Localizing noncooperative receiver through full-duplex amplify-and-forward relay

Localizing noncooperative transmitter (Tx) and receiver (Rx) that belong to another system is important in many scenarios, e.g., interference management in cognitive radio systems and user behavior learning in ad hoc wireless networks. However, obtaining the locations of these nodes in particular in frequency-division duplex systems is challenging, since the localization network usually does not know the spectrum that the Rx uses for backward transmission. In this paper, we propose to use the full-duplex relay technique to localize a noncooperative Rx, which does not require the knowledge of the Rx’s backward transmission spectrum. In the proposed method, localization sensors alternatively act as a full-duplex amplify-and-forward relay to trigger the power control of the Tx–Rx link. Then, by detecting the power adjustment of the Tx, each localization sensor can estimate the time difference of arrival between the direct and relay signals. Finally, the Rx location can be calculated from triangulation. Simulation results show that the proposed method can effectively localize the Rx, which validates its potential for receiver-aware applications and services

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

Systematic Comparison of Structural Characterization of Polysaccharides from <i>Ziziphus Jujuba cv. Muzao</i>

To investigate the structural information differences of Ziziphus Jujuba cv. Muzao polysaccharides, ten samples were successfully extracted from aqueous and alkaline solutions, prepared via DEAE-Sepharose Fast Flow through different eluents and Sephacryl S-300 columns, and systematically analyzed. Their characteristics were studied and then compared using chemical testing, high-performance gel permeation chromatography (HPGPC), gas chromatography (GC), methylation analysis, and NMR spectroscopy. The data achieved demonstrated that different jujube polysaccharide fractions possessed different structural characteristics, and most of them belonged to pectic polysaccharides. Overall, the structural information difference of jujube polysaccharides was preliminarily illuminated, which could not only promote the potential application of Z. Jujuba cv. Muzao polysaccharides but also provide an effective way to analyze the structures of polysaccharides from other genera jujube fruit

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