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The unforeseen mobile data explosion as well as the scarce of spectrum resource pose a major challenge to the performance of today's cellular networks which are in urgent need of novel solutions to handle such voluminous mobile data. Long term evolution-unlicensed (LTE-U), which extends the LTE standard operating on the unlicensed band, has been proposed to improve system throughput. In LTE-U system, arriving users will contend the unlicensed spectrum resource with wireless fidelity (WiFi) users to transmit data information. Nevertheless, there is no clear consensus as to the benefits of transmission using unlicensed bands for LTE users. To this end, in this paper an analytical model is presented based on a queue system to understand the performance achieved by unlicensed based LTE system taking quality of services (QoS) and LTE-U users' behaviors into account. To obtain the stead-state solutions of the queue system, a matrix geometric method is used to solve it. Then, the average delay and utilization of unlicensed band for the LTE-U users is derived by using the queuing model. The performance of LTE-U coexistence is evaluated with WiFi using the proposed model and provide some initial insights as to the advantage of LTE-U in practice.

With the boom of wireless devices, the number of wireless users under wireless local area networks (WLANs) has increased dramatically. However, the standard backoff mechanism in IEEE 802.11 adopts fixed initial contention window (CW) size without considering changes of network load, which leads to a high collision probability and low channel utilization in bursty arrivals. In this paper, a novel CW dynamic adjustment scheme is proposed to achieve high throughput performance in dense user environment. In the proposed scheme, the initial CW size is dynamically adjusted to optimum according to the measured packet collision probability. Simulation results show that the proposed scheme can significantly improve the throughput performance.

In IEEE 802.11 networks, many access points (APs) are required to cover a large area due to the limited coverage range of APs, and frequent handoffs may occur while a station (STA) is moving in an area covered by several APs. However, traditional handoff mechanisms employed at STAs introduce a few hundred milliseconds delay, which is far longer than what can be tolerated by some multimedia streams such as voice over Internet protocol (VoIP), it is a challenging issue for supporting seamless handoff service in IEEE 802.11 networks. In this paper, we propose a pre-scan based fast handoff scheme within an IEEE 802.11 enterprise wireless local area network (EWLAN) environment. The proposed scheme can help STA obtain the best alternative AP in advance after the pre-scan process, and when the handoff is actually triggered, STA can perform the authentication and reassociation process toward the alternative AP directly. Furthermore, we adopt Kalman filter to minimize the fluctuation of received signal strength (RSS), thus reducing the unnecessary pre-scan process and handoffs. We performed simulations to evaluate performance, and the simulation results show that the proposed scheme can effectively reduce the handoff delay.

Objective video quality assessment methods often evaluate all the frames regardless of their importance. For wireless distorted videos, not every frame has the same contribution to the final overall quality due to the channel fading and interference, which may lead to the capacity variation in temporal. Besides, with the content similarity and error propagation pattern in temporal domain, it is possible to evaluate the overall quality with only part of the frames. In this paper, a demonstration is performed to show that the video quality can be evaluated with reduced frames set (RFS), and a state transition model is proposed to extract the RFS. At last, a video quality assessment (VQA) method is carried out based on RFS. Compared with several state-of-the-art methods, our method can achieve a suitable accuracy with less frames to be processed.

Mobile data traffic is going through an explosive growth recently as mobile smart devices become more and more ubiquitous, causing huge pressure on cellular network. Taking advantage of its low cost and easy-to-deploy feature, wireless local-area networks (WLAN) becomes increasingly popular to offload data streams from cellular network, followed by higher and higher density of its deployment. However, the high density of WLAN will cause more interference, which results in degradation of its performance. Therefore, in order to enhance the performance of the network, we aim to minimize the interference caused by high density of WLAN. In this paper, we propose a novel power control scheme to achieve the above aim. We use the quality of experience (QoE) evaluation to coordinate the power of each access point (AP) and finally realize the optimization of the entire network. According to the simulation results, our scheme improves the performance of the network significantly in many aspects, including throughput and QoE.

Quality of experience (QoE) has been one of the most important factors for service providers and operators to develop and deploy services. Previous works have shown that Weber-Fechner law (WFL) can be used to promote the accuracy of best-effort (BE) services’ QoE assessment. In this paper, based on WFL, we take a deep insight into the visual information of BE services and its role in WFL, especially in web browsing services, and propose an enhanced QoE assessment model for BE services by taking the visual information into account. Both images and texts visual information are extracted and combined to get the visual information for web pages. Finally, a subjective experiment is performed to validate performance of proposed QoE assessment model, which shows that it performs better than traditional WFL based model.

The unforeseen mobile data explosion poses a major challenge to the performance of today's cellular networks, and cellular networks are in urgent need of novel solutions to handle such voluminous mobile data. Obviously, data offloading through third-party WiFi access points (APs) can effectively alleviate the data load in the cellular networks with a low operational and capital expenditure. In this paper, we propose and analyze an adaptive WiFi-offloading algorithm based on attractor selection in heterogeneous wireless networks. In the proposed WiFi-offloading algorithm, the WiFi system throughput and cellular throughput in the coverage area of WiFi, are mapped into the activity of the attractor, which is the reflector of the current network environment. When the current attractor activity is low, the network is dominated by the noise. Then, the noise triggers the controller to select adaptive attractor, an optimal WiFi-offloading ratio, to adapt to the dynamic network environment. And users offload the specific portion of traffic to the WiFi networks with the ratio of, which improves the throughput of heterogeneous wireless networks and alleviates the load of cellular networks. Through simulation, we show that the proposed WiFi-offloading algorithm outperforms the existing ones with 21% higher heterogeneous network throughput in a dense traffic environment.

Since the different characteristics of various network services determine that their requirements for network are also disparate, the performance of one network varies according to the services running on it. However, most of previous network performance evaluation (NPE) researches conduct evaluations based on the network parameters, but without considering from the perspective of specific service running on the network. In view of this issue, a novel service-oriented NPE framework is proposed. First, the characteristics discrepancy among different types of services are investigated. Next, in order to conduct comprehensive evaluation of multiple services, an enhanced low-complexity adaptive (LA)-fuzzy analytical hierarchy process (FAHP) is introduced; meanwhile by applying the experts-construct-directly (ECD) algorithm proposed later, the consistency check required in previous studies can be omitted, thereby significantly reducing the computation complexity and assessment workload for experts. Then, in accordance with the features of each service, corrections are made to their respective membership functions, thus making the proposed LA-FAHP adaptive to various service evaluation scenarios. The subsequent comparison with other NPE methods well proves the effectiveness and high sensitivity of proposed framework, and the analysis verifies the low computation complexity of the proposed algorithms as well.