Spectrum Allocation and Performance Analysis for Backhauling of UAV Assisted Cellular Network

To reinforce the coverage and QoS(quality of service) of on-ground cellular communication system, unmanned aerial vehicles which are carrying small cells are deployed in some emergency and disaster areas. Although ASCs(aerial small cells) can provide a higher probability of LoS(line-of-sight) transmission, the wireless backhaul link will bring extra interference to the whole system if not well designed. Therefore, in this paper, we study the backhaul scheme for UAV-assist cellular network. We first analyze the interference environments of UAV-assist cellular network considering the IBOG(In-Band to On-Ground), OBOG(Out-of-Band to On-Ground) and IBTU(In-Band to Tethered-UAV) backhauling mode, and give the descriptions of the performance metrics for each mode. Then, the considered problem is formulated as an optimization of achievable rate. We derive the optimal solutions for the involved three backhauling modes for ASCs respectively, and closed-form optimal value for each mode is acquired with proof. We also give a pseudo-code form of our proposed optimal access/backhaul spectrum allocation algorithm. The simulation results indicate that the proposed scheme can deliver a significant gain, while IBTU performs best among proposed backhauling modes.

A Virtual TDOA Localization Scheme of Chinese DTMB Signal in Radio Monitoring Networks

As the radio communications technology widely used,wireless location technology plays a more important role in maintaining the order of the air waves.However concretely effective symbol calibration method with regard to Chinese DTMB signal of different frame mode is quite under research due to the multiple structure of DTMB signal.In this paper,we propose a Time Difference of Arrival(TDOA)-based passive location scheme using least square principle.Utilizing the large number of anchor nodes in wireless monitoring network,a novel algorithm is formulated to solve the None-LineOf-Sight problem.The derived Cramer Rao Lower Bound of the localization method guides to the accuracy of the position outcome with regards to the calibration precision.In contrast with traditional multi-terminal location schemes,our location scheme can reduce calculation complexity and location costs abruptly.A twostep NLOS identification algorithm is proposed.Computer simulation is employed to verify the well performance of the calibration method of3-4 dB superiority than normal method and also the whole localization scheme for less than 50 meters through channel of SNR lower than dB.Simulation also shows that our algorithm can effectively identify NLOS path and improve positioning accuracy.

Space-Time Correlation Based Fast Regional Spectrum Sensing in Cognitive Radio

In this paper,a space-time correlation based fast regional spectrum sensing(RSS)scheme is proposed to reduce the time and energy consumption of traditional spatial spectrum sensing. The target region is divided into small meshes,and all meshes are clustered into highly related groups using the spatial correlation among them. In each group,some representative meshes are selected as detecting meshes(DMs)using a multi-center mesh(MCM)clustering algorithm,while other meshes(EMs)are estimated according to their correlations with DMs and the Markov modeled dependence on history by MAP principle. Thus,detecting fewer meshes saves the sensing consumption. Since two independent estimation processes may provide contradictory results,minimum entropy principle is adopted to merge the results. Tested with data acquired by radio environment mapping measurement conducted in the downtown Beijing,our scheme is capable to reduce the consumption of traditional sensing method with acceptable sensing performance.

Power Ramping Schemes for M2M and H2H Co-existing Scenario

To analyze and reduce the impact of Machine-to-Machine (M2M) Devices (MDs) on the traditional Human-to-Human (H2H) users for the blending scenario, where both M2M and H2H services coexist in the current Universal Mobile Telecommunication System (UMTS) and perform the Random Access (RA) procedure simultaneously, a comprehensive RA analysis model of RA is proposed in this paper. Further, a power ramping strategy based on the logarithm for M2M is proposed. The efficiency of both the existing and proposed scheme is assessed through a simulation across several metrics, including average target power, throughput, blocking probability, and delay statistics. Numerical results show that the proposed algorithm can ensure a minimal impact on H2H communication while maintaining the throughput of the M2M communication. Meanwhile, because of its low energy consumption, this algorithm has a significant guide value for real-world applications.

Intelligent and efficient development of wireless networks:A review of cognitive radio networks

Facing the challenges on how to improve spectrum efficiency and how to realize heterogeneous network convergence in future wireless networks,a cognitive radio network(CRN) is proposed as one of the solutions.This has become a major research topic in recent years and it is timely to give an overview of the development of CRN and to summarize key issues and technologies.The fundamental concepts of CRN,including the cognitive cycle model,the network architecture,and the cognitive ability and intelligent decision functions,are introduced in detail based on recent advances.Key issues for each topic,followed with recent research on theory and method,are then classified and the industrialization developments of CRN testbeds based on TD-LTE cellular system and standards are briefly presented.Finally,conclusions are reached on the perspectives and directions of future development.

Reconfiguration decision making in cognitive wireless network

Facing the challenges of dynamic adaptation capabilities in the time-varying environment of cognitive wireless networks(CWNs),we introduce reconfiguration capabilities that flexibly and dynamically adapt to changing wireless environments and service requirements.As an essential characteristic of CWNs,the cognitive reconfiguration can meet user requirements,realize interoperability between heterogeneous networks,make full use of radio resources and adapt to time-varying environments to achieve end-to-end requirements.However,the reconfiguration implementation is still challenging due to the need for complex environment cognition,multi-objective optimization,autonomic decision-making and end-to-end requirement extraction.As an intelligent technology for solving complex issues,we apply adaptive neuro-fuzzy inference system(ANFIS) techniques in this paper to address these challenges in cognitive reconfiguration for self-learning and optimal decision making based on multi-domain cognition results.Moreover,this paper designs a generic ANFIS cognitive reconfiguration system including three functional entities,which are the context management module,multi-domain database and ANFIS optimization module.Finally,numerous results prove the effective performance improvements of the ANFIS based reconfiguration solution in CWN for global end-to-end goals.

Cognitive information metrics for cognitive wireless networks

Considering the dynamic changes and uncertainty features of the radio environment in cognitive wireless networks(CWNs),the environment cognition ability is critical for the performance evaluation of CWNs design and optimization.However,there are no effective metrics to evaluate the ability and gain of information cognition in CWNs from an information theory perspective.Therefore,the novel cognitive information concept is proposed and defined as a metric to evaluate the uncertainty of both the internal and external environments of one system that can be removed by other systems or nodes using cognitive radio techniques.As an intelligent wireless communication system that is aware of its surrounding radio,network,and user multi-domains environment,the more cognitive information it achieves,the higher level cognitive capability it is.In this paper,we define and analyze the mathematical features of cognitive information.Results reveal that the increase of cognitive information can improve the spectrum efficiency and reduce the interference probability simultaneously in CWNs.Thus cognitive information can be regarded as a metric for CWNs optimization.Finally,we apply the theory of cognitive information in the parameters optimization in energy detection and cooperative spectrum sensing.

Fractal theory based dynamic mesh grouping scheme for efficient cognitive pilot channel design

As one of the key characteristics in cognitive wireless networks(CWNs),network environment awareness techniques have received much attention recently.Instead of traditional spectrum sensing technology that suffers from problems of miss detection,false alarm,hidden node,and inefficiency,cognitive pilot channel(CPC) technology has been proposed as one of the candidate solutions for an efficient and accurate network information delivery scheme to user equipment(UE).The aim of the CPC technology is to provide the necessary information for the reconfiguration of the UE using the public signaling channel.To ensure the efficient information delivery,the whole geographical area covered by the CPC is divided into square meshes of the same size.Moreover,two typical network information transmission modes for CPC deployment are also proposed:broadcast CPC mode and on-demand CPC mode.To further improve the efficiency of network information delivery,an efficient dynamic mesh grouping scheme has been designed which is based on the fractal theory for the broadcast CPC mode,where adaptive rectangular sized meshes are used to approximately cover the whole area.Compared to the traditional fixed size mesh division strategy,results show that the proposed dynamic mesh grouping scheme significantly reduces the number of meshes by grouping similar meshes together,and the average delay of receiving CPC information on the UE side is therefore reduced.

Energy-efficient relay selection and optimal relay location in cooperative cellular networks with asymmetric traffic

Energy-efficient communication is an important requirement for mobile relay networks due to the limited battery power of user terminals. This paper considers energy-efficient relaying schemes through selection of mobile relays in cooperative cellular systems with asymmetric traffic. The total energy consumption per information bit of the battery-powered terminals,i.e.,the mobile station （MS） and the relay,is derived in theory. In the joint uplink and downlink relay selection （JUDRS） scheme we proposed,the relay which minimizes the total energy consumption is selected. Additionally,the energy-efficient cooperation regions are investigated,and the optimal relay location is found for cooperative cellular systems with asymmetric traffic. The results reveal that the MS-relay and the relay-base station （BS） channels have different influence over relay selection decisions for optimal energy-efficiency. Information theoretic analysis of the diversity-multiplexing tradeoff （DMT） demonstrates that the proposed scheme achieves full spatial diversity in the quantity of cooperating terminals in this network. Finally,numerical results further confirm a significant energy efficiency gain of the proposed algorithm comparing to the previous best worse channel selection and best harmonic mean selection algorithms.

Unitary space vector quantization codebook design for spatial correlated limited feedback MIMO system

In the transmitting, beamforming, and receiving combing （TBRC） MIMO system, a codebook based feedback strategy is usually used to provide the transmitter with the beamforming vector. The adopted codebook affects the system performance considerably. Therefore, the codebook design is a key technology in the TBRC MIMO system. In this article, the unitary space vector quantization （USVQ） codebook design criterion is proposed to design optimal codebooks for various spatial correlated MIMO channels. And the unitary space K-mean （USK） codebook generating algorithm is provided to generate the USVQ codebooks. Simulations show that the capacities of the feedback based TBRC systems using USVQ codebooks are very close to those of the ideal cases.

A novel TOA estimation method with effective NLOS error reduction

It is well known that non-line-of-sight （NLOS） error has been the major factor impeding the enhancement of accuracy for time of arrival （TOA） estimation and wireless positioning. This article proposes a novel method of TOA estimation effectively reducing the NLOS error by 60%, comparing with the traditional timing and synchronization method. By constructing the orthogonal training sequences, this method converts the traditional TOA estimation to the detection of the first arrival path （FAP） in the NLOS multipath environment, and then estimates the TOA by the round-trip transmission （RTT） technology. Both theoretical analysis and numerical simulations prove that the method proposed in this article achieves better performance than the traditional methods.

Non-line-of-sight error mitigating algorithm based on scattering models via multi-antenna system

In urban environment with serious blocking of direct paths, the non-line-of-sight （NLOS） propagation influences the location estimation accuracy. In this article, a novel algorithm is developed, which can mitigate the NLOS errors in location estimation significantly. Utilizing multiantenna array, the information of scatterers that cause the NLOS propagation is obtained. Then, we combine the information with TOA/TDOA based location algorithm to estimate the location of mobile station （MS）. The simulation results show that our method can mitigate NLOS errors and enhance the location accuracy greatly.