Book•
4G: LTE/LTE-Advanced for Mobile Broadband
21 Mar 2011-
TL;DR: In this article, the authors focus on LTE with full updates including LTE-Advanced to provide a complete picture of the LTE system, including the physical layer, access procedures, broadcast, relaying, spectrum and RF characteristics, and system performance.
Abstract: Based on the bestseller "3G Evolution - HSPA and LTE for mobile broadband" and reflecting the ongoing success of LTE throughout the world, this book focuses on LTE with full updates including LTE-Advanced to provide a complete picture of the LTE system. Overview and detailed explanations are given for the latest LTE standards for radio interface architecture, the physical layer, access procedures, broadcast, relaying, spectrum and RF characteristics, and system performance. Key technologies presented include multi-carrier transmission, advanced single-carrier transmission, advanced receivers, OFDM, MIMO and adaptive antenna solutions, advanced radio resource management and protocols, and different radio network architectures. Their role and use in the context of mobile broadband access in general is explained. Both a high-level overview and more detailed step-by-step explanations of the LTE/LTE-Advanced implementation are given. An overview of other related systems such as GSM/EDGE, HSPA, CDMA2000, and WIMAX is also provided. This book is a 'must-have' resource for engineers and other professionals in the telecommunications industry, working with cellular or wireless broadband technologies, giving an understanding of how to utilize the new technology in order to stay ahead of the competition. The authors of the book all work at Ericsson Research and have been deeply involved in 3G and 4G development and standardisation since the early days of 3G research. They are leading experts in the field and are today still actively contributing to the standardisation of LTE within 3GPP. Includes full details of the latest additions to the LTE Radio Access standards and technologies up to and including 3GPP Release 10Clear explanations of the role of the underlying technologies for LTE, including OFDM and MIMO Full coverage of LTE-Advanced, including LTE carrier aggregation, extended multi-antenna transmission, relaying functionality and heterogeneous deploymentsLTE radio interface architecture, physical layer, access procedures, MBMS, RF characteristics and system performance covered in detail
Citations
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18 Mar 2015
TL;DR: This paper introduces the idea of dynamically configuring cells in wireless networks to form single frequency networks based on the multimedia traffic demands from users in each cell and proposes a heuristic algorithm to solve the resource allocation problem in such complex networks.
Abstract: Although the capacity of cellular networks has increased with recent generations, the growth in demand of wireless bandwidth has outpaced this increase in capacity Not only more users are relying on wireless networks, but also the demand from each user has substantially increased For example, it has become common for mobile users to stream full TV episodes, sports events, and movies while on the go Further, as the capabilities of mobile devices improve, the demand for higher quality and even 3D videos will escalate, which will strain cellular networks Therefore, efficient utilization of the expensive and limited wireless spectrum remains an important problem, especially in the context of multimedia streaming services that consume a large portion of the wireless capacity In this paper, we introduce the idea of dynamically configuring cells in wireless networks to form single frequency networks based on the multimedia traffic demands from users in each cell We formulate the resource allocation problem in such complex networks with the goal of maximizing the number of served multimedia streams We prove that this problem is NP-Complete, and we propose a heuristic algorithm to solve it Through detailed packet-level simulations, we show that the proposed algorithm can achieve substantial improvements in the number of streams served as well the energy saving of mobile devices For example, our algorithm can serve up to 40 times more users compared to the common unicast streaming approach, and it achieves at least 80% and up to 400% improvement compared to multicast approaches that do not use single frequency networks
3 citations
Cites methods from "4G: LTE/LTE-Advanced for Mobile Bro..."
...For example, our algorithm can serve up to 40 times more users compared to the common unicast streaming approach, and it achieves at least 80% and up to 400% improvement compared to multicast approaches that do not use single frequency networks....
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Dissertation•
01 Jan 2018
TL;DR: A novel non-intrusive objective method for QoS measurement and prediction using neural networks is introduced in LTE networks and the Bayesian Regularization algorithm with 4 neurons in the hidden layer and sigmoid symmetric transfer function was identified as the best solution.
Abstract: This research aimed to introduce a novel approach for non-intrusive objective
measurement of voice Quality of Service (QoS) in LTE networks. While achieving this aim, the thesis established a thorough knowledge of how voice traffic is
handled in LTE networks, the LTE network architecture and its similarities and
differences to its predecessors and traditional ground IP networks and most
importantly those QoS affecting parameters which are exclusive to LTE environments. Mean Opinion Score (MOS) is the scoring system used to measure
the QoS of voice traffic which can be measured subjectively (as originally intended). Subjective QoS measurement methods are costly and time-consuming,
therefore, objective methods such as Perceptual Evaluation of Speech Quality
(PESQ) were developed to address these limitations. These objective methods
have a high correlation with subjective MOS scores. However, they either require individual calculation of many network parameters or have an intrusive
nature that requires access to both the reference signal and the degraded signal
for comparison by software. Therefore, the current objective methods are not
suitable for application in real-time measurement and prediction scenarios.
A major contribution of the research was identifying LTE-specific QoS affecting parameters. There is no previous work that combines these parameters to
assess their impacts on QoS.
The experiment was configured in a hardware in the loop environment. This
configuration could serve as a platform for future research which requires simulation of voice traffic in LTE environments.
The key contribution of this research is a novel non-intrusive objective method
for QoS measurement and prediction using neural networks. A comparative
analysis is presented that examines the performance of four neural network
algorithms for non-intrusive measurement and prediction of voice quality over
LTE networks. In conclusion, the Bayesian Regularization algorithm with 4 neurons in the hidden layer and sigmoid symmetric transfer function was identified as the best solution with a Mean Square Error (MSE) rate of 0.001 and
regression value of 0.998 measured for the testing data set.
3 citations
Cites background from "4G: LTE/LTE-Advanced for Mobile Bro..."
...Ever since the first experiments with radio communications conducted in the 1890s by Guglielmo Marconi [4], and introduction of mobile telecommunication systems in late 1900s, mobility has had strong impacts on our everyday lives....
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23 Apr 2015
TL;DR: In this article, the authors proposed a method for joint estimation of carrier frequency offsets (CFO) of multiple active users in an orthogonal frequency division multiple access (OFDMA) uplink using the recently developed bat algorithm.
Abstract: In this paper, we propose a method for joint estimation of carrier frequency offsets (CFO) of multiple active users in an orthogonal frequency division multiple access (OFDMA) uplink using the recently-developed bat algorithm. An initialization technique that can drastically reduce the total computational complexity of joint maximum likelihood (ML) estimation problems is employed to make the metaheuristic bat algorithm more efficient. This initialization improves the convergence rate of the estimator and thus reduces its total computational load in a significant manner. The CFO estimates obtained from the proposed method are also characterized by low mean square error values compared to a conventional implementation of the bat algorithm for the problem. The efficacy of the proposed method is substantiated through computer simulation studies.
3 citations
TL;DR: The aim of this paper is to discuss the well-designed PHY Channels which provide high cell-edge performance with specific features, such as dynamic bandwidth allocation to users, the design of reference signals and control channels.
Abstract: Long Term Evolution (LTE) defines a number of physical channels to carry information blocks received from the MAC and higher layers. This paper presents two types of Physical channels: the first type is downlink physical channels which consist of Physical Broadcast Channel (PBCH), Physical Downlink Shared Channel (PDSCH), Physical Multicast Channel (PMCH), Physical Downlink Control Channel (PDCCH), Physical Control Format Indicator Channel (PCFICH) and Physical Hybrid ARQ Indicator Channel (PHICH). The second type of Physical channels is uplink physical channels which consist of Physical Uplink Shared Channel (PUSCH), Physical Uplink Control Channel (PUCCH) and Physical Random Access Channel (PRACH). This paper also highlights the structure of PDSCH and PUSCH, discuss the algorithms of the two types of physical channel and each of its features. The aim of this paper is to discuss the well-designed PHY Channels which provide high cell-edge performance with specific features, such as dynamic bandwidth allocation to users, the design of reference signals and control channels. These channels take into account a more challenging path loss and interference environment at the cell edge.
3 citations
Cites background from "4G: LTE/LTE-Advanced for Mobile Bro..."
...PDSCH or DL-SCH - carries data to the UE (payload) and finally PMCH - carries the downlink payload....
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...Once the random access is successful, the message is transmitted in the UL-SCH....
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...Transport channels for uplink are as follows: UL-SCH: Uplink Shared Channel is for HARQ, dynamic link adaptation, support for UE DRX, and dynamic and semi static resource allocation with 1/3 turbo coding....
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...6 outlines the different steps of the UL-SCH physical-layer processing....
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...6: Physical layer processing for UL-SCH [4]...
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TL;DR: The coordination between goals and design parameters that must be considered in the design phase to exploit the available features of the PHY and MAC layers and avoid the limitations is presented.
Abstract: Resource allocation management is one of the effective factors in the performance of WiMAX base station. Various goals could be achieved when the resource allocation scheme exploits in the right direction. However, resource allocation schemes lack a uniform assessment metrics. Where, most of the researches trying to show author's perspective in the results to show design pros, whilst the overall performance in resource allocation perspective is mostly missing. This paper presents the coordination between goals and design parameters that must be considered in the design phase to exploit the available features of the PHY and MAC layers and avoid the limitations. Moreover, this paper proposes a new method of primary assessment for resource allocation algorithms to ease conducting a fair comparison between the relevant algorithms. The assessment methodology based on a set of evaluation questions. The obtained results showed that the new assessment method distinguishes the overall performance to provide fair comparison.
3 citations
Cites background from "4G: LTE/LTE-Advanced for Mobile Bro..."
...Cross layer design produces a NP-problem algorithm [16]....
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