BtPDR: Bluetooth and PDR-Based Indoor Fusion Localization Using Smartphones

( Yingbiao Yao ),( Qiaojing Bao ),( Qi Han ),( Ruili Yao ),( Xiaorong Xu ),( Junrong Yan ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.8

This paper presents a Bluetooth and pedestrian dead reckoning (PDR)-based indoor fusion localization approach (BtPDR) using smartphones. A Bluetooth and PDR-based indoor fusion localization approach can localize the initial position of a smartphone with the received signal strength (RSS) of Bluetooth. While a smartphone is moving, BtPDR can track its position by fusing the localization results of PDR and Bluetooth RSS. In addition, BtPDR can adaptively modify the parameters of PDR. The contributions of BtPDR include: a Bluetooth RSS-based Probabilistic Voting (BRPV) localization mechanism, a probabilistic voting-based Bluetooth RSS and PDR fusion method, and a heuristic search approach for reducing the complexity of BRPV. The experiment results in a real scene show that the average positioning error is < 2m, which is considered adequate for indoor location-based service applications. Moreover, compared to the traditional PDR method, BtPDR improves the location accuracy by 42.6%, on average. Compared to state-of-the-art Wireless Local Area Network (WLAN) fingerprint + PDR-based fusion indoor localization approaches, BtPDR has better positioning accuracy and does not need the same offline workload as a fingerprint algorithm.

Optimization Algorithm for Spectrum Sensing Delay Time in Cognitive Radio Networks Using Decoding Forward Relay

( Kaili Xia ),( Xianyang Jiang ),( Yingbiao Yao ),( Xianghong Tang ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.3

Using decode-and-forward relaying in the cognitive radio networks, the spectrum efficiency can improve furthermore. The optimization algorithm of the spectrum sensing estimation time is presented for the cognitive relay networks in this paper. The longer sensing time will bring two aspects of the consequences. On the one hand, the channel parameters are estimated more accurate so as to reduce the interferences to the authorized users and to improve the throughput of the cognitive users. On the other hand, it shortens the transmission time so as to decease the system throughput. In this time, it exists an optimal sensing time to maximize the throughput. The channel state information of the sub-bands is considered as the exponentially distributed, so a stochastic programming method is proposed to optimize the sensing time for the cognitive relay networks. The computer simulation results using the Matlab software show that the algorithm is effective, which has a certain engineering application value.

Energy-efficient Buffer-aided Optimal Relay Selection Scheme with Power Adaptation and Inter-relay Interference Cancellation

( Xiaorong Xu ),( Liang Li ),( Yingbiao Yao ),( Xianyang Jiang ),( Sanqing Hu ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.11

Considering the tradeoff between energy consumption and outage behavior in buffer-aided relay selection, a novel energy-efficient buffer-aided optimal relay selection scheme with power adaptation and Inter-Relay Interference (IRI) cancellation is proposed. In the proposed scheme, energy consumption minimization is the objective with the consideration of relay buffer state, outage probability and relay power control, in order to eliminate IRI. The proposed scheme selects a pair of optimal relays from multiple candidate relays, denoted as optimal receive relay and optimal transmit relay respectively. Source-relay and relay-destination communications can be performed within a time-slot, which performs as Full-Duplex (FD) relaying. Markov chain model is applied to analyze the evolution of relay buffer states. System steady state outage probability and achievable diversity order are derived respectively. In addition, packet transmission delay and power reduction performance are investigated with a specific analysis. Numerical results show that the proposed scheme outperforms other relay selection schemes in terms of outage behavior with power adaptation and IRI cancellation in the same relay number and buffer size scenario. Compared with Buffer State relay selection method, the proposed scheme reduces transmission delay significantly with the same amount of relays. Average transmit power reduction can be implemented to relays with the increasing of relay number and buffer size, which realizes the tradeoff between energy-efficiency, outage behavior and delay performance in green cooperative communications.

Joint Subcarrier and Bit Allocation for Secondary User with Primary Users` Cooperation

( Xiaorong Xu ),( Yu-dong Yao ),( Sanqing Hu ),( Yingbiao Yao ) 한국인터넷정보학회 2013 KSII Transactions on Internet and Information Syst Vol.7 No.12

Interference between primary user (PU) and secondary user (SU) transceivers should be mitigated in order to implement underlay spectrum sharing in cognitive radio networks (CRN). Considering this scenario, an improved joint subcarrier and bit allocation scheme for cognitive user with primary users` cooperation (PU Coop) in CRN is proposed. In this scheme, the optimization problem is formulated to minimize the average interference power level at the PU receiver via PU Coop, which guarantees a higher primary signal to interference plus noise ratio (SINR) while maintaining the secondary user total rate constraint. The joint optimal scheme is separated into subcarrier allocation and bit assignment in each subcarrier via arith-metric geo-metric (AM-GM) inequality with asymptotical optimization solution. Moreover, the joint subcarrier and bit optimization scheme, which is evaluated by the available SU subcarriers and the allocated bits, is analyzed in the proposed PU Coop model. The performance of cognitive spectral efficiency and the average interference power level are investigated. Numerical analysis indicates that the SU`s spectral efficiency increases significantly compared with the PU non-cooperation scenario. Moreover, the interference power level decreases dramatically for the proposed scheme compared with the traditional Hughes-Hartogs bit allocation scheme.

Joint Beamforming and Power Splitting Design for Physical Layer Security in Cognitive SWIPT Decode-and-Forward Relay Networks

( Xiaorong Xu ),( Andi Hu ),( Yingbiao Yao ),( Wei Feng ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.1

In an underlay cognitive simultaneous wireless information and power transfer (SWIPT) network, communication from secondary user (SU) to secondary destination (SD) is accomplished with decode-and-forward (DF) relays. Multiple energy-constrained relays are assumed to harvest energy from SU via power splitting (PS) protocol and complete SU secure information transmission with beamforming. Hence, physical layer security (PLS) is investigated in cognitive SWIPT network. In order to interfere with eavesdropper and improve relay’s energy efficiency, a destination-assisted jamming scheme is proposed. Namely, SD transmits artificial noise (AN) to interfere with eavesdropping, while jamming signal can also provide harvested energy to relays. Beamforming vector and power splitting ratio are jointly optimized with the objective of SU secrecy capacity maximization. We solve this non-convex optimization problem via a general two-stage procedure. Firstly, we obtain the optimal beamforming vector through semi-definite relaxation (SDR) method with a fixed power splitting ratio. Secondly, the best power splitting ratio can be obtained by one-dimensional search. We provide simulation results to verify the proposed solution. Simulation results show that the scheme achieves the maximum SD secrecy rate with appropriate selection of power splitting ratio, and the proposed scheme guarantees security in cognitive SWIPT networks.

Performance Optimization and Analysis on P2P Mobile Communication Systems Accelerated by MEC Servers

( Xuesong Liang ),( Yongpeng Wu ),( Yujin Huang ),( Derrick Wing Kwan Ng ),( Pei Li ),( Yingbiao Yao ) 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.1

As a promising technique to support tremendous numbers of Internet of Things devices and a variety of applications efficiently, mobile edge computing (MEC) has attracted extensive studies recently. In this paper, we consider a MEC-assisted peer-to-peer (P2P) mobile communication system where MEC servers are deployed at access points to accelerate the communication process between mobile terminals. To capture the tradeoff between the time delay and the energy consumption of the system, a cost function is introduced to facilitate the optimization of the computation and communication resources. The formulated optimization problem is non-convex and is tackled by an iterative block coordinate descent algorithm that decouples the original optimization problem into two subproblems and alternately optimizes the computation and communication resources. Moreover, the MEC-assisted P2P communication system is compared with the conventional P2P communication system, then a condition is provided in closed-form expression when the MEC-assisted P2P communication system performs better. Simulation results show that the advantage of this system is enhanced when the computing capability of the receiver increases whereas it is reduced when the computing capability of the transmitter increases. In addition, the performance of this system is significantly improved when the signal-to-noise ratio of hop-1 exceeds that of hop-2.

Bidirectional Link Resource Allocation Strategy in GFDM-based Multiuser SWIPT Systems

( Xiaorong Xu ),( Minghang Sun ),( Wei-ping Zhu ),( Wei Feng ),( Yingbiao Yao ) 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.1

In order to enhance system energy efficiency, bidirectional link resource allocation strategy in GFDM-based multiuser SWIPT systems is proposed. In the downlink channel, each SWIPT user applies power splitting (PS) receiver structure in information decoding (ID) and non-linear energy harvesting (EH). In the uplink channel, information transmission power is originated from the harvested energy. An optimization problem is constructed to maximize weighted sum ID achievable rates in the downlink and uplink channels via bidirectional link power allocation as well as subcarriers and subsymbols scheduling. To solve this non-convex optimization problem, Lagrange duality method, sub-gradient-based method and greedy algorithm are adopted respectively. Simulation results show that the proposed strategy is superior to the fixed subcarrier scheme regardless of the weighting coefficients. It is superior to the heuristic algorithm in larger weighting coefficients scenario.