Gongpu Wang

Ambient Backscatter Communication Systems: Detection and Performance Analysis

Ambient backscatter technology that utilizes the ambient radio frequency signals to enable the communications of battery-free devices has attracted much attention recently. In this paper, we study the problem of signal detection for an ambient backscatter communication system that adopts the differential encoding to eliminate the necessity of channel estimation. Specifically, we formulate a new transmission model, design the data detection algorithm, and derive two closed-form detection thresholds. One threshold is used to approximately achieve the minimum sum bit error rate (BER), while the other yields balanced error probabilities for “0” bit and “1” bit. The corresponding BER expressions are derived to fully characterize the detection performance. In addition, the lower and the upper bounds of BER at high signal-to-noise ratio regions are also examined to simplify a performance analysis. Simulation results are then provided to corroborate the theoretical studies.

High-Speed Railway Communications: From GSM-R to LTE-R

High-speed railways (HSRs) improve the quality of rail services, yield greater customer satisfaction, and help to create socioeconomically balanced societies [1]. This highly efficient transport mode creates significant challenges in terms of investment, technology, industry, and environment. To handle increasing traffic, ensure passenger safety, and provide real-time multimedia information, a new communication system for HSR is required. In the last decade, public networks have been evolving from voice-centric second-generation systems, e.g., Global System for Mobile Communications (GSM) with limited capabilities, to fourth-generation (4G) broad-band systems that offer higher data rates, e.g., long-term evolution (LTE). It is thus relevant for HSR to replace the current GSM-railway (GSM-R) technology with the next-generation railway-dedicated communication system providing improved capacity and capability.

Noncoherent Detections for Ambient Backscatter System

Ambient backscatter, an emerging communication mechanism where battery-free devices communicate with each other via backscattering ambient radio frequency (RF) signals, has achieved much attention recently because of its desirable application prospects in the Internet of Things. In this paper, we formulate a practical transmission model for an ambient backscatter system, where a tag wishes to send some low-rate messages to a reader with the help of an ambient RF signal source, and then provide fundamental studies of noncoherent symbol detection when all channel state information of the system is unknown. For the first time, a maximum likelihood detector is derived based on the joint probability density function of received signal vectors. In order to ease availability of prior knowledge of the ambient RF signal and reduce computational complexity of the algorithm, we design a joint-energy detector and derive its corresponding detection threshold. The analytical bit error rate (BER) and BER-based outage probability are also obtained in a closed form, which helps with designing system parameters. An estimation method to obtain detection-required parameters and comparison of computational complexity of the detectors are presented as complementary discussions. Simulation results are provided to corroborate theoretical studies.

Acquisition of channel state information in heterogeneous cloud radio access networks: challenges and research directions

As an emerging system architecture, heterogeneous cloud radio access networks (H-CRANs) can improve system capacity, enlarge coverage, and enhance energy/spectral efficiency. Meanwhile, this newborn architecture also brings many open problems for traditional topics, including synchronization, channel estimation, and data detection. In this article, we present a comprehensive analysis on obtaining CSI in H-CRANs. Specifically, we recognize seven challenges in channel estimation that are caused by a large number of channel parameters, heterogeneity of access nodes in H-CRANs, and the time delays among different nodes. Several research directions for handling these challenges are also proposed, for example, array signal processing and channel compression can eliminate the number of channel estimates, while channel prediction and modification for high-speed railway communications and adaptive downlink array from uplink measurements excel in overcoming the non-reciprocity in channel parameters.

Uplink Detection and BER Analysis for Ambient Backscatter Communication Systems

Ambient backscatter is a new communication technology that utilizes ambient radio frequency signals to enable battery-free devices to communicate with each other. In this paper, we study the problem of signal detection and bit error rate (BER) performance for this new communication system where the differential encoding is adopted to eliminate the necessity of channel estimation. We formulate a new transmission model, design the data detection approach, and derive the optimal/approximate closed-form detection thresholds. In addition, the performance at high signal-to-noise region (SNR) is also analyzed, where the lower and the upper bounds of BERs are found. Simulation results are then provided to corroborate our theoretical studies.

Signal detection and BER analysis for RF-powered devices utilizing ambient backscatter

Devices that harvest power from radio-frequency (RF) signals are generally referred to as RF-powered devices. One emerging technology that enables RF-powered devices to communicate with others is ambient backscatter. In this paper, we study the problem of signal detection and analyse the uplink bit error rate (BER) performance for RF-powered devices utilizing ambient backscatter. Specifically, we build up a theoretical model for a communication system which consists of one reader and one tag. The tag employs ambient backscatter to communicate with the reader. Next we design an optimal detector which can minimize the BER and find the closed-form expression for the detection threshold. Noting that the optimal detector cannot result in equal BERs in detect “0” or “1”, therefore we design another detector that can achieve the same error probability in detecting “0” with that in detecting “1”. Moreover, we analyse the BER performance for both detectors. Finally, simulations are provided to corroborate the proposed studies.

Cognitive transmission and performance analysis for Amplify-and-Forward two-way relay networks

In this paper, we propose a cognitive transmission scheme for Amplify-and-Forward (AF) two-way relay networks (TWRNs) and investigate its joint sensing and transmission performance. Specifically, we derive the overall false alarm probability, the overall detection probability, the outage probability of the cognitive TWRN over Rayleigh fading channels. Furthermore, based on these probabilities, the spectrum hole utilization efficiency of the cognitive TWRN is defined and evaluated. It is shown that smaller individual or overall false alarm probability can result in less outage probability and thus larger spectrum hole utilization efficiency for cognitive TWRN, and also produce more interference to the primary users. Interestingly, it is found that given data rate, more transmission power for the cognitive TWRN does not necessarily obtain higher spectrum hole utilization efficiency. Moreover, our results show that a maximum spectrum hole utilization efficiency can be achieved through an optimal allocation of the time slots between the spectrum sensing and data transmission phases. Finally, simulation results are provided to corroborate our proposed studies.

Signal detection of ambient backscatter system with differential modulation

We study the problem of signal detection for the ambient backscatter system (ABS) when data are transmitted with differential modulation. An implementation of the maximum likelihood (ML) detection algorithm is proposed. To reduce the computational complexity, we further design a suboptimal detector and derive its bit error rate (BER) closed-form expression. Moreover, both the upper and the lower bounds of the BER, which can tell more insight of how system parameters affect the detection performance, are obtained. Simulations are then provided to corroborate the studies.

Cyclostationary Detection Based Spectrum Sensing for Cognitive Radio Networks

In this paper, cyclostationary detection Based spectrum sensing is considered for cognitive radio networks. We first summarize the existing first-order and second-order cyclostationary detection algorithms, which can be considered as a brief tutorial on detection theory of the cyclostationary signals. Based on this, we propose a cooperative spectrum sensing method for a cognitive radio networks with multiple terminals and one fusion center. It is shown that the proposed method have reliable performance even in low signal-to-noise ratio (SNR) region. It is also found that the increasing number of secondary users (SUs) can result in improved detection performance, especially at low SNR. Simulation results are then provided to corroborate the proposed studies. Index Terms—Cognitive radio, cooperative spectrum sensing, cyclostationary detection.

Signal detection for ambient backscatter system with multiple receiving antennas

“Ambient backscatter” is a new communication technology that utilizes ambient radio frequency signals to enable battery-free devices to communicate with each other. In this paper, we formulate a new transmission model when the reader is equipped with multiple antennas and propose a new way for signal detection when the channel state information is unknown. We derive an approximate closed-form detection threshold to identify the transmitted symbols and also analyze the corresponding bit error rate (BER) performance. It is found that increasing number of receiving antennas will lead to lower BER, while there exists an error floor when the antenna number is above certain level. Finally, simulation results are provided to corroborate our theoretical studies.