Jingqing Wang

Statistical QoS-Driven Resource Allocation over FD-SS Cooperative Cognitive Radio Networks

As a critical technique to support the multimedia services - the major traffic in cooperative cognitive radio networks (CRNs), the statistical quality-of-service (QoS) technique has been proved to be effective in statistically guaranteeing delay-bounded video transmissions over the time- varying wireless channels. On the other hand, in modern cooperative CRNs, the full-duplex spectrum sensing (FD-SS) scheme is designed to be a promising candidate technique for fully utilizing the channel spectrum while significantly enhancing the performance. However, how to efficiently integrate the FD-SS technique in supporting statistical QoS over cooperative CRNs imposes many new challenges not met before. To effectively overcome the above-mentioned difficulties, we propose the QoS-driven resource allocation scheme to implement FD-SS based multimedia services in cooperative CRNs. In particular, under the Nakagami-m channel model, we establish the cooperative spectrum sharing system model. We develop the FD-SS scheme and derive the probabilities of miss detection and false alarm for the proposed FD-SS scheme over cooperative CRNs. Given the statistical QoS constraints, we analyze the effective capacity and our proposed optimal resource allocation policy using the proposed FD-SS architecture over cooperative CRNs. Also conducted is a set of simulations which evaluate the system performance and show that our proposed resource allocation policy can achieve the optimality under the statistical delay-bounded QoS constraints over cooperative CRNs.

Adaptive Power Control for Maximizing Channel Capacity over Full-Duplex D2D Q-OFDMA Ad Hoc Networks

To support the emerging next generation wireless networks, researchers have made a great deal of efforts in investigating various promising techniques, such as full-duplex (FD) multiple-input and multiple-output (MIMO) technique and device-to-device (D2D) communications. FD MIMO technique can practically achieve the theoretical doubling of throughput if the self-interference can be efficiently cancelled. And D2D communication is designed and implemented to significantly enhance the FD communication performance by effectively reducing the overall interference and lowering transmit power over ad hoc networks. However, how to efficiently cancel the selfinterference induced by the FD MIMO transmissions under D2D communications has imposed many new challenges. To overcome the above-mentioned problems, we propose the adaptive power control policy for maximizing channel capacity over FD D2D QOFDMA ad hoc networks. In particular, under the Nakagami-m channel model, we establish the system model for the spatial multiplexing oriented Q-OFDMA system, and apply the selfinterference suppression techniques for FD model. We derive and analyze the energy efficiency for FD system over ad hoc networks. Then, we develop the adaptive power control policy for maximizing the MIMO channel capacity under our proposed spatial multiplexing based Q-OFDMA system over ad hoc networks. Also conducted is a set of simulations which show that our proposed scheme outperform the other existing schemes in terms of energy efficiency and self-interference cancellation over ad hoc networks.

Heterogeneous QoS-Driven Resource Adaptation over Full-Duplex Relay Networks

To support the emerging next era of mobile wireless networks, researchers have made a great deal of efforts in investigating promising techniques in multimedia services - the statistical quality-of-service (QoS) technique, which has been proved to be effective in statistically guaranteeing delay-bounded video transmissions over the time-varying wireless channels. On the other hand, as the 5G- promising techniques, the full-duplex (FD) technique can also significantly enhance the performance of statistical QoS for real-time traffic over 5G mobile wireless networks. However, due to the heterogeneity caused by different types of simultaneous traffics over the wireless FD relay links, supporting diverse delay-bounded QoS guarantees for wireless FD relay networks imposes many new challenges not encountered before. To effectively overcome the aforementioned problems, in this paper we propose the heterogeneous QoS-driven resource adaptation scheme by applying the full-duplex relaying scheme. In particular, under the Nakagami-m fading model, we establish the system model for the decode and forward (DF) protocol based FD relay system. Then, we propose the FD based relay selection model. Given the heterogeneous statistical QoS constraints, we derive and analyze the effective capacity under our developed optimal power-adaptation policies for the FD relays over 5G mobile wireless networks. Also conducted is a set of simulations which show that our proposed scheme outperforms the other existing schemes in terms of self- interference cancellation to efficiently implement the heterogeneous statistical QoS over FD relay networks.

3D percolation theory-based exposure-path prevention for optimal power-coverage tradeoff in clustered wireless camera sensor networks

With fast advances in camera sensor devices and wide applications of wireless camera sensor networks (WCSNs), optimizing the tradeoff between power consumption and coverage rate of WCSNs attracts a great deal of research attention. In contrast to 2D WCSNs, 3D WCSNs capture more accurate and comprehensive information for surveillant applications. The percolation theory has been proved to be powerful and effective in characterizing the exposure path prevention using 2D WCSNs. While percolation theory can be potentially extended into 3D WCSNs to improve the power and coverage performances, there are still many new challenges remaining unsolved. On the other hand, the clustering algorithm is widely cited as an efficient power saving and interference mitigation technique for WCSNs. However, how to integrate the clustering technique with 3D percolation theory in WCSNs is still an open problem. To overcome the aforementioned challenges, in this paper we propose the 3D percolation theory-based exposure-path prevention scheme for optimizing the tradeoff between power consumption and coverage rate over clustered WCSNs. First, we apply and extend the bond-percolation theory to derive the optimal density of camera sensors deployed in 3D WCSNs subject to the minimum exposure-path prevention probability constraint. Then, we apply the mutual entropy to analyze the dependency among 3D neighboring camera sensors, justifying the bond-percolation theory in 3D WCSNs. Finally, we apply the new low energy adaptive clustering hierarchy (LEACH) architecture into our 3D WCSNs for power saving and interference mitigation. The conducted extensive simulations show that our proposed schemes outperform the other existing schemes in optimizing the tradeoff between power consumption and coverage rate over 3D WCSNs.

Heterogeneous QoS-Driven Resource Allocation over MIMO-OFDMA Based 5G Cognitive Radio Networks

With the explosive development of the next era for mobile wireless networks, there has been a lot of studies in the promising techniques for multimedia services - the statistical quality-of-service (QoS) technique, which has been proved to be effective in statistically guaranteeing delay-bounded video transmissions over the time-varying wireless channels. On the other hand, as the 5G-promising techniques, multiple input multiple output-orthogonal frequency-division multiple access (MIMO-OFDMA) based cognitive radio schemes are proposed to significantly improve the system capacity while mitigate the interference for future dynamic spectrum access networks. However, due to the heterogeneity caused by different links of simultaneous traffics over the wireless relay, supporting diverse delay-bounded QoS guarantees for MIMO-OFDMA based cognitive radio networks (CRNs) imposes many new challenges not encountered before. To effectively overcome the aforementioned problems, in this paper we propose the heterogeneous QoS- driven resource allocation scheme by applying the MIMO-OFDMA based relaying scheme over CRNs. In particular, under the Nakagami-m fading model, we establish the MIMO-OFDMA based system model. Then, given the heterogeneous statistical QoS constraints, we derive and analyze the effective capacity under our developed optimal power-allocation policies for the MIMO- OFDMA based CRNs. Also conducted is a set of simulations which show that our proposed scheme outperforms the other existing schemes in terms of effective capacity to efficiently implement the heterogeneous statistical QoS over MIMO-OFDMA based CRNs.

Statistical QoS-Driven Cooperative Power Allocation Game over Wireless Cognitive Radio Networks

As a critical technique to support the multimedia services - the major traffic in cognitive radio networks (CRNs), the statistical quality-of-service (QoS) technique has been proved to be effective in statistically guaranteeing delay-bounded video transmissions over the time-varying wireless channels. On the other hand, in modern CRNs, cooperative spectrum sensing is shown to be able to greatly improve the sensing performance in cognitive radio networks. However, secondary users belonging to different service providers tend to be selfish and allocate their resources independently. Accordingly, challenges have been raised in applying the cooperative game to maximize the total network utility. To effectively overcome the above-mentioned challenges, we propose the QoS-driven power allocation scheme implementing the cooperative spectrum sensing game over CRNs. In particular, under the Nakagami-m channel model, we establish the cooperative spectrum sensing system model. Given the statistical QoS constraints, we analyze the effective capacity and Markov chain model for different sensing scenarios. We propose the QoS-aware cooperative power control game for cooperative spectrum sensing system over CRNs. Also conducted is a set of simulations which evaluate the system performance and show that our proposed resource allocation policy can achieve the optimality under the statistical delay-bounded QoS constraints over cooperative spectrum sensing CRNs.

Statistical QoS-Driven Power Adaptation over Q-OFDMA-Based Full-Duplex D2D 5G Mobile Wireless Networks

To support the emerging next generation wireless networks, researchers have made a great deal of efforts in investigating promising techniques in multimedia services - the statistical quality-of-service (QoS) technique, which has been proved to be effective in statistically guaranteeing delay-bounded video transmissions over the time-varying wireless channels. On the other hand, as the two 5G-promising candidate techniques, the multiple-input and multiple-output (MIMO) based full-duplex (FD) and device-to-device (D2D) can also significantly enhance the performance of statistical QoS for time- sensitive traffics over the 5G mobile wireless networks. However, how to efficiently integrate these advanced techniques in supporting statistical QoS impose many new challenges not met before. To effectively overcome the difficulties, in this paper we propose the QoS-driven power adaptation scheme by applying Quadrature- OFDMA (Q-OFDMA) to implement MIMO FD D2D based multimedia services in 5G mobile wireless networks. In particular, under the Nakagami-m channel model, we establish the PHY-layer Q-OFDMA system model and FD D2D model. Given the statistical QoS constraint, we derive and analyze the effective capacity under our proposed optimal power adaptation policy over 5G mobile wireless networks. Also conducted is a set of simulations which show that our proposed scheme outperforms the other existing schemes in terms of self-interference cancellation to efficiently implement the statistical QoS over 5G mobile wireless networks.

Statistical QoS-driven power allocation for WiFi offloading over heterogeneous wireless networks

To support the emerging next era of mobile wireless networks, researchers have made a great deal of efforts in promising techniques in multimedia services - the statistical quality-of-service (QoS) technique, which has been proved to be effective in statistically guaranteeing delay-bounded video transmissions over the time-varying wireless channels. On the other hand, as one of the 5G-promising techniques, the offloading technique has been demonstrated as the powerful approach to address the data explosion problem, alleviating the congestion in macrocells. Consequently, challenges have been imposed in applying the WiFi offloading scheme for maximizing the effective capacity under QoS constraints. To effectively overcome the above-mentioned challenges, we propose the statistical QoS-driven power allocation scheme through applying the WiFi offloading system over heterogeneous wireless networks. In particular, under the Nakagami-m fading channel model, we establish the communication model for WiFi offloading over heterogeneous wireless networks. Then, we propose the WiFi offloading methods. Given the statistical QoS constraints, we derive and analyze the effective capacity under our developed optimal power-allocation policies for the WiFi offloading scheme over heterogeneous wireless networks. Also conducted is a set of simulations which analyze the performance and the benefits of our proposed WiFi offloading scheme, compared to the schemes without WiFi offloading in terms of effective capacity under statistical QoS constraints over heterogeneous wireless networks.

Statistical QoS-driven power adaptation for distributed caching based mobile offloading over 5G wireless networks

To support the emerging next era of mobile wireless networks, researchers have made a great deal of efforts in promising techniques in multimedia services — the statistical quality of service (QoS) technique, which has been proved to be effective in statistically guaranteeing delay-bounded video transmissions over the time-varying wireless channels. On the other hand, as the 5G-promising techniques, the device-to-device (D2D) assisted mobile traffic offloading and caching techniques have also been proposed to significantly improve the overall system capacity as well as mitigate the traffic congestion at the base stations for the real-time traffic over 5G wireless networks. However, how to efficiently integrate these advanced techniques in supporting the statistical QoS requirements have imposed many new challenges not met before. To effectively overcome the aforementioned problems, in this paper we propose the statistical QoS-driven power adaptation scheme for the distributed caching assisted mobile offloading scheme over 5G wireless networks. In particular, under the Nakagami-m fading model, we establish the system models for the D2D assisted caching and the partial in-network transcoding. Given the statistical QoS constraints, we derive and analyze the effective capacity under our developed optimal adaptation policies for cache-enabled D2D assisted mobile offloading system under 5G wireless networks. Also conducted is a set of simulations which show that our proposed scheme outperforms the other existing schemes to efficiently implement the statistical QoS requirements over cache-enabled 5G wireless networks.

Efficient MAC-layer spectrum sensing scheme over underwater cognitive acoustic networks

The cognitive access techniques were originally developed for radio communication networks, and are recently extended to the research area for underwater acoustic networks. One of the important problems for developing the underwater cognitive acoustic networks lies in the optimal spectrum sensing strategy to maximize the exploitation of spectrum holes, which are the idle channels due to the absence of the primary acoustic user. To overcome this challenge, we propose the media access control (MAC)-layer spectrum sensing scheme to find the spectrum hole with minimum channel switching delay while obtaining the maximum signal-to-noise ratio. Using our proposed MAC-layer spectrum sensing scheme, the secondary underwater acoustic users efficiently reduce the channel switching delay.