Su Hu

Training Sequence Design for Efficient Channel Estimation in MIMO-FBMC Systems

This paper is focused on training sequence design for efficient channel estimation in multiple-input multiple-output filterbank multicarrier (MIMO-FBMC) communications using offset quadrature amplitude modulation (OQAM). MIMO-FBMC is a promising technique to achieve high spectrum efficiency as well as strong robustness against dispersive channels due to its feature of time-frequency localization. A salient drawback of FBMC/OQAM signals is that only real-field orthogonality can be kept, leading to the intrinsic imaginary interference being a barrier for high-performance channel estimations. Also, conventional channel estimations in the MIMO-FBMC systems mostly suffer from high training overhead especially for large number of transmit antennas. Motivated by these problems, in this paper, we propose a new class of training sequences, which are formed by concatenation of two identical zero-correlation zone sequences whose auto-correlation and cross correlation are zero within a time-shift window around the in-phase position. Since only real-valued symbols can be transmitted in MIMO-FBMC systems, we propose “complex training sequence decomposition (CTSD)” to facilitate the reconstruction of the complex-field orthogonality of MIMO-FBMC signals. Our simulations validate that the proposed CTSD is an efficient channel estimation approach for practical preamble-based MIMO-FBMC systems.

Frequency-Domain Oversampling for Cognitive CDMA Systems: Enabling Robust and Massive Multiple Access for Internet of Things

Toward the era of mobile internet and Internet of Things (IoT), numerous sensors and devices are being introduced and interconnected. To support such amount of data traffic, traditional wireless communication technologies are facing challenges both in terms of increasingly shortage of spectrum resource and massive multiple access. In this paper, cognitive code division multiple access (Cognitive-CDMA) is proposed by combining the concept of cognitive radio with dynamic noncontinuous spectrum bands and code division multiple access. In order to suppress multiple access interference resulting from the non-orthogonality of partial available spectrum bins, carrier frequency offset, and spectrum sensing mismatch, an enhanced receiver design using frequency-domain oversampling (FDO) with linear minimum mean square error (MMSE) is considered in this paper for Cognitive-CDMA systems. By spectrum sensing to mitigate spectral interference in the transceiver and by utilizing FDO in the receiver to project received signal to a higher dimension, the proposed Cognitive-CDMA is able to support robust and massive multiple access for IoT applications. The simulation results show that the cognitive-CDMA with FDO-MMSE receiver outperforms that with conventional per-user MMSE receiver in the presence of multipath fading channels, carrier frequency offset, and spectrum sensing mismatch.

Mobile Network Security and Privacy in WSN

Abstract This paper discuss the term threats, attacks and vulnerabilities in Wireless Sensor Networks followed by a model that relates the three entities. Based on the model, a framework of Trusted Wireless Sensor node is presented consisting of two major sections which are platform security enhancement and Trusted Authentication protocol to enhance sensor nodes security features and confirm the fidelity of node joining the network respectively. The design of the framework is in line with Trusted Computing Group specifications toward trusted platform implementation. Finally, brief analysis on the proposed framework is presented.

Optimal spectrally-constrained sequences

A sequence is said to be spectrally-constrained if it has to satisfy a spectral map consisting of several non-contiguous nulled frequency-slots. Such sequences play a key role in emerging spectrally-constrained systems such as cognitive radio and cognitive radar. In this paper, we study two types of spectrally-constrained sequences (SCSs), one with low periodic auto-correlation function (PACF) sidelobe, the other with zero auto-correlation zone (ZACZ). By deriving a correlation lower bound, we show that Type-I SCSs are optimal with minimum total PACF sidelobe energy provided that uniform power allocation is applied to all active (non-nulled) frequency-slots. We also propose optimal Type-II SCSs, each having maximum ZACZ width, for certain spectral map patterns.

Game theoretic approach of a novel decision policy for customers based on big data

In recent days, big data based analysis in hotel industry become popular. Merchants are attracting clients using the accurate analysis of historic data and predicting the behavior of possible clients to perform proper marketing strategy. To study the principle of the game between clients and merchants, in this work, we propose a novel two-stage game theoretic approach of decision policy for clients when choosing the suitable hotel to stay among many candidates, the merchants will provide a non-cooperative game strategy to attract the attention of potential clients. Analysis of the non-cooperative game method based on big data has been given. Simulation results indicate that, by using our proposed novel method, the average price for clients to choose a satisfied hotel is reduced and the successful rate of stay is increased for merchants, which will bring the expected income to a higher level because of the sticky phenomena of users.

Cooperative Downlink Resource Allocation in 5G Wireless Backhaul Network

The 5th wireless communication system will provide higher throughput and more reliable QoS through many key techniques. Cooperation is one possible technology that may provide satisfied performance to users, especially the cell edge users. In this work, we provide the analysis of resource allocation in wireless backhaul networks, through capacity constraint wireless backhaul, the cooperative downlink joint processing is proposed to enhance cell edge performance. We propose the system level simulation and evaluate the cluster performance. Simulation results indicate that the capacity constraint wireless backhaul will bring delay, capacity limit to joint processing method, traditional cooperation scheme will not work well, and our proposed method could gain 13% compared to traditional method.

Constant Envelope OFDM RadCom System

A joint radar and communication system would constitute a unique platform for future intelligent transportation networks effecting the essential tasks of environmental sensing and wireless communication. While the inherent high peak-to-average power ratio (PAPR) question of OFDM system cannot be solved. This paper introduces a constant envelope multi-carrier RadCom approach with the advantages of high data rate, high ability of anti-fading, simple radar processing, and constant 0 dB PAPR. Constant envelope OFDM RadCom system is able to solve the high PAPR question perfectly, promote efficiency of power amplifier and resistance to fading.

On Transform Domain Communication Systems under Spectrum Sensing Mismatch: A Deterministic Analysis.

Towards the era of mobile Internet and the Internet of Things (IoT), numerous sensors and devices are being introduced and interconnected. To support such an amount of data traffic, traditional wireless communication technologies are facing challenges both in terms of the increasing shortage of spectrum resources and massive multiple access. The transform-domain communication system (TDCS) is considered as an alternative multiple access system, where 5G and mobile IoT are mainly focused. However, previous studies about TDCS are under the assumption that the transceiver has the global spectrum information, without the consideration of spectrum sensing mismatch (SSM). In this paper, we present the deterministic analysis of TDCS systems under arbitrary given spectrum sensing scenarios, especially the influence of the SSM pattern to the signal to noise ratio (SNR) performance. Simulation results show that arbitrary SSM pattern can lead to inferior bit error rate (BER) performance.