Abstract
In order to improve support for higher data rates, third-generation partnership project (3GPP) introduced dual-carrier high-speed downlink packet access (DC-HSDPA), which reaches up to 42-Mbps throughput with the use of two adjacent 5-MHz carriers in Release-8. Defining the dependence of throughput on prevailing channel parameters is crucial because a frequency-selective channel limits achieving these data rates. For this reason, DC-HSDPA throughput real field measurements were taken in different propagation environments by using the “TEMS Investigation” program. The evaluation of the measurements showed that one-parameter linear mapping methods, such as signal-to-interference ratio and channel quality indicator, are insufficient for characterizing user throughput. Therefore, this study will propose a novel mapping method with more than one variable. Although multiple linear regression gives a better normalized root-mean-square error, results have shown that frequently used artificial neural network-based mapping methods—such as those for adaptive network-based fuzzy inference system, multilayer perceptron, and generalized regression neural network (GRNN)—yield improved accuracy. From among these, user throughput can be best estimated with the use of GRNN for a commercial DC-HSDPA system, with approximately 93.3 % precision. The GRNN structure allows system designers to update system parameters to maximize user throughput.
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Abbreviations
- ACK/NACK:
-
Acknowledgment/not acknowledgment
- ANFIS:
-
Adaptive network-based fuzzy inference system
- ANN:
-
Artificial neural network
- AMC:
-
Adaptive modulation and coding
- BLER:
-
Block error rate
- CPICH Ec/N0 :
-
Common pilot channel energy per chip over total received power spectral density
- CPICH RSCP:
-
Common pilot channel-received signal code power
- CPICH SIR:
-
Common pilot channel—signal to interference ratio
- CQI:
-
Channel quality indicator
- DC-HSDPA:
-
Dual-carrier high-speed downlink packet access
- Ec/Ior :
-
Energy per chip/noise spectral density
- GRNN:
-
Generalized regression neural network
- HARQ:
-
Hybrid automatic repeat request
- HS-DPCCH:
-
High-speed dedicated physical control channel
- HS-DSCH:
-
High-speed downlink shared channel
- HS-PDSCH:
-
High-speed physical downlink shared channel
- HS-SCCH:
-
High-speed synchronization control channel
- LM:
-
Levenberg–Marquardt
- MIMO:
-
Multiple input multiple output
- MLP:
-
Multilayer perceptron
- NRMSE:
-
Normalized root-mean-square error
- SIR:
-
Signal-to-interference ratio
- SNR:
-
Signal-to-noise ratio
- TBS:
-
Transport block size
- TTI:
-
Transmit time interval
- UE:
-
User equipment
- UMTS:
-
Universal mobile telecommunication system
- WCDMA:
-
Wideband code division multiple access
- 3GPP:
-
Third-generation partnership project
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Kurnaz, Ç., Engiz, B.K. & Esenalp, M. A novel throughput mapping method for DC-HSDPA systems based on ANN. Neural Comput & Applic 28, 265–274 (2017). https://doi.org/10.1007/s00521-015-2054-1
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DOI: https://doi.org/10.1007/s00521-015-2054-1