Existing Rate Adaptation Schemes Research Articles

Augmenting Drive-Thru Internet via Reinforcement Learning-Based Rate Adaptation

Drive-thru Internet has been considered as an effective Internet access method for Internet of Vehicles (IoV). Through the opportunistic vehicle-to-roadside WiFi connection, it can provide high throughput performance with low communication cost for IoV applications, such as intelligent transportation system, automotive infotainment, etc. However, its usability is highly affected by a fundamental issue called rate adaptation (RA), which is to adjust the modulation and coding rate to adapt to the dynamic wireless channel between the vehicle and the roadside access point (AP). Conventional WiFi RA schemes are designed for indoor or quasistatic scenarios and do not account for the channel variations in drive-thru Internet. In this article, we study the limitation of applying existing RA schemes in drive-thru Internet and propose a reinforcement learning (RL)-based RA scheme to capture the potential channel variation patterns and efficiently select the rate for every vehicle’s egress frame. Simulation results demonstrate that the proposed RA scheme outperforms the existing schemes in network throughput and that the efficiency of the learning model can be generalized under various conditions. The proposed RA method can provide useful inspirations for designing robust and scalable link adaptation protocols in IoV.

Probabilistic Tile Visibility-Based Server-Side Rate Adaptation for Adaptive 360-Degree Video Streaming

In this paper, we study the server-side rate adaptation problem for streaming tile-based adaptive 360-degree videos to multiple users who are competing for transmission resources at the network bottleneck. Specifically, we develop a convolutional neural network (CNN)-based viewpoint prediction model to capture the nonlinear relationship between the future and historical viewpoints. A Laplace distribution model is utilized to characterize the probability distribution of the prediction error. Given the predicted viewpoint, we then map the viewport in the spherical space into its corresponding planar projection in the 2-D plane, and further derive the visibility probability of each tile based on the planar projection and the prediction error probability. According to the visibility probability, tiles are classified as viewport, marginal and invisible tiles. The server-side tile rate allocation problem for multiple users is then formulated as a non-linear discrete optimization problem to minimize the overall received video distortion of all users and the quality difference between the viewport and marginal tiles of each user, subject to the transmission capacity constraints and users' specific viewport requirements. We develop a steepest descent algorithm to solve this non-linear discrete optimization problem, by initializing the feasible starting point in accordance with the optimal solution of its continuous relaxation. Extensive experimental results show that the proposed algorithm can achieve a near-optimal solution, and outperforms the existing rate adaptation schemes for tile-based adaptive 360-video streaming.

A Survey of Rate-Adaptation Schemes for IEEE 802.11 Compliant WLANs

The IEEE 802.11 compliant stations can transmit at multiple transmission rates. Selection of an appropriate transmission rate plays a significant role in determining the overall efficiency of a communication system. The technique which determines the channel state information and accordingly selects an appropriate transmission rate is called rate-adaptation protocol. The IEEE 802.11 standard does not provide standard specification for implementing a rate-adaptation protocol for its multi-rate capable wireless stations. Due to the lack of standard specification, there is a myriad of rate-adaptation protocols, proposed by industry and various research institutes. This paper surveys the existing rate-adaptation schemes, discusses various features which contribute significantly in the process of rate-adaptation, the timing constraints on such schemes, and the performance gains in terms of throughput, delay and energy efficiency; which can be gained by the use of rate-adaptation. The paper also discusses the implication of rate-adaptation schemes on the performance of overall communication and identifies existing research challenges in the design of rate-adaptation schemes.

SRAG: A Priority-Based Rate Adaptation Scheme Using Game Theory for Vehicular Networks

Rate adaptation is critical to the system performance of Wireless Local Area Networks (WLANs). Existing rate adaptation schemes mostly make use of packet statistics or the signal strengths of received packets to adapt transmission rates, regardless of the packet priorities. In this paper, we first find out that it is beneficial for rate adaptation schemes to consider packet priorities when adapting transmission rates. We then propose a novel priority-based rate adaptation scheme for vehicular networks named SRAG (Stackelberg Rate Adaptation Game) which jointly considers channel conditions and packet priorities using game theory. In SRAG, rate adaptation is modeled as a game which consists of different priorities of users and each user tries to select an optimal transmission rate that maximizes its utility regardless of others' utilities. SRAG adopts a Stackelberg game model to regulate behaviors of self-interested users and gives priority to high priority users in order to achieve better overall performance. Extensive ns-2 simulations demonstrate that SRAG can provide much better performance for high priority users than existing rate adaptation schemes, while maintaining good performance for low priority users.

Adaptive threshold control for auto-rate fallback algorithm in IEEE 802.11 multi-rate WLANs

The IEEE 802.11 standard supports multiple rates for data transmission in the physical layer. Nowadays, to improve network performance, a rate adaptation scheme called auto-rate fallback (ARF) is widely adopted in practice. However, ARF scheme suffers performance degradation in multiple contending nodes environments. In this article, we propose a novel rate adaptation scheme called ARF with adaptive threshold control. In multiple contending nodes environment, the proposed scheme can effectively mitigate the frame collision effect on rate adaptation decision by adaptively adjusting rate-up and rate-down threshold according to the current collision level. Simulation results show that the proposed scheme can achieve significantly higher throughput than the other existing rate adaptation schemes. Furthermore, the simulation results also demonstrate that the proposed scheme can effectively respond to the varying channel condition.

Rate Adaptation Technique for Coexisting Heterogeneous IEEE 802.11 Wireless LANs

Different physical (PHY) layers of IEEE 802.11 provide the option of multiple data rates [such as 802.11 (a/b/g) all provide multi-rate capabilities]. A good rate adaptation mechanism is required to determine the optimal transmission rate appropriate for the current wireless channel condition. But a rate adaptation mechanism is still unspecified in the 802.11 standards. In this paper, we design a rata adaptation scheme for coexisting heterogeneous IEEE 802.11 WLANs which comprise three different modules. Firstly, based on the distance from the AP, a node chooses the achievable set of rates applicable to it. Secondly, we differentiate a packet loss by measuring the probability that a packet is lost due to channel error. Finally, our rate adaptation mechanism selects the best rate based on the measured normalized rate efficiency. We have performed extensive simulations and the result shows that the proposed mechanism outperforms other well-known existing rate adaptation schemes by achieving higher network throughput.