric show the efficiency and practicality of the blockchain-based defense mechanism.

Inter-person occlusion handling is a critical issue in the field of tracking, and it has been extensively researched. Several state-of-the-art methods have been proposed, such as focusing on the appearance of the targets or utilizing knowledge of the scene. In contrast with the approaches proposed in the literature, we propose to address this issue using a social interaction model, which allows us to explore spatio-temporal information pertaining to the targets involved in the occlusion situation. Our experimental results show promising results compared with those obtained using other methods.

It is known that a heterodyne multimode receiver implemented with a single RF (Radio Frequency) receiver suffers from image-band interference due to imbalance, i.e. the phase error and the gain imbalance of the RF Hilbert transformer. The blind image band interference canceler with deterministic imbalance estimation that has been proposed mitigates the image-band interference. This performance of the image-band interference canceler is analyzed theoretically in this paper. As a result, it is revealed that estimation accuracy of the deterministic imbalance estimation is improved slightly as the imbalance becomes greater. In addition, it is also shown that the deterministic estimation achieves better performance as the power of image-band interference increases. The performance is confirmed by computer simulation.

The selection of mutation strategy greatly affects the performance of differential evolution algorithm (DE). For different types of optimization problems, different mutation strategies should be selected. How to choose a suitable mutation strategy for different problems is a challenging task. To deal with this challenge, this paper proposes a novel DE algorithm based on local fitness landscape, called FLIDE. In the proposed method, fitness landscape information is obtained to guide the selection of mutation operators. In this way, different problems can be solved with proper evolutionary mechanisms. Moreover, a population adjustment method is used to balance the search ability and population diversity. On one hand, the diversity of the population in the early stage is enhanced with a relative large population. One the other hand, the computational cost is reduced in the later stage with a relative small population. The evolutionary information is utilized as much as possible to guide the search direction. The proposed method is compared with five popular algorithms on 30 test functions with different characteristics. Experimental results show that the proposed FLIDE is more effective on problems with high dimensions.