Zhongzhao Zhang

Virtual multi-beamforming for distributed satellite clusters in space information networks

This article introduces some basic theories of space information networking (SIN), which is a novel research field. A SIN is a network that is able to achieve real-time acquisition, transmission, and processing of space information. The article first investigates the basic satellite-terrestrial architecture of SINs, and then three key technologies of SINs are presented, specifically more details on the high data rate transmission theory. The DSC is the foundation of high data rate transmission; thus, the core technology of DSC, which is beam/beamforming theory, is discussed in detail. Compared to the traditional spot beam theory, this article proposes a novel VBF concept, which is capable of increasing the channel capacity. Some key technologies are also investigated for VBF; they are channel capacity theoretical analysis, opportunistic beamforming, virtual multi-beamforming, and resource management.

Asymmetric active cooperation strategy in spectrum sharing game with imperfect information

In this paper, we study the spectrum sharing problem in the cognitive network where two secondary users coexist and interfere with each other in an unlicensed channel. Each user in our scenario is independent and is unaware of the characteristic of its rival but its statistics imperfect information. An important issue is the interaction among selfish independent wireless communication systems secondary users who aim to maximize their own current utility. We provide a self-enforcing spectrum sharing framework, which has the advantage of not requiring a control center or communicating between two users. The short-term profits of users gained before cooperation being builded are asymmetrical. The long-term profit is used as the users utility. Users improve their long-term profits by creating mutual cooperation actively. The historical action of the user is used by its rival to evaluate/update the current action. The action updating algorithm is provided. Moreover, we investigate the stability of the cooperation. As demonstrated, the proposed scheme can build mutual cooperation through extensive simulations. The existence of equilibrium is confirmed by the repeated game. And our scheme can achieve a good trade-off between short-term profits and long-term profits. Copyright

A Spatial Division Clustering Method and Low Dimensional Feature Extraction Technique Based Indoor Positioning System

Indoor positioning systems based on the fingerprint method are widely used due to the large number of existing devices with a wide range of coverage. However, extensive positioning regions with a massive fingerprint database may cause high computational complexity and error margins, therefore clustering methods are widely applied as a solution. However, traditional clustering methods in positioning systems can only measure the similarity of the Received Signal Strength without being concerned with the continuity of physical coordinates. Besides, outage of access points could result in asymmetric matching problems which severely affect the fine positioning procedure. To solve these issues, in this paper we propose a positioning system based on the Spatial Division Clustering (SDC) method for clustering the fingerprint dataset subject to physical distance constraints. With the Genetic Algorithm and Support Vector Machine techniques, SDC can achieve higher coarse positioning accuracy than traditional clustering algorithms. In terms of fine localization, based on the Kernel Principal Component Analysis method, the proposed positioning system outperforms its counterparts based on other feature extraction methods in low dimensionality. Apart from balancing online matching computational burden, the new positioning system exhibits advantageous performance on radio map clustering, and also shows better robustness and adaptability in the asymmetric matching problem aspect.

Random Forest Based Coarse Locating and KPCA Feature Extraction for Indoor Positioning System

With the fast developing of mobile terminals, positioning techniques based on fingerprinting method draw attention from many researchers even world famous companies. To conquer some shortcomings of the existing fingerprinting systems and further improve the system performance, on the one hand, in the paper, we propose a coarse positioning method based on random forest, which is able to customize several subregions, and classify test point to the region with an outstanding accuracy compared with some typical clustering algorithms. On the other hand, through the mathematical analysis in engineering, the proposed kernel principal component analysis algorithm is applied for radio map processing, which may provide better robustness and adaptability compared with linear feature extraction methods and manifold learning technique. We build both theoretical model and real environment for verifying the feasibility and reliability. The experimental results show that the proposed indoor positioning system could achieve 99% coarse locating accuracy and enhance 15% fine positioning accuracy on average in a strong noisy environment compared with some typical fingerprinting based methods.

High Dynamic GPS Signal Tracking Based on UKF and Carrier Aiding Technology

Due to the impacts of the loop bandwidth, the high dynamic environment could cause the carrier tracking loop of the GPS receiver loss of lock, and the pseudo-code tracking loop errors increased. According to the characters of the high dynamic environment, a GPS IF digital signal source is firstly designed here, then an improved carrier tracking loop based on the UKF is proposed, which works steady and has high tracking accuracy. Besides, the estimates of the Doppler frequency shift and its derivative is also extracted by UKF to aid pseudo-code tracking loop. To certain extent, with carrier aiding, the dynamics of the code loop is eliminated to decrease the tracking errors. Finally, all designs in this paper are completed by Matlab and evaluated by computer simulation. Results show that: the signal source design is proper, the proposed carrier tracking loop works steady, and the errors of the code tracking loop is decreased significantly.

UKF-Based Iterative Channel Estimation Using Two-Dimensional Block Spread Coding for Uplink Transmission in Multicarrier CDMA Networks

Future broadband wireless applications must effectively work under highly dynamic and strong multipath channel conditions, where severe time- and frequency-selective fading effects will coexist. Although some advanced techniques, such as 2-D block spread coding and antenna diversity techniques, can be applied to the code-division multiple-access (CDMA) networks to improve the performance, an accurate estimation of the channel is normally required. Conventional channel estimators (CE) such as the minimum-mean-square-error (MMSE)-based CE cannot effectively track the channel when the time-selective fading of the channel becomes severe. The performance will even be deteriorated in a multiuser environment, where multiple-access interference (MAI) exists. Therefore, in this paper, we demonstrate the challenges to CE in 2-D block spread coding networks through analytical derivation and then propose an unscented Kalman-filter (UKF)-based iterative CE for uplink transmission in multicarrier CDMA networks. By jointly working with the MMSE-CE, our proposed UKF-based approach can effectively track the dynamic changes in the time-selective fading channel and compensate for the estimation lag caused by the Doppler effects. Our scheme can also effectively mitigate the impact of the residual MAI, which resulted from the detection process. Simulation analysis demonstrates the good estimation performance and the quick convergence of the proposed MMSE-UKF CE, particularly under fast-varying channel conditions.

A novel UKF based scheme for GPS signal tracking in high dynamic environment

Unscented Kalman filter (UKF) based methods have been developed for the tracking of GPS L1 signal. Optimal Kalman filtering theory makes it possible to maintain locking with large Doppler frequency shift when the receiver works in high dynamic environment. A novel UKF based carrier tracking loop with high accurate tracking performance is put forward, where a frequency fast pull-in technology is performed to ensure the filter converge fast and another two different carrier amplitude estimation methods are included to make the dynamic model complete. The relationship between the noise parameter of UKF and the equal loop-bandwidth is also studied. Based on this novel loop and carrier-aiding technology, a joint carrier aiding and code phase extracting from the estimation results of the UKF for code tracking is analyzed. Simulation results show that the carrier tracking loop works steady in high dynamic situations, and the pseudo-code tracking precision is improved significantly.

Joint UKF and MMSE Channel Estimation for Uplink 2-Dimensional Block Spread MC-CDMA with Cyclic Delay Transmit Diversity

Multi-access interference (MAI) free uplink transmission can be achieved by 2-dimensional (2D) block spread code division multi access (CDMA), and low-complexity single-user frequency-domain equalization (FDE) is performed at base station to obtain the frequency diversity gain. Cyclic delay transmit diversity (CDTD) can further improve the transmission performance by obtaining a larger frequency diversity gain in the frequency selective fading channel. However, accurate estimation of the channel transfer function is the premise for the use of 2D block spread CDMA with CDTD. Unscented Kalman filter (UKF) is an attractive technology and suitable for the Rayleigh channel estimation in time domain, which can be used to assist the minimum mean square error (MMSE) criterion based channel estimation (CE) to improve the BER performance. This paper proposes a joint UKF and MMSE criterion CE method. The achievable uplink BER performance is evaluated by computer simulation for 2D block spread multi-carrier (MC) CDMA, which shows that the joint CE can improve the BER performance about 0.8dB compared with MMSE-CE when BER=10-4.

Maximum product of effective channel gains: an innovative user selection algorithm for downlink multi-user multiple input and multiple output

Recently, zero-forcing beamforming has been widely used for multiple-input and multiple-output broadcast channels, because it could provide suboptimal capacity with low complexity. To increase the sum data rate, a good user selection algorithm is attractive. In this paper, a new user selection algorithm named maximum product of effective channel gains is presented. The proposed algorithm is described mathematically, and the lower bound of the sum capacity is demonstrated to be proportional to the product of effective channel gains. Our simulation results show that maximum product of effective channel gains can achieve higher sum rate compared with the classical algorithm, semi-orthogonal user selection, with the same complexity order, especially when the signal-to-noise ratio is high; in addition, the complexity of the proposed algorithm is superior to minimum of the Frobenius norm of the pseudo-inverse algorithm. Meanwhile, the number of users that can be served simultaneously is equal to the number of transmission antennas, which is the maximum performance that can be achieved.Copyright

UKF Based Iterative Joint Channel Estimation for Uplink Two Dimensional Block Spread Wireless Networks

Applications for future broadband wireless network should work effectively under highly dynamic wireless channel environment, where strong frequency-selective and time-selective fading and severe multi-path channels will exist. Though some advantage techniques, such as 2-dimensional (2D) block spread, frequency domain equalization (FDE) and antenna diversity techniques, can be applied to the code division multiple access (CDMA) networks to improve the bit error rate (BER) performance, they all require an accurate estimation of the channel. Conventional channel estimation method such as the minimum mean square errors (MMSE) based channel estimation scheme may not be applicable because its performance degrades significantly when the channel dynamics become severe. Therefore, in this paper, we propose an unscented Kalman filter (UKF) based iterative channel estimation method, which is jointly used with the MMSE channel estimation scheme, to track the channel dynamics in both time domain and frequency domain. Hence, better estimation accuracy of the fast fading channels can be achieved. Furthermore, we utilize cyclic iteration to ensure UKF converge to the stable result accurately and quickly, and the iteration count can be adjusted according to the Doppler effects. Our performance analysis demonstrates that the proposed joint estimation method can achieve good BER performance under both low and high dynamic channel conditions. It is much better than the pure MMSE based channel estimation method, and is very close to results from an ideal channel estimator.