Ruizhe Yang

Cooperative and distributed spectrum sharing in dynamic spectrum pooling networks

In dynamic spectrum access systems, such as cognitive radio networks, spectrum pooling is one of the approaches to manage the available spectrum bands from different licensed networks. Based on the concept of spectrum pooling, most previous work focuses on the system architecture and the design of flexible access algorithms and schemes. In this paper, a cooperative and distributed scheme for dynamic internetwork spectrum sharing among multiple networks is proposed, taking into account the spectrum access price and the spectrum efficiency. Specifically, the spectrum sharing problem is formulated as a restless bandits model-based optimization system, which dramatically reduces the complexity of the scheme by allowing the spectrum allocation scheme to be simply select the network with the lowest index. Extensive simulation results illustrate that the proposed scheme improves the performance significantly compared to the existing scheme that ignores the distributed and cooperative spectrum sharing.

Raised Cosine-Like Companding Scheme for Peak-to-Average Power Ratio Reduction of SCFDMA Signals

The 3rd generation partnership project long term evolution standard uses orthogonal frequency division multiplexing access in downlink and single carrier frequency division multiple access (SCFDMA) scheme for the uplink transmissions, which utilizes single carrier modulation and frequency domain equalization. In this paper, we proposed a Raised Cosine-like companding scheme to reduce the peak-to-average power ratio (PAPR) of SCFDMA signals. The proposed scheme can transform the original SCFDMA signals into Raised Cosine-like-distributed. Moreover, this scheme can compress the large signals, while maintaining the average power constant. Computer simulation results show that the proposed companding scheme can offer better PAPR reduction by properly choosing the parameters.

DaVe: Offloading Delay-Tolerant Data Traffic to Connected Vehicle Networks

The promising connected vehicle technologies will enable a huge network of roadside units (RSUs) and vehicles equipped with communication, computing, storage, and positioning devices. Current research on connected vehicle networks focuses on delivering the data generated from or required by the vehicle networks themselves, of which the data traffic is light; thus, the vehicle-network resource utilization efficiency is low. On the other hand, a large amount of delay-tolerant traffic in other data networks consumes significant communication resources. In this paper, we introduce a new architecture of DaVe to utilize efficiently the potential resource from connected vehicles and to mitigate the congestion problem in other data networks. Delay-tolerant data traffic is offloaded from the data networks to the connected vehicle networks without extra infrastructure/hardware deployment. An optimal distributed data hopping mechanism is also proposed to enable delay-tolerant data routing over connected vehicle networks. We formulate the next-hop decision optimization problem as a partially observable Markov decision process (POMDP) and propose a heuristic algorithm to reduce computational complexity. Extensive simulation results are also presented to demonstrate the significant performance improvement of the proposed scheme.

Iterative channel estimation and detection for fast time-varying MIMO-OFDM channels

This paper is concerned with the challenging problem of joint channel estimation and data detection for high mobility multiple-input multiple-output orthogonal frequency division multiplexing systems. We propose a new iterative channel estimation and detection scheme, which reduces the unexpected effects of both detection errors and channel estimation errors. Detection errors in channel estimation are analyzed and transformed as part of the noise. To filter this equivalent noise by Kalman estimator, we derive the covariance of both the channels and data errors in detection. Besides, we propose a new detection algorithm with an optimized weight to minimize the detection error caused by channel estimation errors. To obtain this optimized weight, the error covariance of the estimated channels is derived from the error estimate covariance matrix in Kalman estimator. Simulation results are presented to demonstrate the significant performance improvement in joint channel estimation and data detection with the proposed iterative scheme.

Power Function Companding Scheme for Peak-to-Average Power Ratio Reduction of SC-FDMA Signals

The 3rd generation partnership project (3GPP) long term evolution (LTE) standard has adopted orthogonal frequency division multiplexing access (OFDMA) in downlink and single carrier-frequency division multiple access (SC-FDMA) scheme for the uplink transmissions, which utilizes single carrier modulation and frequency domain equalization. In this paper, we proposed a power-function companding scheme to reduce the peak-to-average power ratio (PAPR) of SC-FDMA signals. The proposed companding scheme can transform the original SC-FDMA signals into power-function-distributed. Moreover, the scheme can compress the large signals, while maintaining the average power constant. Computer simulation results show that the proposed companding scheme can offer better PAPR reduction by properly choosing the control parameters.

Raised Cosine-like companding scheme for peak-to-average power ratio reduction of SCFDMA signals

The 3rd generation partnership project (3GPP) long term evolution (LTE) standard has adopted orthogonal frequency division multiplexing access (OFDMA) in downlink and single carrier frequency division multiple access (SCFDMA) scheme for the uplink transmissions, which utilizes single carrier modulation and frequency domain equalization. In this paper, we proposed a Raised Cosine-like companding scheme to reduce the peak-to-average power ratio (PAPR) of SCFDMA signals. The proposed scheme can transform the original SCFDMA signals into Raised Cosine-like-distributed. Moreover, the scheme can compress the large signals, while maintaining the average power constant. Computer simulation results show that the proposed companding scheme can offer better PAPR reduction by properly choosing the parameters.

Navigation Data-Assisted Opportunistic Spectrum Scheduling for Network-Based UAV Systems: A Parallel Restless Bandits Formulation

AbstractA myriad of applications and services of information and communication technology (ICT) has been developed in the past decades, within which networks are the fundamental architecture to connect people and things. As one of the network-based ICT applications, recently, unmanned aerial vehicle (UAV) cooperation systems have attached much attention due to their successful applications in complex military and civilian missions. In this paper, we propose a navigation data-assisted optimal opportunistic spectrum access scheme for wireless communications in heterogeneous UAV networks, to achieve maximized long-term data rate by flexibly scheduling the spectrum subbands. Thanks to the navigation data that is always available locally at the entities in the network, rough prediction of wireless link quality can be obtained to assist subband allocations. Furthermore, to formulate the optimal spectrum scheduling problem, we develop a parallel restless bandits model, which can reduce the NP-hard optimization problem to simply selecting the link with the minimum index in the online stage. Extensive simulation results are also presented to demonstrate the significant performance improvement of the proposed scheme compared to the existing one.

Spectrum Pooling-Based Optimal Internetwork Spectrum Sharing for Cognitive Radio Systems

This work was supported in part by the National Natural Science Foundation of China under Grant 60832009.} Spectrum pooling, which allows the secondary networks to utilize the available spectrum bands from different licensed networks, is one of the most promising technologies for dynamic spectrum sharing in cognitive radio systems. Most previous work on spectrum pooling concentrates on the system architecture and the design of flexible access algorithms and schemes. In this paper, a distributed scheme for optimal internetwork spectrum sharing among multiple cognitive radio systems is proposed. Besides, the spectrum access price and spectrum efficiency are considered as the design criteria in the proposed scheme. The spectrum sharing problem is formulated as a restless bandits system, which dramatically reduces the computational complexity by simply allocating the new available band to the secondary network with the lowest index. Furthermore, extensive simulation results illustrate the significant performance improvement of the proposed scheme improves compared to the existing scheme.

Dynamic spectrum management for heterogeneous UAV networks with navigation data assistance

Recently, unmanned aerial vehicle (UAV) cooperation networks have attached much attention due to their successful applications in complex military and civilian missions. In this paper, we propose a navigation data-assisted optimal opportunistic spectrum access scheme for wireless communications in heterogeneous UAV networks, to achieve maximized data rate by flexibly scheduling the spectrum subbands. The system architecture is introduced, and thanks to the navigation data that is always available locally at the entities in the network, prediction of wireless link quality and routing information can be obtained to assist subband allocations. Furthermore, the spectrum allocation process is formulated as an optimization problem. Simulation results are also presented to demonstrate the significant performance improvement of the proposed scheme compared to the existing one.

Analysis of nonlinear companding schemes for papr reduction of SC-FDMA signals

The 3rd generation partnership project (3GPP) long term evolution (LTE) standard uses orthogonal frequency division multiplexing access (OFDMA) in downlink and single carrier frequency division multiple access (SC-FDMA) scheme for the uplink transmissions, which utilizes single carrier modulation and frequency domain equalization. In this paper, we compared and analyzed the performance of the nonlinear companding schemes, i.e., Raised-Cosine-like scheme and power function scheme, to reduce the peak-to-average power ratio (PAPR) of SC-FDMA signals, and summarized the nonlinear features that the schemes should have. Both the nonlinear schemes could transform the original SC-FDMA signals into nonlinear-distributed. Moreover, the schemes can compress the large input signals, while maintaining the average power constant. Computer simulation results show that the PAPR reduction performance of the power function scheme is better than that of the Raised-Cosine-like scheme.