Ad hoc networks are characterized by limited resources (e.g. energy, bandwidth). Efficient information dissemination while avoiding excessive energy cost can be achieved through the suitable design of a network. To th...
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Ad hoc networks are characterized by limited resources (e.g. energy, bandwidth). Efficient information dissemination while avoiding excessive energy cost can be achieved through the suitable design of a network. To this end we propose an information dissemination scheme which couples epidemic dissemination with adaptive modulation and coding (AMC). The proposed scheme tunes the message forwarding probability and the coding and modulation mode in order to achieve a balance between maximum coverage over the network and minimum energy expenditure. We achieve this based on the evaluation of suitably defined indicators related to the lower network layers and exploiting information on the current status of the wireless medium. Building on established previous AMC-related work, our simulation results indicate that our scheme brings significant improvement over non-adaptive approaches, comparable with other adaptive epidemic dissemination schemes. Our findings are quite promising for adaptive epidemic-based information dissemination schemes with a strong cross-layer component.
This letter considers hybrid automatic repeat request (HARQ) protocols on a block Rayleigh fading channel. We derive the packet loss probability and the throughput for HARQ in closed-form. We propose a simple approxim...
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This letter considers hybrid automatic repeat request (HARQ) protocols on a block Rayleigh fading channel. We derive the packet loss probability and the throughput for HARQ in closed-form. We propose a simple approximated but very accurate formula for the throughput. We deduce a cross-layer design of adaptive modulation and coding with HARQ.
In this letter, the joint probability density function (pdf) of the order statistics for a set of correlated Nakagami-m fading channels is derived. This result is useful in analyzing the performance of a variety of di...
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In this letter, the joint probability density function (pdf) of the order statistics for a set of correlated Nakagami-m fading channels is derived. This result is useful in analyzing the performance of a variety of diversity schemes which involve branch selection. The derivation also yields a computationally efficient method for obtaining the marginal pdf of the p-th order statistic for a set of correlated Nakagami-m fading channels.
In this letter, we obtain the optimal signal-to-noise ratio regions for the adaptive modulation and coding (AMC) over a set of correlated subcarriers. We use logistic regression to model the block error rate (BLER) wi...
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In this letter, we obtain the optimal signal-to-noise ratio regions for the adaptive modulation and coding (AMC) over a set of correlated subcarriers. We use logistic regression to model the block error rate (BLER) with the aim of maximizing the throughput while keeping the BLER below a predefined target. We also study the robustness of a suboptimal optimization procedure, which maintains the relative distance among thresholds to that preserving the instantaneous BLER under the target. Moreover, we bring a new understanding of the outer loop link adaptation (OLLA) mechanism in terms of the AMC. We show that OLLA is able to converge (in average) to the thresholds designed by this suboptimal procedure. We also study the unstable behavior of OLLA implementations that update one offset per modulation and coding scheme, bringing out the need for new more flexible link adaptation mechanisms.
In wireless adaptive modulation and coding (AMC) systems, modulation type of a user's connection can change and the ongoing connection might fail due to the change of modulation. In this paper, we approach the AMC...
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In wireless adaptive modulation and coding (AMC) systems, modulation type of a user's connection can change and the ongoing connection might fail due to the change of modulation. In this paper, we approach the AMC-induced call admission control (CAC) problem by focusing on the guaranteed connection. Three classes of calls, new, handoff, and modulation-changed, are considered. We modify the guard-channel CAC scheme such that the modulation-changed calls, in addition to the handoff calls, are allowed to use the guard channel. Then we analyze a Markov model for the CAC scheme designed with long-term AMC in mind. The proposed approach will be an essential tool to determine the guard-channel thresholds in the wireless AMC networks.
In this letter, we proposed an efficient underwater acoustic (UWA) image communication algorithm based on reinforcement learning which can improve the image quality while reduce the energy consumption and time delay i...
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In this letter, we proposed an efficient underwater acoustic (UWA) image communication algorithm based on reinforcement learning which can improve the image quality while reduce the energy consumption and time delay in fast time variant UWA channels. In the proposed algorithm, the received image quality and other communication performance parameters are estimated at the sink continuously and then feedback to the sensor by an independent channel in order to avoid bandwidth loss caused by large time delay. At the sensor, the most suitable modulation and coding method is chosen to maximize a special designed value function in order to achieve the best efficient underwater image communication. Sea test results show that the proposed UWA image communication algorithm can reduce the bit-error rate by 3.1 dB, the energy consumption of the sensor by 26.9% and the time delay by 58.2%. The proposed algorithm can also shorten the convergence time by 47.4% compared with the model-free reinforcement learning underwater communication algorithm.
The impact of channel state estimation errors in a CDMA system employing adaptive modulation and coding in conjunction with multicodes is studied. The channel is modelled as a finite-state Markov chain and the perform...
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The impact of channel state estimation errors in a CDMA system employing adaptive modulation and coding in conjunction with multicodes is studied. The channel is modelled as a finite-state Markov chain and the performances using (1) a simple moving average (SMA) filter (2) a hidden Markov model (HMM) filter to estimate the channel state are compared. The results show that the HMM filter is more robust and provides a significant throughput improvement over the SMA filter, especially when the channel estimate is quite noisy or the normalized Doppler rate is small.
In this paper, we propose a new adaptive link layer protocol that consists in adapting packet length and modulation and coding Scheme (MCS) to Average Signal to Noise Ratio or instantaneous SNR (ISNR). adaptive MCS an...
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In this paper, we propose a new adaptive link layer protocol that consists in adapting packet length and modulation and coding Scheme (MCS) to Average Signal to Noise Ratio or instantaneous SNR (ISNR). adaptive MCS and adaptive packet length offer higher throughput than adaptive MCS and fixed packet length as considered in previous studies. The best strategy is to adapt the MCS and packet length to ISNR. adaptive MCS and adaptive packet length offer 1-2 dB gains with respect to adaptive MCS and fixed packet length. The proposed adaptive link layer protocol has been implemented by quantizing the SNR on the feedback channel over four hits and yielding close results to unquantized SNR.
This paper presents a novel cross-layer optimization framework to improve the quality of user experience (QoE) and energy efficiency of the heterogeneous wireless multimedia broadcast receivers. This joint optimizatio...
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This paper presents a novel cross-layer optimization framework to improve the quality of user experience (QoE) and energy efficiency of the heterogeneous wireless multimedia broadcast receivers. This joint optimization is achieved by grouping the users based on their device capabilities and estimated channel conditions experienced by them and broadcasting adaptive content to these groups. The adaptive multimedia content is obtained by using scalable video coding (SVC) with optimal source encoding parameters resulted from an innovative cooperative game. Energy saving at user terminals results from using a layer-aware time slicing approach in the transmission stage. A trade-off between energy saving and QoE is observed, and is incorporated in the definition of a utility function of the players in the formulated heterogeneous user composition and physical channel aware game. An adaptive modulation and coding scheme is also optimally incorporated in order to maximize the reception quality of the broadcast receivers, while maximizing the network broadcast capacity. Compared to the conventional broadcast schemes, the proposed framework shows an appreciable improvement in QoE levels for all users, while achieving higher energy-savings for the energy constrained users.
We consider the problem of energy-efficient point-to-point transmission of delay-sensitive data (e. g., multimedia data) over a fading channel. Existing research on this topic utilizes either physical-layer centric so...
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We consider the problem of energy-efficient point-to-point transmission of delay-sensitive data (e. g., multimedia data) over a fading channel. Existing research on this topic utilizes either physical-layer centric solutions, namely power-control and adaptive modulation and coding (AMC), or system-level solutions based on dynamic power management (DPM);however, there is currently no rigorous and unified framework for simultaneously utilizing both physical-layer centric and system-level techniques to achieve the minimum possible energy consumption, under delay constraints, in the presence of stochastic and a priori unknown traffic and channel conditions. In this paper, we propose such a framework. We formulate the stochastic optimization problem as a Markov decision process (MDP) and solve it online using reinforcement learning (RL). The advantages of the proposed online method are that 1) it does not require a priori knowledge of the traffic arrival and channel statistics to determine the jointly optimal power-control, AMC, and DPM policies;2) it exploits partial information about the system so that less information needs to be learned than when using conventional reinforcement learning algorithms;and 3) it obviates the need for action exploration, which severely limits the adaptation speed and runtime performance of conventional reinforcement learning algorithms. Our results show that the proposed learning algorithms can converge up to two orders of magnitude faster than a state-of-the-art learning algorithm for physical layer power-control and up to three orders of magnitude faster than conventional reinforcement learning algorithms.
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