Qixuan Zhu

Spectrum efficiency maximization using primal-dual adaptive algorithm for distributed mobile devices caching over edge computing networks

The information-centric network techniques enable the in-network caching mechanism to cache the popular data contents in the mobile devices. Even though each mobile devices caching memory can be limited, caching in mobile devices offers the great potential of caching capability because of the massive mobile devices. Using caching in mobile devices, a mobile user can obtain its requested files from other mobile users through device-to-device (D2D) communication instead of the remote data-source provider, which significantly reduces the duplicate data traffics in the core network and through base stations. In this paper, we use the distributed mobile devices caching, where we randomly distribute and store the popular data contents in mobile devices of a cellular network. To avoid the interference among D2D communications, we partition the entire wireless cell into several squarelets and only activate the D2D connections within each squarelet. Then, we derive the expected number of mobile users in a squarelet and develop a primal-dual adaptive algorithm to maximize the overall spectrum efficiency for these mobile users with unknown wireless channel conditions. To evaluate the performance of our proposed adaptive algorithm, we compare our obtained spectrum efficiency with the spectrum efficiency under the optimal situation where all wireless channel conditions are given. Our proposed algorithm can guarantee the smallest ratio for the obtained spectrum efficiency under these two situations, showing the performance lower bound of our proposed adaptive algorithm.

Bayesian-game based power and spectrum virtualization for maximizing spectrum efficiency over mobile cloud-computing wireless networks

Mobile cloud-computing is a wireless network environment that focuses on sharing the publicly available wireless resources. Wireless network virtualization provides an efficient technique to implement the mobile cloud-computing by enabling multiple virtual wireless networks to be mapped onto one physical substrate wireless network. One of the most important challenges of this technique lies in how to efficiently allocate the wireless resources of physical wireless networks to the multiple virtual wireless network users. To overcome these difficulties, in this paper we propose the Bayesian-game based schemes to resolve the wireless resources allocation problem in terms of transmit power and wireless spectrum. We formulate this wireless resources allocation problem as the gaming process where each mobile user bids for the limited wireless resources from physical substrate wireless networks, and competes with the other mobile-user players bidding for the same resources. Since the bidding strategies for other mobile-user players are incomplete information, we propose the Bayesian-game based schemes to dictate the virtual users to request wireless resources based on the probabilities of these incomplete information. Our proposed game is guaranteed to converge to the Bayesian Nash Equilibrium, where each virtual user optimizes their resources request actions with the consideration to actions of the other mobile-user players. The extensive simulation results obtained validate and evaluate our proposed schemes.

Statistical quality of service provisioning over edge computing mobile wireless networks

The edge computing techniques have been developed to support the exponentially increasing service demands in the fifth generation (5G) networks by bringing the data contents and their corresponding computations/communications near to mobile users. As a promising and efficient solution to implement edge computing techniques, mobile data offloading complements the traditional cellular transmission through either WiFi networks or device-to-device (D2D) communication/relay to mitigate the overloaded wireless traffics for cellular networks. However, the mobile data offloading in edge computing wireless networks imposes many new quality of service (QoS) guarantee problems which still remain opening research areas. To overcome these challenges, in this paper we propose the statistical delay-bounded QoS provisioning schemes using the effective capacity theory for two types of mobile data offloading: WiFi offloading and D2D offloading, where we formulate the WiFi offloading and D2D offloading as the single-hop and two-hop wireless-link statistical QoS provisioning problems, respectively. We also derive the optimal probability of using each type of offloading which maximizes the average effective capacity for all mobile users under the following two scenarios: (1) all mobile users have the same probability of requesting the popular multimedia data contents and have the same probability to become a relay in D2D offloading; and (2) each mobile user has the distinct probability of requesting the popular multimedia data contents and the distinct probability to become a relay in D2D offloading. Finally, we evaluate and validate our proposed statistical delay-bounded QoS provisioning schemes over multimedia data offloading architecture through numerical analyses.

Game-Theory Based Power and Spectrum Virtualization for Optimizing Spectrum Efficiency in Mobile Cloud-Computing Wireless Networks

Mobile cloud-computing is a wireless network environment that focuses on sharing the publicly available wireless resources. Wireless network virtualization provides an efficient technique to implement the mobile cloud-computing by enabling multiple virtual wireless networks to be mapped onto one physical substrate wireless network. One of the most important challenges of this technique lies in how to efficiently allocate the wireless resources of physical wireless networks to the multiple virtual wireless network users. To overcome these difficulties, in this paper we propose a set of novel game-theory based schemes to resolve the wireless resources allocation problem in terms of transmit power and wireless spectrum. We formulate this wireless resources allocation problem as the gaming process where each mobile user bids for the limited wireless resources from physical substrate wireless networks, and competes with the other mobile-user players bidding for the same resources. Under our proposed game-theory framework, we develop three types of wireless resources request strategies: price-based strategy, correlation-based strategy, and water-filling-based strategy to allocate wireless resources under three different gaming mechanisms. The extensive simulation results obtained validate and evaluate our proposed schemes.

Information-centric network virtualization for QoS provisioning over software defined wireless networks

The software defined network (SDN) has emerged as an efficient network technology capable of supporting the dynamic nature of network functions while lowering the operating costs through simplified hardware, software, and management. The SDN is an efficient implementing technique for network function virtualization, because SDN maximizes network utilization by decoupling the wireless network infrastructure from the service that it provide, so that differentiated services can share the same infrastructure. One the other hand, information-centric network technique can reduce duplicate transmissions for popular contents by adopting caching strategy and enabling mobile-users to access popular contents from caches of nearby network gateways. One of the main challenges of implementing SDN is how to transmit the time-sensitive multimedia data with the delay-bounded quality of service (QoS) guaranteed in SDN environments. To overcome these difficulties, we propose an information-centric wireless network virtualization technique, which integrates the wireless network virtualization with information-centric networking. We formulate this data transmission problem over virtualized information-centric wireless network as follows. The mobile-user requests the data-source from the network controller. Network controller finds this data-source (located at the end host or a cache), and sets up a data delivery path for the mobile-user. We apply the effective capacity theory to measure the delay-bounded QoS for time-sensitive multimedia data transmission. The data delivery path is established based on a flexible network architecture, which can maximize the effective capacity, for the delivered data. In the delivery process, the data can be copied and stored in a network node as the cache for other mobile-users requests, aiming at minimizing the average transmit power consumption over all mobile-users.

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.

Effective-Capacity Based Auctions for Relay Selection over Wireless Cooperative Communications Networks

Cooperative communication is an efficient technique for mobile wireless networks supporting information transmission through relay nodes, which forward the signal received from a source node to its destination. Applying the cooperative communication in wireless networks can significantly improve the network performance. One of the most important challenges is how to efficiently allocate the access opportunity of a relay node to multiple mobile-users while taking into account the delay-bounded quality of service (QoS) for the time-sensitive multimedia data transmissions. To overcome these difficulties, in this paper we propose a novel game-theory based scheme to resolve the relay node allocation problem by measuring the maximum throughput for time-sensitive multimedia data transmission under a QoS requirement as the effective capacity gain. We formulate this one relay allocation problem as a single-relay-auction such that all mobile-user players can decide whether to patriciate in this relay auction, and the mobile-user player who places the highest bid obtains the relay allocation. The mobile-user players who lose or stay out of the auction can only directly transmit information to their destinations. Then, we derive the optimal strategies for the single-relay-auction, maximizing the payoff (effective capacity gain minus costs) in each bid round.The extensive simulation results obtained validate and evaluate our proposed schemes.

Statistical-QoS based gaming for optimal power allocations over virtualized wireless relay networks supporting multimedia services

Cooperative communication is one of the efficient techniques to support statistical delay-bounded quality-of-service (QoS) multimedia (audio/video) services over mobile wireless networks by employing relay nodes, which forward the signal received from source node to the destination. Wireless network virtualization provides another efficient technique to implement the data transmissions by enabling multiple virtual wireless networks (VWNs) to be mapped onto one physical substrate wireless network (SWN), increasing the utilization efficiency of SWN. Applying the cooperative communication to virtual wireless networks provides a significant improvement on time-sensitive multimedia services in order to support the diverse quality of service requirements over mobile wireless networks. One of the most important challenges of this application lies in how to efficiently allocate the wireless resources of physical wireless networks to the multiple virtual wireless network users, taking into account the statistical delay-bounded QoS for the multimedia information transmission. To overcome this difficulty, in this paper we propose a novel game-theory based scheme to resolve the wireless resources allocation problem in terms of transmit power, aiming at maximizing the effective-capacity to guarantee the statistical delay-bounded QoS for wireless multimedia communications. We formulate this wireless resources allocation problem as follows. A mobile user starts with asking for the cooperation from the other virtual users in the same virtual network to be as its relay nodes. When at least one virtual user agrees to cooperate, the mobile user executes the following two gaming processes. First, the mobile user bids for the source-node-transmit-power resources from SWN. Second, at the same time the mobile user bids for the relay-transmit-power from those cooperated virtual users, coordinating with the first bid strategies to maximize its payoff (performance-gain minus cost) in each bid round. The extensive simulation results obtained validate and evaluate our proposed schemes.

Statistical QoS-Driven Power Adaptation Over MIMO-GFDM Based Underwater Wireless Networks

With the explosive developments of underwater acoustic communications, underwater acoustic communications have played a critically important role in many critical applications, such as oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, and tactical surveillance. Due to hash underwater environment, underwater acoustic communications impose new challenges to wireless communications research. Therefore, to guarantee the system performance with minimum resource consumption for underwater acoustic channel, we propose the novel statistical QoS-driven power adaptation over MIMO generalized frequency division multiplexing (GFDM) [1] based underwater wireless networks. The objective of underwater acoustic communications is to transmit large-volume data information at a high-data rate with quality of service (QoS) provisioning. The statistical QoS guarantees [2], in terms of effective capacity and queue-length-bound/delay-bound violation probabilities, have been proposed and demonstrated as the powerful way to characterize delay QoS requirements for wireless traffics. On the other hand, to support the underwater acoustic wireless networks, for the last several years researchers have made a great deal of efforts in investigating various advanced wireless techniques, such as the MIMO-OFDM scheme [3]. However, the complicated application scenarios present new challenges making the OFDM less efficient in various underwater wireless networks. To overcome the aforementioned challenges, in this paper we propose the novel GFDM based scheme over underwater wireless networks.

Transmit Antenna and Relay Selections for Underwater MIMO-OFDM Cooperative Wireless Networks

The multiple-input-multiple-output (MIMO), the orthogonal frequency division multiplexing (OFDM), and the cooperative communication techniques are widely applied in and significantly improved the essential performances of underwater acoustic (UWA) wireless networks in recent years. However, the challenge of reducing the computational complexity while guaranteeing performances of MIMO-OFDM based UWA wireless networks still remains to be resolved. In this paper, we propose a scheme for transmit antenna selection and relay selection to address this problem as follows. Using the channel station information feedback in the MIMO-OFDM based UWA cooperative communication channel, a single transmit antenna for each underwater sensor and one relay node which can maximize the total channel coefficient are selected to transmit data to the corresponding surface destination station, providing a balanced tradeoff between complexity and performance of the network.