Channel Quality Indicator Feedback in Long Term Evolution (LTE) System

Ibrahim, Makram

doi:10.9790/2834-09241419

Cited by 10 publications

(6 citation statements)

References 8 publications

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“…If a user is allocated a specific PRB, the eNB chooses the appropriate MCS according to the CQI reported by the user. Table II lists the CQI and the SINR switching threshold for the corresponding MCS that satisfies a 10% Block Error Rate (BLER) [33]. We assume VoLTE is configured to use the Adaptive Multi-Rate Wideband (AMR-WB) 12.65 coder, and Robust Header Compression (RoHC) is enabled.…”

Section: System Modelmentioning

confidence: 99%

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Scheduling for VoLTE: Resource Allocation Optimization and Low-Complexity Algorithms

Mohseni

Banani

Eckford

et al. 2019

IEEE Trans. Wireless Commun.

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We consider scheduling and resource allocation in long-term evolution (LTE) networks across voice over LTE (VoLTE) and best-effort data users. The difference between these two is that VoLTE users get scheduling priority to receive their required quality of service. As we show, strict priority causes data services to suffer. We propose new scheduling and resource allocation algorithms to maximize the sumor proportional fair (PF) throughout amongst data users while meeting VoLTE demands. Essentially, we use VoLTE as an example application with both a guaranteed bit-rate and strict application-specific requirements. We first formulate and solve the frame-level optimization problem for throughput maximization; however, this leads to an integer problem coupled across the LTE transmission time intervals (TTIs). We then propose a TTI-level problem to decouple scheduling across TTIs. Finally, we propose a heuristic, with extremely low complexity. The formulations illustrate the detail required to realize resource allocation in an implemented standard. Numerical results show that the performance of the TTI-level scheme is very close to that of the frame-level upper bound. Similarly, the heuristic scheme works well compared to TTI-level optimization and a baseline scheduling algorithm. Finally, we show that our PF optimization retains the high fairness index characterizing PF-scheduling.

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Section: System Modelmentioning

confidence: 99%

“…CQI index, SINR switching threshold and corresponding MCS for 10% BLER[33] Because VoLTE users have a critical constraint on delay, they (traditionally) receive higher scheduling priority. Given the granularity of the allowed scheduling, as described above, a simplistic strict priority-based scheduler (our baseline scheme) would be inefficient.…”

mentioning

confidence: 99%

Scheduling for VoLTE: Resource Allocation Optimization and Low-Complexity Algorithms

Mohseni

Banani

Eckford

et al. 2019

IEEE Trans. Wireless Commun.

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“…The total power P T at the BS is 40W which is a typical value for macro cell base station at the antenna connector. 15 UEs are placed at different locations in the cell and one UE in each CQI zone, as seen in Figure 2. The UEs are placed at the further edge of each CQI zone, which is the worst channel quality in each CQI zone.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Thresholds were set to the SINR values with the Block Error Rate (BLER) smaller than 10% for the MCSs and mapping between SINR value, and CQI were also provided. In [15], CQI values were derived by calculating the post-detection SINR from the instantaneous channel quality measured at the receiver side.…”

Section: A Related Workmentioning

confidence: 99%

Optimal power allocation for LTE users with different modulations

Wang

Abdelhadi

Clancy

2016

2016 Annual IEEE Systems Conference (SysCon)

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In this paper, we demonstrate the optimal power allocation for QPSK, 16-QAM, and 64-QAM modulation schedules and the role of channel quality indicator (CQI). We used sigmoidal-like utility functions to represent the probability of successful reception of packets at user equipment (UE). CQI as a feedback to the base station (BS) indicates the data rate that a downlink channel can support. With Levenberg-Marquardt (LM) Optimization method, we present utility functions of different CQI values for standardized 15 Modulation order and Coding Scheme (MCS) in 3 rd Generation Partnership Project (3GPP). Finally, we simulate and show the results of the optimal power allocation algorithm.

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“…It can have values from 1 to 5. Since the channel is time varying, either loss of packet [8,9,11,17] due to delay created by SH or packet error rate (PER) due to low channel conditions can occur. MOS=(𝑟1+𝑟2.…”

Section: Spectrum Handoff (Sh)mentioning

confidence: 99%

Reinforcement Learning Based Handoff Mechanism in Cooperative Cognitive Radio Networks

Mathai¹,

Indumathi²

2021

DSA

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The spectrum handoff (SH) is a dynamic spectrum access technique which ensures effective channel utilization, fair resource allocation, as well as uninterrupted real-time connection. Facilitating SH across traffics of dissimilar characteristics in Cognitive Radio Networks (CRNs) is posing difficulty due to manifold interventions from Primary Users (PUs), disagreement among Secondary Users (SUs) and diversified Quality of Experience (QoE) demand. Here, we consider effective channel selection strategy (CSS) and put forward a learning-based handoff scheme to enhance QoE demand of users by the introduction of docition idea. A PU prioritized Markov method is introduced to represent the communications between PUs and SUs for even channel access. The reinforcement learning (RL) is applied to CSS to carry out proper channel selection. Numerical outcomes projects that proposed queuing model, suggested learning based handoff scheme and docitive learning enhances the quality of service by maintaining the average MOS of 3.6.

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Channel Quality Indicator Feedback in Long Term Evolution (LTE) System

Abstract: LTE is a 3GPP evolution of UMTS that is envisaged to

Cited by 10 publications

References 8 publications

Scheduling for VoLTE: Resource Allocation Optimization and Low-Complexity Algorithms

Scheduling for VoLTE: Resource Allocation Optimization and Low-Complexity Algorithms

Optimal power allocation for LTE users with different modulations

Reinforcement Learning Based Handoff Mechanism in Cooperative Cognitive Radio Networks

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