Enchang Sun

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.

Random Access and Virtual Resource Allocation in Software-Defined Cellular Networks With Machine-to-Machine Communications

Machine-to-machine (M2M) communications have attracted great attention from both academia and industry. In this paper, with recent advances in wireless network virtualization and software-defined networking (SDN), we propose a novel framework for M2M communications in software-defined cellular networks with wireless network virtualization. In the proposed framework, according to different functions and quality-of-service (QoS) requirements of machine-type communication devices, a hypervisor enables the virtualization of the physical M2M network, which is abstracted and sliced into multiple virtual M2M networks. In addition, we develop a decision-theoretic approach to optimize the random access process of M2M communications. Furthermore, we develop a feedback and control loop to dynamically adjust the number of resource blocks that are used in the random access phase in a virtual M2M network by the SDN controller. Extensive simulation results with different system parameters are presented to show the performance 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.

Random Access Optimization for M2M Communications in VANET with Wireless Network Virtualization

With the growing interest in the use of internet of things (IoT), machine-to-machine (M2M) communications have become an important networking paradigm. In this paper, with recent advances in wireless network virtualization (WNV), we propose a novel framework for M2M communications in vehicular ad-hoc networks (VANETs) with WNV. In the proposed framework, according to different applications and quality of service (QoS) requirements of vehicles, a hypervisor enables the virtualization of the physical vehicular network, which is abstracted and sliced into multiple virtual networks. Moreover, the process of resource blocks (RBs) selection and random access in each virtual vehicular network is formulated as a partially observable Markov decision process (POMDP), which can achieve the maximum reward about transmission capacity. The optimal policy for RBs selection is derived by virtue of a dynamic programming approach. Extensive simulation results with different system parameters are presented to show the performance improvement of the proposed scheme.

Evidence Theory Based Self-Interference Suppression for Two-Way Full-Duplex MIMO Relays

In this paper, a novel self-interference (SI) suppression scheme based on Dempster-Shafer (D-S) evidence theory is proposed to cancel self-interference in two-way full-duplex (FD) MIMO relay. D-S evidence theory can appropriately characterize uncertainty and make full use of multiple evidence source information by Dempsters combination rule to obtain reliable decisions. Instead of traditional spatial-domain suppression schemes, the proposed DS-Sum and Difference(SAD)-PNC scheme adopts D-S evidence theory to detect the sum and difference signal for two source nodes considering the SI cancellation in obtaining basic probability assignment (BPA) function in the multiple access (MA) phase. For comparison, Log-Likelihood-Ratio (LLR) combining technique is extended for FD mode with SI suppression considered in soft information computation for network-coded symbol. In the broadcast (BC) phase, antenna selection scheme is adopted to achieve full transmit diversity gain. Simulation results reveal that the proposed DS-SAD-PNC scheme obtains better end-to-end average bit error rate (BER) performance compared with extended MIMO-LLR-PNC and traditional spatial-domain suppression schemes like ZF and MMSE with a little complexity increased.

An Energy-Efficient User Location-Aware Switch-Off Method for LTE-A Cellular Networks

With the rapid development of information and communication technology, the communication networks have been more efficient and more energy-intensive. In order to decrease the energy consumption, we propose a distributed switch-off method, based on the user equipments (UEs) locations and minimax algorithm, for the orthogonal frequency division multiplexing access-based cellular networks. For the sake of obtaining a nearly optimal result, the minimax algorithm adopted the full search manner and brought higher complexity meanwhile. In the proposed method, the complexity of the minimax algorithm is decreased by narrowing the search range according to the locations of UEs. Furthermore, in order to improve energy efficiency (EE), the numbers of UEs within cells and the load factor (LF) of base stations (BSs) are jointly considered as the measure factors to switch off the appropriate BSs. Simulation results demonstrate that the proposed method can decrease the complexity with a little sacrifice of EE performance, and the joint consideration of the UEs number and LF can improve the EE effectively.

Optimal transmission behavior policy of secondary users in proactive-optimization cognitive radio networks

In cognitive radio (CR) networks, there is a common assumption that the secondary devices always obey the spectrum access rules and are under full control. However, this may become unrealistic for future CR networks composed of intelligent, complicated and autonomous devices. To solve this problem, the concept of “proactive-optimization” cognitive radio (POCR) is proposed in this paper, in which the highly-intelligent secondary users proactively optimize their own behavior decisions according to the available information including device state and network condition to maximize their long-term reward. Furthermore, we propose an optimal transmission behavior decision scheme for secondary users in POCR networks considering imperfect spectrum channel sensing results. Specifically, we formulate the system as a partially-observable Markov decision process (POMDP) problem. With this formulation, a low complexity dynamic programming framework is introduced to obtain the optimal behavior policy. Extensive simulation results are presented to illustrate the significant performance improvement of the proposed scheme compared with the existing one that ignores the secondary user behavior optimization.

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.