Joint Performance Analysis of Channel Quality Indicator Feedback Schemes and Frequency-Domain Scheduling for LTE

Donthi, Sushruth N.; Mehta, Neelesh B.

doi:10.1109/tvt.2011.2159034

Cited by 55 publications

(35 citation statements)

References 31 publications

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“…The proposed method is inefficient because there is no consideration for non-best CQI values which may have a low SNR strength. An analytical evaluation of the system performance of CQI feedback for LTE systems was addressed in [30]. Similarly, authors in [31] proposed the best-M averaging method for special processing and feedback calculation.…”

Section: Related Workmentioning

confidence: 99%

An Adaptive Threshold Feedback Compression Scheme Based on Channel Quality Indicator (CQI) in Long Term Evolution (LTE) System

Abdulhasan

Salman

et al. 2015

Wireless Pers Commun

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Channel quality indicator (CQI) feedback in long-term evolution (LTE) system is an essential technique in describing the instantaneous channel state information. The CQI calculations highly depend on the accuracy of the channel estimation process in order to assign appropriate modulation and coding scheme. However, one of the critical issues affecting the LTE system performance is obtaining the CQI for each transmission period which will inevitably cost many resources. Therefore, an appropriate method for reducing CQI feedback overhead along with accurate channel estimation technique is required to manage the allocated resources and obtains significant improvements in system performance. In this paper, an adaptive threshold feedback compression scheme based on CQI scheme is proposed to obtain better system performance in terms of system throughput and error rate in LTE system. This proposed adaptive scheme dynamically adapts its threshold level to the signal to noise ratio variations, thus increasing the throughput and reducing the CQI feedback overhead. Results show that the proposed CQI based adaptive threshold feedback compression scheme enhances the tradeoff between system throughput and block error rate.

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Section: Related Workmentioning

confidence: 99%

An Adaptive Threshold Feedback Compression Scheme Based on Channel Quality Indicator (CQI) in Long Term Evolution (LTE) System

Abdulhasan

Salman

et al. 2015

Wireless Pers Commun

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“…In each subframe, the MAC scheduler of the eNB decides which Resource Block (RB) has to be allocated to which user. This is performed with the help of the Channel Quality Indicator (CQI) reporting mechanism [4]. The UE, periodically or when requested by the eNB, monitors the downlink channel quality based on the downlink data traffic as well as the reference signals transmitted by the eNB.…”

Section: A Ltementioning

confidence: 99%

Dynamic DRX algorithms for reduced energy consumption and delay in LTE networks

Sivalingam

Tung

et al. 2014

2014 IFIP Wireless Days (WD)

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Abstract-The Long Term Evolution (LTE) standard specifies the Discontinuous Reception Mechanism (DRX) mechanism for saving power at the User Equipment (UE). Here, a UE switches off its RF circuitry when there are no packets to be transmitted or received. The existing DRX algorithms use static operational parameters that are determined by the evolved nodeB (eNB) at the start of a UE's session. During the switch-off period, packets destined to the UE are buffered in the eNB leading to higher packet latency. This paper presents two adaptive algorithms to dynamically adjust the DRX parameters, in order to reduce both energy consumption and the extra delay incurred. The algorithms use application Quality-of-Service and channel quality information to adjust the DRX parameters. ns3-based simulation performance studies show that the algorithms are able to reduce packet delay compared to static DRX by up to 60%, 60% and 75% and reduce energy consumption by up to 75%, 43% and 90% for video streaming, VoIP and bursty data applications respectively. I. INTRODUCTIONLong Term Evolution (LTE) is a fourth generation wireless technology, designed to provide data rate and reduced latency to users [1]. LTE uses advanced physical layer techniques that lead to increased power consumption of the User Equipment (UE). The LTE standards have proposed the Discontinuous Reception mechanism (DRX) method to save battery power by enabling the UE to switch off its RF circuitry in the absence of packets for transmission and reception. Despite the use of DRX, an LTE UE is about 23 times less power efficient compared to WiFi and even worse compared to 3G [2]. Hence, there is a need to improve the operation of DRX for better power savings.A DRX-enabled UE listens to the downlink control channel at intervals determined by DRX parameters that are established by the base station, i.e. evolved NodeB (eNB), at the time of session establishment. The parameters include DRX short cycle, DRX long cycle, and DRX Inactivity Timer. These timers have a significant impact on power savings and the delay incurred by the UE applications. When the UE is in sleep mode, the packets intended for the UE get buffered at the enodeB till the UE returns to active mode. If the UE follows a long sleep cycle, it can save more power; however, the delay incurred by the application also increases. Similarly, the channel quality experienced by the users will also impact when, and for how long, the UE has to remain awake to receive the packets. A high channel quality implies a longer sleep time and vice-versa. Thus, there is a need to update the DRX parameters so that the trade-off between the power savings and the application delay is well-balanced.

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“…To evaluate this probability, we need the PDF of the EESM of ordered subband effective SNRs, which is analytically intractable. We circumvent this problem by deriving an approximate expression that involves only a single integral as follows [21]:…”

Section: A Proof Of Claimmentioning

confidence: 99%

“…However, EESM was not considered and the analysis was limited to determining the fading-averaged probability that channel information about a given number of clusters of subcarriers is fed back. While [19]- [21] did model the coarseness, the arithmetic mean (AM) of the subcarrier SNRs was used. The AM is less accurate than the EESM [3], but entails a simpler and easier analysis.…”

Section: Introductionmentioning

confidence: 99%

An Accurate Model for EESM and its Application to Analysis of CQI Feedback Schemes and Scheduling in LTE

Donthi

Mehta²

2011

IEEE Trans. Wireless Commun.

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Abstract-The Effective Exponential SNR Mapping (EESM)is an indispensable tool for analyzing and simulating next generation orthogonal frequency division multiplexing (OFDM) based wireless systems. It converts the different gains of multiple subchannels, over which a codeword is transmitted, into a single effective flat-fading gain with the same codeword error rate. It facilitates link adaptation by helping each user to compute an accurate channel quality indicator (CQI), which is fed back to the base station to enable downlink rate adaptation and scheduling. However, the highly non-linear nature of EESM makes a performance analysis of adaptation and scheduling difficult; even the probability distribution of EESM is not known in closed-form. This paper shows that EESM can be accurately modeled as a lognormal random variable when the subchannel gains are Rayleigh distributed. The model is also valid when the subchannel gains are correlated in frequency or space. With some simplifying assumptions, the paper then develops a novel analysis of the performance of LTE's two CQI feedback schemes that use EESM to generate CQI. The comprehensive model and analysis quantify the joint effect of several critical components such as scheduler, multiple antenna mode, CQI feedback scheme, and EESM-based feedback averaging on the overall system throughput.Index Terms-Effective exponential SNR mapping (EESM), long term evolution (LTE), orthogonal frequency division multiplexing (OFDM), channel quality feedback, multiple antenna diversity, frequency-domain scheduling, adaptive modulation and coding, lognormal random variable.

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Joint Performance Analysis of Channel Quality Indicator Feedback Schemes and Frequency-Domain Scheduling for LTE

Cited by 55 publications

References 31 publications

An Adaptive Threshold Feedback Compression Scheme Based on Channel Quality Indicator (CQI) in Long Term Evolution (LTE) System

An Adaptive Threshold Feedback Compression Scheme Based on Channel Quality Indicator (CQI) in Long Term Evolution (LTE) System

Dynamic DRX algorithms for reduced energy consumption and delay in LTE networks

An Accurate Model for EESM and its Application to Analysis of CQI Feedback Schemes and Scheduling in LTE

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