High Speed Downlink Packet Access Research Articles

Energy consumption on high-speed downlink packet access transmission in the Denpasar area in 2014

The need for cellular telecommunication services is increasing every year. Cellular technology is rapidly growing in developing countries because of the lack of wired physical networks. This has an impact on increasing the energy demand.

Estimating Pole Capacity From Radio Network Performance Statistics by Supervised Learning

Network dimensioning is a critical task for cellular operators to avoid degraded user experience and unnecessary upgrades of network resources with changing mobile traffic patterns. For this purpose, smart network planning tools require accurate cell and user capacity estimates. In these tools, throughput is often used as a capacity metric due to its close relationship with user satisfaction. In this work, a comprehensive analysis is carried out to compare different well-known Supervised Learning (SL) algorithms for estimating cell and user throughput in the DownLink in busy hours from radio measurements collected on a cell basis in the Operation Support System (OSS). The considered SL approaches include random forest, shallow multi-layer perceptron, support vector regression and k-nearest neighbors. Such algorithms are compared with classical multiple linear regression and deep learning approaches considered in previous works. All these algorithms are tested in two radio access technologies: High Speed DownLink Packet Access (HSDPA) and Long Term Evolution (LTE). To this end, two datasets with the most relevant performance indicators per technology are collected from live cellular networks. Results show that non-deep SL algorithms are the most appropriate option for applications with storage constraints, such as network planning tools, since they provide a higher accuracy with reduced datasets.

Implementation of Class-Based Low Latency Fair Queueing (CBLLFQ) Packet Scheduling Algorithm for HSDPA Core Network

To provide a guaranteed Quality of Service (QoS) to real-time traffic in High-Speed Downlink Packet Access (HSDPA) core network, we proposed an enhanced mechanism. For an enhanced QoS, a Class-Based Low Latency Fair Queueing (CBLLFQ) packet scheduling algorithm is introduced in this work. Packet classification, metering, queuing, and scheduling using differentiated services (DiffServ) environment was the points in focus. To classify different types of real-time voice and multimedia traffic, the QoS provisioning mechanisms use different DiffServ code points (DSCP).The proposed algorithm is based on traffic classes which efficiently require the guarantee of services and specified level of fairness. In CBLLFQ, a mapping criterion and an efficient queuing mechanism for voice, video and other traffic in separate queues are used. It is proved, that the algorithm enhances the throughput and fairness along with a reduction in the delay and packet loss factors for smooth and worst traffic conditions. The results calculated through simulation show that the proposed calculations meet the QoS prerequisites efficiently.

A Design of Packet Scheduling Algorithm to Enhance QoS in High-Speed Downlink Packet Access (HSDPA) Core Network

Voice over Internet Protocol (VOIP) in an efficient manner is a basic requirement of modern era. The real time and non-real traffics demand customized communication provisioning to get guarantee of service. For this we proposed a user fulfillment design for facilitating packets switching in 3G cellular network to insure provisioning of QoS (quality of service) in DiffServ (Differentiated Services) Network. To enhance QoS for real time traffic by reducing delay, packet loss and jitter, we proposed Low latency queuing (LLQ) algorithm. In this paper, we focused on packet scheduling, Diffserv and QoS classes mapping into Universal Mobile telecommunication System (UMTS) classes and buffering. To associate different types of real time multimedia traffic, the QoS provisioning mechanism used different code points of Diffserv. The new idea in LLQ is to map the video and voice traffics against two separate queues and used priority queuing in Low latency queuing for voice traffic. The results got from reproductions shows that proposed calculation meets the QoS prerequisites.

Investigation of turbo decoding techniques based on lottery arbiter in 3D network on chip

In this digital age, turbo Codes have been largely favoured in various high speed wireless communication systems standards (3GPP-LTE, WiMAX and WiFi). These codes are preferred due to their high performance that corresponds to that of the Shannon limit. Due to the current trends in wireless communications, there has been a demand for high throughput and power efficiency leading to revolutionary research. The ASIP architecture, which is the multi-application specific instruction processor, has been extensively preferred for turbo decoders due to high-throughput and flexibility. The multi-ASIP turbo decoders are successfully brought forth by utilization of a network-on-chip (NoC) structure. This paper incorporates the study of the turbo decoding process, as well as analyzing the addressing patterns for various communication standards. To reduce the complexity of the NoC, mathematical calculation sequence and sub networking techniques are proposed. The arbitration of the network is done by lottery routing algorithm. The final results obtained from the structure proposed in this paper show a massive breakthrough compared to Network-on-chip (NoC). The results show a 50% improvement for High Speed Downlink Packet Access (HSDPA) and a breakthrough of 13% for Long Term Evolution (LTE) in throughput to area efficiency.

Resources Management of High Speed Downlink Packet Access Network in the Presence of Mobility

High-Speed Downlink Protocol Access (HSDPA) is a mobile telephony protocol. It is designed to increase data capacity and transfer rate. This paper presents a resource allocation strategy in the HSDPA broadband network. An admission check is proposed. It divides the coverage area of a base station (Node-B) into several regions based on the principle of Adaptive Modulation and Coding (AMC) efficiency. The call admission control (CAC) mechanism distinguishes two RT and NRT traffic according to the type of service requested by the user. It dynamically allocates an effective bandwidth to each accepted call in the system based on its modulation efficiency and maintains its initial rate during its communication.

A cooperative neural network approach for enhancing data traffic prediction

This paper addresses the problem of learning a regression model for the prediction of data traffic in a cellular network. We proposed a cooperative learning strategy that involves two Jordan recurrent neural networks (JNNs) trained using the firefly algorithm (FFA) and resilient backpropagation algorithm (Rprop), respectively. While the cooperative capability of the learning process ensures the effectiveness of the regression model, the recurrent nature of the neural networks allows the model to handle temporally evolving data. Experiments were carried out to evaluate the proposed approach using high-speed downlink packet access data demand and throughput measurements collected from different cell sites of a universal mobile telecommunications system-based cellular operator. The proposed model produced significantly superior results compared to the results obtained on the same problems from the traditional method of separately training a JNN with FFA and Rprop.

Capacity Bounds and Detection Schemes for Data Over Voice

Cellular networks provide widespread and reliable voice communications among subscribers through mobile voice channels. These channels benefit from superior priority and higher availability compared with conventional cellular data communication services, such as General Packet Radio Service, Enhanced Data Rates for GSM Evolution, and High-Speed Downlink Packet Access. These properties are of major interest to applications that require transmitting small volumes of data urgently and reliably, such as an emergency call in vehicular applications. This encourages excessive research to make digital communication through voice channels feasible, leading to the emergence of Data over Voice (DoV) technology. In this research, we investigate the challenges of transmitting data through mobile voice channels. We introduce a simplified information-theoretic model of the vocoder channel and derive bounds on its capacity. By invoking detection theory concepts and conjecturing Weibull and chi-square distributions for approximately modeling the probability distribution of channel output, we propose improved detection schemes based on the mentioned distributions and compare the achieved performances with the calculated bounds and other state-of-the-art DoV structures. Moreover, in common mobile networks, the vocoder compression rate is adopted in accordance with the network traffic adaptively. Although this phenomenon affects the overall capacity significantly, it has been overlooked by previous research studies. In this research, we apply the Gilbert–Elliott (GE) model to the voice channel, extract the required model parameters from the Markov model, and bound the overall voice channel capacity by considering the adaptive rate adjustment phenomenon.

A Performance Model for the HSDPA User Equipment and its Validation

A new queuing model is proposed for the performance evaluation of the High Speed Downlink Packet Access (HSDPA) protocol, with respect to a specified user, in UMTS networks. This analytical model is an integrated one capable of capturing many complicated features of HSDPA operation such as correlated and bursty traffic, channel fading, channel allocation policy and packet-losses in the air interface. The validation of the model for comparing the user terminal categories is performed with a detailed simulation of HSDPA terminals with "real" traffic traces. It is shown that the model is quite accurate to predict and compare the throughput of the HSDPA terminal categories.

A novel throughput mapping method for DC-HSDPA systems based on ANN

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.

Cost-Efficient, High-Volume Transmission: Advanced Transmission Design and Architecture of Next Generation RF Modems and Front-Ends

Growing demands for higher data rates and the sheer volume of data traffic have been the main drivers for the evolution of Third-Generation Partnership Project (3GPP) cellular communication standards. Increased data rates have, in turn, enabled network operators to offer consumers unparalleled performance and a seamless user experience (UX). To address future demands for even better performance, the UX has to evolve to support various new high-speed packet access (HSPA) configurations, such as dual-cell high-speed downlink (DL) packet access (DC-HSDPA), DC-HSDPA together with dual-band or multiple-input, multiple-output (MIMO), DC high-speed uplink (UL) packet access (DC-HSUPA), high-speed DL packet access (HSDPA) with MIMO, and long-term evolution (LTE) with carrier aggregation (CA).

Network-on-Chip for Turbo Decoders

The multi-application specific instruction processor (ASIP) architecture is a promising candidate for flexible high-throughput turbo decoders. This brief proposes a network-on-chip (NoC) structure for multi-ASIP turbo decoders. The process of turbo decoding is studied, and the addressing patterns for turbo codes in long term evolution (LTE) and High Speed Downlink Packet Access (HSDPA) are analyzed. Based on this analysis, two techniques, subnetworking and calculation sequence, are proposed for reducing the complexity of the NoC. The implementation results show that the proposed structure gives an improvement of 53% for HSDPA and 133% for LTE in throughput/area efficiency compared with state-of-the-art NoC solutions.

Comparison Simulator Data Rate Modulation QPSK and 16 QAM System WCDMA (Wide Code Division Multiple Access) and HSDPA (High Speed Downlink Packet Access)

HSDPA (High Speed Downlink Packet Access) is the upgrade performance data packets extraordinary against WCDMA thus producing top speed 14,4 Mbps. One of the goals the creation of HSDPA is as an improvement over previous technologies. The expected improvement of HSDPA technology increasing the data rate is capable of exceeding data rate in order to WCDMA customer satisfaction in accessing multimedia content such as streaming video and data at high speed. Data Rate is the maximum data rate that can be accepted by the UE (User Equipment) in ideal conditions. One of the factors that affect the data rate is modulation scheme used by each of the technologies. QPSK modulation is used in WCDMA system and adaptive modulation (QPSK and 16QAM) is used in HSDPA system.In the research the results obtained by selection of symbol rate of 480 kbps bit rate will yield 960 kbps while the selection symbol rate is 960 kbps will produce 1920 kbps bit rate using modulation QPSK modulation. As for 16QAM modulation, symbol rate of 480 kbps produces 1920 kbps and symbol rate is 960 kbps bit rate produces 3840 kbps. Of the trial results, the more number of bits sent then the higher data rate that can be accepted by the UE (user equipment).

Adaptive Modulation and Coding for LTE Wireless Communication

Long Term Evolution (LTE) is the new upgrade path for carrier with both GSM/UMTS networks and CDMA2000 networks. The LTE is targeting to become the first global mobile phone standard regardless of the different LTE frequencies and bands use in other countries barrier. Adaptive Modulation and Coding (AMC) is used to increase the network capacity or downlink data rates. Various modulation types are discussed such as Quadrature Phase Shift Keying (QPSK), Quadrature Amplitude Modulation (QAM). Spatial multiplexing techniques for 4×4 MIMO antenna configuration is studied. With channel station information feedback from the mobile receiver to the base station transmitter, adaptive modulation and coding can be applied to adapt to the mobile wireless channels condition to increase spectral efficiencies without increasing bit error rate in noisy channels. In High-Speed Downlink Packet Access (HSDPA) in Universal Mobile Telecommunications System (UMTS), AMC can be used to choose modulation types and forward error correction (FEC) coding rate.

Network delay modeling for assisted GPS

Currently, conventional Global Positioning System (GPS) receivers work well in open-sky environments. However, location finding in weak-signal conditions, such as urban canyons and indoors, is challenging and has been the subject of extensive research. Assisted GPS (A-GPS) is one of the concepts that helps receivers acquire weak signals by receiving assistance data from wireless networks, such as orbital parameters, and coarse time and location references. A-GPS also improves time-to-first-fix (TTFF) through faster delivery of information that is recovered from navigation data broadcast by GPS satellites. Receiver technology developers rely on signal simulators for testing real-world scenarios. While A-GPS support has been integrated in many simulators, probabilistic models of delays occurring during assistance data delivery have not been studied properly. This paper provides a methodology of A-GPS network delay modeling that is applicable to various simulation environments. Particularly, a testbed is designed to collect delay data, model them statistically and integrate the model in a simulator. The testbed employs secure user plane location (SUPL) architecture in two modes, mobile station (MS) based (MS-based) and MS-assisted, where data channels are used to communicate A-GPS assistance data.Measurement campaigns are conducted and network delay models are derived for various representative distances between assistance servers and receivers, and for various networks that users connect to, such as LAN, WLAN, third-generation mobile telecommunication (3G), high-speed downlink packet access (HSDPA), and fourth-generation long term evolution (4G LTE), with the Transmission Control Protocol and the Internet Protocol (TCP/IP) connection between a server and a receiver.

A New Packet Scheduling Scheme in Satellite HSDPA Networks

ABSTRACTSatellite access networks serve as an extension of the terrestrial access networks counterparts to provide services to areas where terrestrial access is not technically or economically viable. This paper proposes a new packet scheduling scheme that is designed for satellite high speed downlink packet access (S-HSDPA) networks using a cross-layer approach. The proposed scheduler uses the channel state information (CSI), queuing factors and application type (QoS factors) in taking scheduling decisions. The performance of the proposed scheduler is favourably compared with other schedulers in literature. This paper also investigates the effect of the signal-to-noise ratio (SNR) margin that has been introduced to compensate for the propagation delay experienced in GEO satellites in order to ensure an appropriate CSI is used by packet scheduler in the Node B of the S-HSDPA network. The optimal SNR margin that will provide the best performance (capacity) is then computed.

Network acknowledgement‐based and error‐propagation‐aware importance modelling for H.264/AVC video transmission over wireless networks

In this study, a network acknowledgement-based and error-propagation-aware (NEPA) importance model for H.264/AVC video packet is proposed. Unlike those existing models, the network acknowledgement information is firstly studied to predict the video importance in the author's NEPA model. As a result, the authors can dynamically predict the importance of the current video packet, when its referenced frames are lost. Moreover, by means of analysing the reference relationships among the macro-blocks (MBs), an error propagation/conceal map is drawn to accurately estimate the error propagation effect. The simulation results demonstrate that their NEPA model could achieve an acceptable accuracy for any video sequence as long as its group of pictures (GoP) size is not too large. Furthermore, an application example which adopts the NEPA model in High Speed Downlink Packet Access scheduling system demonstrates the effectiveness of the NEPA model.

Measurement and Modeling of Network Delays for MS-Based A-GPS Assistance Delivery

While conventional global positioning system (GPS) receivers have gained popularity for applications in open-sky environments, their performance degrades in challenging conditions, such as urban canyons and indoors. The assisted GPS (A-GPS) concept enhanced receiver capability to operate in weak signal conditions using terrestrial links to communicate helpful information such as satellite orbital parameters, coarse estimates of time and location, and so forth. The A-GPS mode has been standardized for many wireless networks and is integrated in high-end simulators to support development and testing efforts. As the terrestrial-assistance data channel becomes an important link for the receiver, the statistical modeling of information delivery delays should be addressed to simulate more adequate operation scenarios. This paper addresses this aspect by presenting a delay measurement and modeling approach for Mobile Station Based assistance data. Even though the approach can be applied to other measurement setups, this paper is presented for standardized secure user plane location architecture that exploits data channels of wireless networks to deliver assistance data. Measurement data are collected and modeled for various scenarios of relative deployment of assistance servers and receivers. Delays are modeled for LAN, WLAN, third-generation mobile telecommunication, high-speed downlink packet access, and fourth-generation long-term evolution networks, with the transmission control protocol and the Internet protocol connection between a server and receiver.

Integration of Disaster Detection and Warning System for a Smart Vehicle

For firefighters and rescuers, the disaster relief works are difficulty performed in the tunnels because of their constricted space. To reduce the losses of accident, the safety of tunnels and factories should be ordinarily kept under surveillance. Hence, a multisensor based smart tracked vehicle is designed for the application of autonomous detection and surveillance in this paper. Besides, multisensors, communication modules, wireless cameras, an electronic compass, and a GPS module are installed in the vehicle. The key feature is the integration of disaster detection and warning systems so that the vehicle can move autonomously. Furthermore, a LabVIEW graphical programming software is applied to design a human machine interface (HMI) and integrate all systems such that the vehicle can be guided by High Speed Downlink Packet Access (HSHPA) based remote control. Moreover, basic stamp microcontrollers are utilized as its control kernel such that the remote monitoring and control system (RMCS) can be constructed successfully.

Advanced Antenna Techniques and High Order Sectorization with Novel Network Tessellation for Enhancing Macro Cell Capacity in DC-HSDPA Network

Mobile operators commonly use macro cells with traditional wide beam antennas for wider coverage in the cell, but future capacity demands cannot be achieved by using them only. It is required to achieve maximum practical capacity from macro cells by employing higher order sectorization and by utilizing all possible antenna solutions including smart antennas. This paper presents enhanced tessellation for 6-sector sites and proposes novel layout for 12-sector sites. The main target of this paper is to compare the performance of conventional wide beam antenna, switched beam smart antenna, adaptive beam antenna and different network layouts in terms of offering better received signal quality and user throughput. Splitting macro cell into smaller micro or pico cells can improve the capacity of network, but this paper highlights the importance of higher order sectorization and advance antenna techniques to attain high Signal to Interference plus Noise Ratio (SINR), along with improved network capacity. Monte Carlo simulations at system level were done for Dual Cell High Speed Downlink Packet Access (DC-HSDPA) technology with multiple (five) users per Transmission Time Interval (TTI) at different Intersite Distance (ISD). The obtained results validate and estimate the gain of using smart antennas and higher order sectorization with proposed network layout.