Rate Adaptation Scheme Research Articles

Capacity of dual branch MRC system for correlated imbalanced average SNRs over Nakagami-m fading channels using OPRA scheme

The closed-form expressions of the capacity for dual branch Maximal Ratio Combining (MRC) diversity system with correlated and imbalanced average Signal-to-Noise Ratio (SNRs) over Nakagami-m fading channels are presented. Our approach is based on probability density function to find the mathematical expressions for Optimal Power and Rate Adaptation (OPRA) scheme. Numerically evaluated results are shown and compared with the available capacity results of OPRA scheme in the literature. The effect of different practical constraint i.e. - fade correlation and level of imbalanced in average SNRs on the channel capacity of the systems, is analysed.

Efficient Adaptation of Fuzzy Controller for Smooth Sending Rate to Avoid Congestion in Multicast Networks

This paper prefers a fuzzy-logic-based sending rate adaption scheme named FSR(Fuzzy Sending Rate) intending to improve the evenness of TCPFriendly Multicast Congestion Control (TFMCC). To mitigate fluctuation of sending rate for TFMCC sender, FSR intends, five actions and link utilization for tuning sending rate and uses a fuzzy controller to determine which operation should be reaped according to the feedback information from CLR (current limiting receiver). Asymmetrical membership functions and biased fuzzy inference rules make FSR as friendly to TCP flows as TFMCC. Simulation results show that FSR has exceptional smoothness and fine TCP Friendliness.

Delay Performance of Wireless Communications With Imperfect CSI and Finite-Length Coding

With the rise of critical machine-to-machine applications, next generation wireless communication systems must meet challenging requirements with respect to latency and reliability. A key question in this context relates to channel state estimation, which allows the transmitter to adapt the code rate to the channel state. In this paper, we characterize the tradeoff between the training sequence length and data codeword length: shorter channel estimation leaves more time for the payload transmission but reduces the estimation accuracy and causes more decoding errors. Using lower coding rates can mitigate this effect, but may result in a higher backlog of data at the transmitter. In order to optimize the training sequence length and the rate adaptation scheme with respect to the delay performance, we employ queuing analysis on top of accurate models of the physical layer. We obtain an analytically tractable solution to the problem by deriving a closed-form approximation for the decoding error probability due to imperfect channel knowledge and finite-blocklength channel coding. The optimized training sequence length and rate adaptation strategy can reduce the delay violation probability by an order of magnitude, compared with suboptimal strategies that do not consider the delay constraints.

Improving Video Transmission over Heterogeneous Networks

Mobile Ad-doc Networks (MANETs) have been conceived to operate as stand-alone networks, which means that data traffic will be restricted within the MANETs. However, in most practical applications of MANETs, mobile devices require access to wired hosts (e.g. video servers) located beyond the limits of the mobile ad hoc network. Therefore, routing protocols originally designed for an ad hoc environment must be extended to support the interoperability with other networks. This work presents a new algorithm that is integrated into the AQA-AODV routing protocol in order to improve the interoperability between MANETs and wired networks (heterogeneous networks). The proposed algorithm has been designed to improve the network conditions for video transmission over heterogeneous networks. Therefore, a performance evaluation of the video streaming over a simulated network was carried out using the proposed approach. The simulations experiments performed in this study involve the transmission of H.264/AVC streams with different spatial and temporal characteristics. The results reveal that the rate-adaptive strategy helps avoid or reduce the congestion obtaining an improvement of the received video quality.

ANFIS-based rate adaptation scheme for adaptive streaming over HTTP

Recently, HTTP-based video streaming traffic has continued to increase. Therefore, video service providers have been using HTTP-based adaptive streaming (HAS) technology to reduce the traffic load of the HTTP server. Accordingly, many adaptive bit rate (ABR) schemes have been proposed to provide a high quality of experience (QoE) to video service clients. In this paper, we propose a new ABR scheme using an adaptive network-based fuzzy inference system (ANFIS), which is one of the neuro-fuzzy structures. The proposed scheme learns optimal fuzzy parameters by using (1) the learning ability of ANFIS and (2) the video streaming data providing high QoE to clients. Then, the bit rate of the next segment is determined according to these trained parameters. In the simulation using NS-3, we show that the proposed scheme selects the appropriate bit rate under various wireless network conditions and provides better QoE to clients than the existing schemes.

Energy-Efficient Traffic Rate Adaptation for Wireless Streaming Media Transmission

Energy-efficient streaming of real-time scalable video over wireless fading channels with imperfect channel state information is considered in this paper. A traffic rate adaptation (TRA) scheme is presented to minimize the transmission energy consumption while satisfying the quality of experience (QoE) requirement by dynamically selecting the delivered encoding layers of streaming media depending on the channel condition. A partially observable Markov decision process model is introduced to formulate the energy-efficient QoE-guaranteed TRA problem. Based on the Lagrange method of multipliers, an online policy iteration algorithm is proposed to solve the constrained optimization problem. This algorithm performs policy evaluation and improvement without intensive computations and prior knowledge of channel statistics. The adaptability to unknown environments and high computation efficiency make the proposed scheme attractive for implementation in real-life mobile systems. Simulation results demonstrate the effectiveness of the proposed method.

Power- and Rate-Adaptation Improves the Effective Capacity of C-RAN for Nakagami-$m$ Fading Channels

We propose a power-and rate-adaptation scheme for cloud radio access networks (C-RANs), where each radio remote head (RRH) is connected to the baseband unit pool through optical links. The RRHs jointly support the users by efficiently exploiting the enhanced spatial degrees of freedom. Our proposed scheme aims at maximizing the effective capacity (EC) of the user subject to both per-RRH average- and peak-power constraints, where the EC is defined as the maximum arrival rate that can be supported by the C-RAN under the statistical delay requirement. We first transform the EC maximization problem into an equivalent convex optimization problem. By using the Lagrange dual decomposition method and solving the Karush–Kuhn–Tucker equations, the optimal transmission power of each RRH can be obtained in the closed form. Furthermore, an online tracking method is provided for approximating the average power of each RRH. For the special case of two RRHs, the expression of the average power of each RRH can be calculated in the explicit form. Hence, the Lagrange dual variables can be computed in advance in this special case. Furthermore, we derive the power allocation for two important extreme cases: first, no delay constraint and, second, extremely stringent delay requirements. Our simulation results show that the proposed scheme significantly outperforms the conventional algorithm without considering the delay requirements. Furthermore, when appropriately tuning the value of the delay exponent, our proposed algorithm is capable of guaranteeing a delay outage probability below $10^{-9}$ when the maximum tolerable delay is 1 ms. This is suitable for the future ultra-reliable low-latency communications.

Two-phase rate adaptation strategy for improving real-time video QoE in mobile networks

With the popularity of smart handheld devices, mobile streaming video has multiplied the global network traffic in recent years. A huge concern of users' quality of experience (QoE) has made rate adaptation methods very attractive. In this paper, we propose a two-phase rate adaptation strategy to improve users' real-time video QoE. First, to measure and assess video QoE, we provide a continuous QoE prediction engine modeled by RNN recurrent neural network. Different from traditional QoE models which consider the QoE-aware factors separately or incompletely, our RNN-QoE model accounts for three descriptive factors (video quality, rebuffering, and rate change) and reflects the impact of cognitive memory and recency. Besides, the video playing is separated into the initial startup phase and the steady playback phase, and we takes different optimization goals for each phase: the former aims at shortening the startup delay while the latter ameliorates the video quality and the rebufferings. Simulation results have shown that RNN-QoE can follow the subjective QoE quite well, and the proposed strategy can effectively reduce the occurrence of rebufferings caused by the mismatch between the requested video rates and the fluctuated throughput and attains standout performance on real-time QoE compared with classical rate adaption methods.

CBA-TCP: A cross-layer TCP transmission rate adaptation scheme based on the compressed block ACK bitmap of IEEE 802.11n networks

Optimizing the performance of TCP in wireless networks in a changing network condition is a highly challenging issue. The lack of information at the TCP layer about the link quality will result in inaccurate transmission rate. Therefore, TCP needs to have sufficient information about the environment and the different characteristics of the lower layers to improve the performance. To achieve this goal we proposed a cross-layer scheme which makes use of the information stored in the 802.11n compressed block acknowledged bitmap about the status of the transmitted subframes of the aggregated frame. This information is fed to the TCP transmission mechanism as a new criterion to adjust the TCP transmission rate with accordance to the aggregation level and channel quality. The simulation results show that the proposed scheme improves the TCP performance in term of throughput and packet loss.

Exploiting Video Quality Information With Lightweight Network Coordination for HTTP-Based Adaptive Video Streaming

This paper investigates how video-quality information can be exploited by HTTP-based adaptive streaming clients in their rate adaptation schemes. We also seek to answer the question: How much network coordination is required to achieve quality fairness across multiple competing clients? To that end, we envision a loosely coupled architecture where a lightweight centralized coordinator complements multiple federated quality-aware clients. Instead of actively programming network bandwidth allocation to each client, in our proposed architecture, the central coordinator simply collects quality and buffer level information from individual clients and publishes the aggregate quality statistics as reference. Such global reference statistics help to guide each federated client to self-tune its aggressiveness in its quality-aware adaptation scheme. Testbed-based evaluations show that such a lightweight approach is effective in reaping most of the performance gains previously achieved by a centralized joint optimization scheme. Compared to both state-of-the-art rate-based clients and independent quality-aware clients, our proposed federated quality-aware scheme can save up to 50% of total bandwidth while maintaining comparable aggregate video quality across all clients.

Efficient feedback mechanism for LTE-based D2D communication

Abstract Along with the surge of data traffic amount, Long Term Evolution (LTE)-based Device-to-Device (D2D) communication is emerging as a key data traffic offloading technology. However, current LTE-based D2D communication has limitations such as the lack of feedback mechanism, causing difficulty for efficient radio resource use. In this paper, we propose a feedback mechanism to increase the spectral efficiency of LTE-based D2D communication. In particular, the proposed feedback mechanism is designed to minimize signaling overhead and D2D Rxs can use the proposed feedback mechanism without any connection to Base Station (BS). On top of the proposed mechanism, we also propose feedback-aided rate adaptation and recovery schemes. Through extensive simulations, we verify that the proposed solutions achieve solid performances, e.g., goodput and latency, under various channel environments.

Cross-Layer Performance Analysis of Cooperative ARQ With Opportunistic Multi-Point Relaying in Mobile Networks

A cross-layer analysis framework is developed for the design and performance evaluations of cooperative automatic repeat request (ARQ) with opportunistic multi-point relaying (OMPR) in mobile networks. In particular, three exemplar OMPR functions and their combinations are studied for opportunistic distributed space–time coded (ODSTC) retransmissions in time-division duplex long-term evolution advanced systems. According to the complexities and coordination delays of the OMPR functions, the influences of channel fading on the spatial and temporal diversities offered by ODSTC-based ARQ and their impacts on the system throughput, transmission energy consumption, and relays’ queuing delays can be evaluated effectively under this framework. Based on the analytical results, a rate adaptation strategy is also proposed to maximize the system throughput subject to constraints on queuing delays at relay stations (RSs) and packet error rates at mobile stations (MSs). Analysis and simulation results show that in typical vehicular speeds, using maximally two active RSs for ODSTC is a very robust and effective choice to provide near best system throughput with less energy consumptions and lower protocol complexities. The throughput gains over a system without using RS retransmissions range from 16 ~ 80% for cell-edge MSs, with only 25 ~ 45% of the transmission energy consumption.

Multi-armed Bandit with Additional Observations

We study multi-armed bandit (MAB) problems with additional observations, where in each round, the decision maker selects an arm to play and can also observe rewards of additional arms (within a given budget) by paying certain costs. In the case of stochastic rewards, we develop a new algorithm KL-UCB-AO which is asymptotically optimal when the time horizon grows large, by smartly identifying the optimal set of the arms to be explored using the given budget of additional observations. In the case of adversarial rewards, we propose H-INF, an algorithm with order-optimal regret. H-INF exploits a two-layered structure where in each layer, we run a known optimal MAB algorithm. Such a hierarchical structure facilitates the regret analysis of the algorithm, and in turn, yields order-optimal regret. We apply the framework of MAB with additional observations to the design of rate adaptation schemes in 802.11-like wireless systems, and to that of online advertisement systems. In both cases, we demonstrate that our algorithms leverage additional observations to significantly improve the system performance. We believe the techniques developed in this paper are of independent interest for other MAB problems, e.g., contextual or graph-structured MAB.

Channel-Aware Rate Adaptation for Backscatter Networks

Backscatter communication networks receive much attention recently due to the small size and low power of backscatter nodes. As backscatter communication is often influenced by the dynamic wireless channel quality, rate adaptation becomes necessary. Most existing approaches share a common drawback: they fail to take both spatial and frequency diversity into consideration at the same time. Consequently, the transmission rate may be improperly selected, resulting in low network throughput. In this paper, we propose a channel-aware rate adaptation framework (CARA) for backscatter networks. CARA incorporates three essential modules, a lightweight channel probing scheme that differentiates collisions from packet losses, a burstiness-aware channel selection mechanism benefiting as many backscatter nodes as possible, a rate selection method choosing the optimal rate, and a mobility detection that discovers location changes. We implement CARA on commercial readers, and the experiment results show that CARA achieves up to $4 \times$ goodput gain compared with the state-of-the-art rate adaptation scheme.

Multi‐relay cooperative transmission based on rateless codes and adaptive demodulation

A rate adaption scheme is given at the receiver using rateless codes and log-likelihood ratio (LLR) threshold-based adaptive demodulation (ADM). The received bits with LLR absolute values higher than the preset threshold are demodulated by the receiver, otherwise, deleted. Through the theoretical analysis of the average mutual information (MI) of the demodulated bits, the method is obtained to calculate the LLR demodulation threshold under the required error performance after decoding and the constraint of codeword length for decoding. Then, the rate adaption scheme is applied in a parallel multiple relay wireless communication system. The LLR threshold is set according to the instantaneous SNR of the received signals in order to keep the average MI per demodulated bit of each relay link the same. The demodulated bits coming from all links are combined for decoding. The 256-QAM constellation and Raptor code are then considered as a special case to design a sample scheme. Simulation results prove the correctness of the theoretical analysis and the feasibility of the proposed scheme, and when it is employed by a multi-relay transmission system, the diversity gain can be obtained, and the anti-fading and the anti-jamming abilities of the system are promoted.

Battery-aware rate adaptation for extending video streaming playback time

Multimedia streaming applications are computation and network intensive that put a high demand on battery usage of mobile devices. Battery usage forms an important metric in user satisfaction, as increased battery consumption results in faster battery depletion and eventually leads to battery outage. In this paper, we propose an adaptation technique, referred as Battery-Aware Rate Adaptation (BARA) scheme, which adapts to the appropriate bit rate to prolong the battery lifetime. BARA considers both the wireless channel conditions, as well as the device’s battery level, to determine the best transmission rate for optimizing the mobile battery consumption. Actual experiment and simulation results corroborate that compared to the conventional techniques, BARA can save more than 40% of battery power, while extending the video playback time by 20%.

Fuzzy Rough Set Inspired Rate Adaptation and resource allocation using Hidden Markov Model (FRSIRA-HMM) in mobile ad hoc networks

Data transmission in ad hoc networks necessitates different quality of services (QoS) for ensuring reliable throughput of the network. This reliability in network performance is achievable through a rate adaptation scheme that aids in effective allocation of resource for ensuring QoS, based on network demand. In this approach, the available bandwidth is forecasted based on Hidden Markov Model for improving the efficacy in resource allocation and the new users are facilitated to utilize the resources based on the estimation of currently available resources determined through rough set theory. The rate of adaptation is forecasted based on the present load condition of the network by Rough set theory, which forms the input of the Hidden Markov Model. The fuzzy Rough set concept is mainly used in this technique as they are reliable in analyzing data that not require any basic or auxiliary information pertaining to data than its fuzzy set theory, Bayesian theory and Shafer–Dempster theory counter parts that necessitate the assignment of probability. Fuzzy Rough set concept determines the rate of adaptation through the estimation of queuing state, queuing delay, channel utilization rate, and bandwidth availability. This fuzzy Rough set concept also considers the resource allocation as the significant entity as the channel allocation in dynamic networks purely relies on the dynamic channel variation that alternates in real time distribution of data.

LORA: Loss Differentiation Rate Adaptation Scheme for Vehicle-to-Vehicle Safety Communications

Existing study shows that safety applications supported by vehicle-to-vehicle (V2V) communications have the potential to address 80% of all road crash issues. IEEE 802.11p is a key enabling technology to support V2V safety applications. To meet the stringent delay and reliability requirements of these applications, rate adaptation approaches have been proposed to determine the optimal data transmission rate according to the channel conditions such as packet losses. However, existing rate adaptation solutions cannot be directly applied to V2V safety communications in highway scenarios, which exhibit lots of dynamics and severe packet losses. Moreover, PHY-layer channel fading and MAC-layer interference contribute differently to the packet losses, and thus should be treated separately. To address these issues, we propose LORA, a Loss Differentiation Rate Adaptation scheme in this paper. LORA can estimate the average packet loss rate for each sender and differentiate the fading losses from the interference losses. Extensive evaluation results demonstrate that LORA can provide reliability guarantees for V2V safety applications, and response to environment changes in a real-time manner.

Multi‐rate combination of partial information‐based routing and adaptive modulation and coding for space deterministic delay/disruption tolerant networks

Delay/disruption tolerant network (DTN), in which the network connectivity is intermittent and the node buffer size is limited, is a promising approach to model space networks. In this study, the authors focus on the space deterministic DTNs whose mobility and connectivity are predictable. A rate adaptation scheme based on adaptive modulation and coding (AMC) is adopted. Based on the analysis of data delay in DTN, the authors propose two routing algorithms, namely local information-based routing (LIR) and local and neighbour information-based routing (LNIR) for space DTNs. Queuing information in partial nodes is used in routing selection. The two proposed algorithms outperform the traditional least delay routing (LDR) in average end-to-end delay, packet loss ratio and traffic distribution. With the same network load, the average delay of LDR, LIR and LNIR are 44.43 s, 22.82 s and 14.08 s while the packet loss ratio of three algorithms are 6.37, 0.76 and 0.00%. Simulation result also shows the superiority of AMC over fixed modulation and coding (FMC) in space DTNs. When the DTN is heavily loaded, the delay of AMC is 15 s smaller than that of FMC. At the same time, the packet loss ratio of AMC is one-sixth that of FMC.

How to Boost the Throughput of HARQ With Off-the-Shelf Codes

In this paper, we propose a coding strategy designed to enhance the throughput of hybrid automatic repeat request (HARQ) transmissions over independent identically distributed block-fading channels with the channel state information unknown at the transmitter. We use a joint packet coding where the same channel block is logically shared among many packets. To reduce the encoding and decoding complexity, we use a two-layer coding where, first, packets are punctured, mixed, and then passed to the conventional channel encoder. We show how to optimize the puncturing rates on the basis of the empirical error-rate curves. We also discuss how the parameters of the practical turbo-codes may be modified to take advantage of the proposed HARQ scheme. Finally, simple and pragmatic rate adaptation strategies are developed. In numerical examples, our scheme is compared with the conventional incremental redundancy HARQ (IR-HARQ), which remains a strategy of choice in the region of small throughput; however, our scheme shows a notable gain of $1-2~\textrm {dB}$ in the region of high throughput, where IR-HARQ fails to provide any improvement.