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Journal ArticleDOI

LTE-advanced: next-generation wireless broadband technology [Invited Paper]

01 Jun 2010-IEEE Wireless Communications (IEEE Press)-Vol. 17, Iss: 3, pp 10-22
TL;DR: An overview of the techniques being considered for LTE Release 10 (aka LTEAdvanced) is discussed, which includes bandwidth extension via carrier aggregation to support deployment bandwidths up to 100 MHz, downlink spatial multiplexing including single-cell multi-user multiple-input multiple-output transmission and coordinated multi point transmission, and heterogeneous networks with emphasis on Type 1 and Type 2 relays.
Abstract: LTE Release 8 is one of the primary broadband technologies based on OFDM, which is currently being commercialized. LTE Release 8, which is mainly deployed in a macro/microcell layout, provides improved system capacity and coverage, high peak data rates, low latency, reduced operating costs, multi-antenna support, flexible bandwidth operation and seamless integration with existing systems. LTE-Advanced (also known as LTE Release 10) significantly enhances the existing LTE Release 8 and supports much higher peak rates, higher throughput and coverage, and lower latencies, resulting in a better user experience. Additionally, LTE Release 10 will support heterogeneous deployments where low-power nodes comprising picocells, femtocells, relays, remote radio heads, and so on are placed in a macrocell layout. The LTE-Advanced features enable one to meet or exceed IMT-Advanced requirements. It may also be noted that LTE Release 9 provides some minor enhancement to LTE Release 8 with respect to the air interface, and includes features like dual-layer beamforming and time-difference- of-arrival-based location techniques. In this article an overview of the techniques being considered for LTE Release 10 (aka LTEAdvanced) is discussed. This includes bandwidth extension via carrier aggregation to support deployment bandwidths up to 100 MHz, downlink spatial multiplexing including single-cell multi-user multiple-input multiple-output transmission and coordinated multi point transmission, uplink spatial multiplexing including extension to four-layer MIMO, and heterogeneous networks with emphasis on Type 1 and Type 2 relays. Finally, the performance of LTEAdvanced using IMT-A scenarios is presented and compared against IMT-A targets for full buffer and bursty traffic model.
Citations
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Dissertation
01 Jan 2017
TL;DR: In this paper, a cooperative power control scheme with closed-form solution is derived, where base stations dynamically control their own transmit powers to satisfy the data rate requirements of the users connected to neighboring base stations.
Abstract: The concept of cooperation where two or more parties work together to pursue a common goal, is applicable in almost every aspect of today's life. For instance, in the upcoming car-to-car communications, the vehicles exchange information regarding their current status and potential threats on the road in order to avoid accidents. With the evolution of the wireless communication systems and the advent of new services and devices with more capabilities, the demand for higher data rates is ever increasing. In cellular networks, the achievable data rates of the users are limited by the inter-cell interference, which is caused by the simultaneous utilization of the time/frequency resources. Especially, the data rates of the users located at the vicinity of neighboring base stations is affected by the inter-cell interference. Hence, in this dissertation, cooperation in cellular communication downlink networks is investigated, where the base stations coordinate their operation in order to mitigate the impact of co-channel inter-cell interference. Thus, the constantly increasing user demand can be satisfied. Cooperative resource allocation schemes are derived, where practical conditions and side constraints regarding the available channel state information at the base stations are taken into account. Cooperation in the form of power control and joint time/frequency scheduling is mainly studied. In the former type of cooperation, the base stations dynamically adjust their own transmit powers to cause less inter-cell interference to the users connected to neighboring base stations. In the case of cooperative scheduling, the available time/frequency resources are jointly allocated by the base stations in order to trade off user throughput and inter-cell interference. The cooperative scheduling schemes apply two special cases of the power control approach, where the base stations either serve their connected users with maximum transmit power, or abstain from transmitting data, i.e., muting, in order to reduce the interference caused to users served by neighboring base stations. One major contribution of this work is the formulation of the cooperative resource allocation problems by considering the availability of channel state information at the transmitter in form of data rate measurement reports, which follows standard compliant procedures of current mobile networks such as LTE and LTE-Advanced. From a system perspective, two parameters are considered throughout this dissertation in order to derive the proposed cooperative schemes. These parameters are the cooperation architecture and the traffic model characterizing the demand of the connected users. In the case of the cooperation architecture, centralized and decentralized schemes are studied. In the former, a central controller performs the cooperative schemes based on global knowledge of the channel state information, and in the latter, the cooperative decisions are carried out independently per base station based on local information exchanged with adjacent base stations. It is expected that the centralized architecture provides the best performance, however, the gap with respect to the decentralized approaches reduces significantly under practical network assumptions, as demonstrated in this work based on numerical simulations. With respect to the traffic model, the user demand is characterized by full-buffer and non-full-buffer models. The first model is applied in order to assess the performance of the proposed cooperative schemes from a capacity enhancement perspective, where all users constantly demand as much data as possible. On the other hand, the non-full-buffer model represents a more practical network scenario with a dynamic utilization of the network resources. In the non-full-buffer model case, the proposed schemes are derived in order to improve the link adaptation procedures at the base stations serving users with bursty traffic. These link adaptation procedures, establish the transmission parameters used per serving link, e.g., the transmit power, the modulation and the coding schemes. Specifically, a cooperative power control scheme with closed-form solution is derived, where base stations dynamically control their own transmit powers to satisfy the data rate requirements of the users connected to neighboring base stations. Moreover, centralized and decentralized coordinated scheduling with muting is studied to improve the user throughput. For the centralized case, an integer linear problem formulation is proposed which is solved optimally by using commercial solvers. The optimal solution is used as a benchmark to evaluate heuristic algorithms. In the case of decentralized coordinated scheduling with muting, a heuristic approach is derived which requires a low number of messages exchanged between the base stations in order to coordinate the cooperation. Finally, an integer linear problem is formulated to improve the link adaptation procedures of networks with user demand characterized by bursty traffic. This improvement results in a reduction of the transmission error rates and an increase of the experienced data rates. With respect to non-cooperative approaches and state-of-the-art solutions, significant performance improvement of the achievable user throughput is obtained as the result of applying the proposed cooperative schemes, especially for the users experiencing severe inter-cell interference.
Posted Content
TL;DR: In this paper, the authors proposed a new model that helps GSM radio frequency engineers to choose the optimal value of hysteresis parameter for Ericsson BTS power saving algorithm which aims to switch OFF unused frequency channels, their model is based on unsupervised machine learning clustering K-means algorithm.
Abstract: Gaza Strip suffers from a chronic electricity deficit that affects all industries including the telecommunication field, so there is a need to optimize and reduce power consumption of the telecommunication equipment. In this paper we propose a new model that helps GSM radio frequency engineers to choose the optimal value of hysteresis parameter for Ericsson BTS power saving algorithm which aims to switch OFF unused frequency channels, our model is based on unsupervised machine learning clustering K-means algorithm. By using our model with BTS power saving algorithm we reduce number of active TRX by 20.9%.
30 Apr 2019
TL;DR: The purpose of this research is to implement the internet of things (IoT) system into a food court place to reduce its service time and cost and there will be no need for waiter and cashier employees.
Abstract: The purpose of this research is to implement the internet of things (IoT) system into a food court place to reduce its service time and cost. The IoT will handle the security and the payment of this self-service food court. Thus, there will be no need for waiter and cashier employees. We created a mobile and server side application and also a food container boxes equipped with the IoT devices to handle this food court service operations. Each food container has a quick response (QR) code for its identification. These food containers only can be opened by smartphone through the food court app by scanning the container’s QR code, while the IoT system will get the user identification and measure how many foods that the buyer took. Then, the payment will be handled back through the mobile application.

Cites background from "LTE-advanced: next-generation wirel..."

  • ...Today, smartphones are already connected into the 4th generation of the wireless communication system that can provide sufficient data speed and quality [2]....

    [...]

Proceedings ArticleDOI
01 May 2017
TL;DR: In the modification process a general framework for the use of wireless networks using load-balancing to alteration the data and monitoring with emphasis on Authentication and security during the data transfer is proposed.
Abstract: Data dissemination is big issue to mobile users using a wireless network. Wireless networks face many difficulties like limited resources and high susceptibility to harsh environmental conditions that have to be considered carefully. The load-balancing algorithm can afford the accelerate path to reach the destination without any packet loss. After the nodes being allocated the data will be transferred to the sink and is secure to the control host, which issues commands and configures the network. In the modification process a general framework for the use of wireless networks using load-balancing to alteration the data and monitoring with emphasis on Authentication and security during the data transfer is proposed.

Additional excerpts

  • ...kalyan chakaravarthi [1] PG Scholar [1], Dept....

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References
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Proceedings ArticleDOI
01 Sep 2006
TL;DR: A preliminary look at the air interface for Evolved UTRA (E-UTRA) and associated key technologies required to reach its design objectives are provided.
Abstract: With the emergence of packet-based wireless broadband systems such as 802.16e, it is evident that a comprehensive evolution of the universal mobile telecommunications system specifications is required to remain competitive. As a result, work has begun on long term evolution (LTE) of the UMTS terrestrial radio access and radio access network aimed for commercial deployment in 2010. Goals for the evolved system include support for improved system capacity and coverage, high peak data rates, low latency, reduced operating costs, multi-antenna support, flexible bandwidth operations and seamless integration with existing systems. To reach these goals, a new design for the air interface is envisioned. This paper provides a preliminary look at the air interface for Evolved UTRA (E-UTRA) and associated key technologies required to reach its design objectives. Initial E-UTRA system performance results show a 2 to 3x improvement over a reference Rel-6 UMTS system configuration [1, 2] for both uplink and downlink.

30 citations

Proceedings ArticleDOI
24 Oct 2008
TL;DR: The proposed channel estimation technique is shown to have significant gains in performance compared to other well known channel estimation techniques such as the maximum-likelihood (ML) and the inverse fast Fourier transform (IFFT) channel estimation methods.
Abstract: The performance of the uplink physical channel of the 3GPP LTE system is considered in this paper. Assuming a single user spatial division multiple access transmission scheme, where users' signals are transmitted over different subcarriers, a low complexity channel estimation technique is proposed for the physical uplink shared channel (PUSCH). The proposed channel estimation technique is shown to have significant gains in performance compared to other well known channel estimation techniques such as the maximum-likelihood (ML) and the inverse fast Fourier transform (IFFT) channel estimation methods [5]. Simulation results for different channel models and modulation and coding schemes (MCS) using incremental redundancy (IR) based hybrid automatic repeat request (HARQ) operation are also shown. Finally, a robust detection scheme is proposed for the physical uplink control channel (PUCCH) and simulation results are summarized.

10 citations


"LTE-advanced: next-generation wirel..." refers methods in this paper

  • ...The DFT precoding operation is performed to reduce the cubic metric (CM) of the signal, leading to higher maximum transmit power [2]....

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Trending Questions (1)
What is the difference between LTE and FIOS Internet?

LTE-Advanced (also known as LTE Release 10) significantly enhances the existing LTE Release 8 and supports much higher peak rates, higher throughput and coverage, and lower latencies, resulting in a better user experience.