AMC and HARQ: Effective capacity analysis

Sassioui, Redouane; Szczeciński, Leszek; Le, Long Bao; Benjillali, Mustapha

doi:10.1109/wcnc.2016.7564779

Cited by 13 publications

(18 citation statements)

References 15 publications

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“…Indeed an extensive work has been done on EC modelling of wireless channel while taking into account the video streaming applications [39], [49]- [52], [56]- [71], [73]- [80]. In the above mentioned works, authors have used the EC model in different fading conditions, such as Rayleigh, Nakagami-m, and Rician.…”

Section: Video Applicationsmentioning

confidence: 99%

“…In cellular networks, with statistical QoS provisioning, Rayleigh fading has been extensively evaluated with EC metric. In CRNs with multiple channels, prediction related to multiple interference has also been studied with Nakagami-m Networks [21], [33], [39], [57], [58], [60]- [62], [65], [77], [81], [93]- [124] Rician [42], [45], [70], [125] Log-Normal [126] Weibull [127] Generalized Fading Models [52], [128]- [131] Rayleigh Fading Channels [6], [23], [26], [28], [29], [31], [32], [35], [41], [44], [49], [54], [66]- [69], [73]- [75], [79], [80], [83], [84], [132]- [218] 2D [160] Multidimensional [219] Turbulence Model [220]- [223] Gamma Fading…”

Section: A Stochastic Fading Modelsmentioning

confidence: 99%

“…Traditional ARQ [117] Selective Repeat ARQ (SR-ARQ) [160] Network Coded ARQ (NC-ARQ) [226] Two-Mode ARQ [226] Multi-Layer ARQ [226] Traditional HARQ [49] Type-1 HARQ [173] Chase combining HARQ (CC-HARQ) [173] Incremental redundancy HARQ (HARQ-IR) [173], [200], [296] Persistent HARQ [226] Truncated HARQ [226]…”

Section: Hybrid-arq (Harq)mentioning

confidence: 99%

“…1) Traditional HARQ: To deal with challenging conditions of dynamic wireless medium, different transmission schemes including the adaptive modulation coding (AMC) and HARQ have been introduced and then have been investigated with their achievable EC. Authors in [49], have provided a comparative view of AMC and HARQ while considering the EC model. Delay caused by AMC and HARQ has been taken into account to analyse the performance of the above both.…”

Section: B Hybrid Automatic Repeat Request (Harq)mentioning

confidence: 99%

See 3 more Smart Citations

Effective Capacity in Wireless Networks: A Comprehensive Survey

Amjad

Musavian

Rehmani

2019

IEEE Commun. Surv. Tutorials

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Low latency applications, such as multimedia communications, autonomous vehicles, and Tactile Internet are the emerging applications for next-generation wireless networks, such as 5th generation (5G) mobile networks. Existing physicallayer channel models, however, do not explicitly consider qualityof-service (QoS) aware related parameters under specific delay constraints. To investigate the performance of low-latency applications in future networks, a new mathematical framework is needed. Effective capacity (EC), which is a link-layer channel model with QoS-awareness, can be used to investigate the performance of wireless networks under certain statistical delay constraints. In this paper, we provide a comprehensive survey on existing works, that use the EC model in various wireless networks. We summarize the work related to EC for different networks such as cognitive radio networks (CRNs), cellular networks, relay networks, adhoc networks, and mesh networks. We explore five case studies encompassing EC operation with different design and architectural requirements. We survey various delay-sensitive applications such as voice and video with their EC analysis under certain delay constraints. We finally present the future research directions with open issues covering EC maximization.

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Section: Video Applicationsmentioning

confidence: 99%

Section: A Stochastic Fading Modelsmentioning

confidence: 99%

Section: Hybrid-arq (Harq)mentioning

confidence: 99%

Section: B Hybrid Automatic Repeat Request (Harq)mentioning

confidence: 99%

See 2 more Smart Citations

Effective Capacity in Wireless Networks: A Comprehensive Survey

Amjad

Musavian

Rehmani

2019

IEEE Commun. Surv. Tutorials

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“…In the literature, the papers related to effective capacity are twofold: on the hand, they offer some simplified or exact expressions for the effective capacity under certain asymptotic regimes as in [4], [5] or compare numerically the effective capacity of some practical schemes as in [6]. On the other hand, they are devoted to resource allocation with effective capacity as the performance metric.…”

Section: Introductionmentioning

confidence: 99%

Effective Capacity Based Resource Allocation for Rayleigh-Fading Parallel Channels

Ciblat¹,

Stupia²,

Vandendorpe³

2018

2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

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We address the problem of allocating different powers amongst parallel channels when effective capacity is the performance metric and sum-power is constrained. We assume that Chase-Combining-HARQ mechanism is applied. Closedform expressions for the powers are exhibited. Numerical comparisons with other power allocations obtained through either ergodic capacity or throughput optimizations are done.

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Age of error information and throughput for truncated and layer‐coded HARQ‐based satellite‐IoT systems

Zhao,

Jia,

Xie

et al. 2023

Int J Communication

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SummaryThe work focuses on the simultaneous improvement on the throughput and information freshness of the promising satellite‐based Internet of Things (S‐IoT). To this end, we first propose a method based on the adaptive modulation coding (AMC) and truncated layer‐coded hybrid automatic repeat request (L‐HARQ) strategies by especially considering the difference in the channel state information (CSI) between the transmitter and receiver. On account of the large signal delay of the S‐IoT systems, this paper establishes the channel model based on the correlation of the signal‐to‐noise ratio (SNR) under the outdated channel and the ideal channel. Secondly, considering the fact that the improved backtrack decoding is used in the L‐HARQ, the classical definition of age of information (AoI) is insufficient to quantify the status update freshness, we propose the age of error information (AoEI), which is defined as the elapsed time since the generation of the lastly successfully backtrack‐decoded status update. Thirdly, we characterize the statistical descriptions of the maximum wait time of the successfully recovered status updates and the interdeparture time between the two consecutive status update packets that are lastly successfully received. Then, the closed‐form expression of average AoEI is derived under the assumption of independent and identically distributed fading channels. Finally, the Markov decision process (MDP) framework is used to optimize the packet parameters in each round of L‐HARQ process under the general fading scenario. Thereby, the optimized transmission scheme that minimizes AoI with throughput constraint is solved. The simulations investigate the effect of system parameters on the average AoEI.

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AMC and HARQ: Effective capacity analysis

Cited by 13 publications

References 15 publications

Effective Capacity in Wireless Networks: A Comprehensive Survey

Effective Capacity in Wireless Networks: A Comprehensive Survey

Effective Capacity Based Resource Allocation for Rayleigh-Fading Parallel Channels

Age of error information and throughput for truncated and layer‐coded HARQ‐based satellite‐IoT systems

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