LTE Advanced

About: LTE Advanced is a research topic. Over the lifetime, 4055 publications have been published within this topic receiving 74262 citations. The topic is also known as: Long-Term Evolution Advanced & LTE-A.

Energy efficient resource allocation in LTE-A

Abstract: We study the resource allocation problem in LTE-A downlink transmissions. Rather than maximizing the capacity, we consider energy metrics at the BS (base station), with certain rate guarantee for each MS (mobile station). Specifically, two energy related problems are investigated. By enabling a tradeoff between the number of PRBs (physical resource blocks) and the consumed power for each MS transmission, the first problem is to minimize the total power at the BS with constant MS rate guarantee. Based on the PRB scheduling, the second problem is to change the power allocation, such that energy efficiency can be maximized by minimizing an EPG (energy-per-goodbit) metric. We propose heuristic algorithms to circumvent the optimization models. Numerical results show that significant power decrease and energy efficiency increase can be achieved by properly trading off between PRBs and power consumptions.

When 5G Meets Deep Learning: A Systematic Review

Abstract: This last decade, the amount of data exchanged on the Internet increased by over a staggering factor of 100, and is expected to exceed well over the 500 exabytes by 2020. This phenomenon is mainly due to the evolution of high-speed broadband Internet and, more specifically, the popularization and wide spread use of smartphones and associated accessible data plans. Although 4G with its long-term evolution (LTE) technology is seen as a mature technology, there is continual improvement to its radio technology and architecture such as in the scope of the LTE Advanced standard, a major enhancement of LTE. However, for the long run, the next generation of telecommunication (5G) is considered and is gaining considerable momentum from both industry and researchers. In addition, with the deployment of the Internet of Things (IoT) applications, smart cities, vehicular networks, e-health systems, and Industry 4.0, a new plethora of 5G services has emerged with very diverging and technologically challenging design requirements. These include high mobile data volume per area, high number of devices connected per area, high data rates, longer battery life for low-power devices, and reduced end-to-end latency. Several technologies are being developed to meet these new requirements, and each of these technologies brings its own design issues and challenges. In this context, deep learning models could be seen as one of the main tools that can be used to process monitoring data and automate decisions. As these models are able to extract relevant features from raw data (images, texts, and other types of unstructured data), the integration between 5G and DL looks promising and one that requires exploring. As main contribution, this paper presents a systematic review about how DL is being applied to solve some 5G issues. Differently from the current literature, we examine data from the last decade and the works that address diverse 5G specific problems, such as physical medium state estimation, network traffic prediction, user device location prediction, self network management, among others. We also discuss the main research challenges when using deep learning models in 5G scenarios and identify several issues that deserve further consideration.

HiPAcc-LTE: an integrated high performance accelerator for 3GPP LTE stream ciphers

Abstract: Stream ciphers SNOW 3G and ZUC are the major players in the domain of next generation mobile security as both of them have been included in the security portfolio of 3GPP LTE-Advanced, the potential candidate for 4G mobile broadband communication standard. In this paper, we propose HiPAcc-LTE, a high performance integrated design that combines the two ciphers in hardware, based on their structural similarities. The integrated architecture reduces the area overhead significantly compared to two distinct cores, and also provides almost double throughput in terms of keystream generation. This is in comparison with the state-of-the-art implementations of the individual ciphers, both in the academic literature as well as in the commercial domain. We present detailed description of the design idea, optimization techniques and comparison results in this paper. Long term vision of this hardware integration approach for cryptographic primitives is to build a flexible core supporting multiple designs having similar algorithmic structures.

Impact of Relays on LTE-Advanced Performance

Abstract: This paper studies the performance and coverage improvements introduced by relay deployment in LTE-Advanced systems. Different relay deployment strategies are investigated, namely, amplify-and-forward (AF) repeaters and decode-and-forward (DF) relays (orthogonal and non-orthogonal modes). First, the expressions of peak throughput (i.e., assuming allocate all resources in a cell to one user) for different relay deployment strategies are derived. Next, the calculation of resource partition between e-Node B (eNB) and relay nodes for the repeater and relay scenarios are detailed. A capacity evaluation method for relay deployment is then proposed; this includes the analysis of user-perceived Quality of Service (QoS) based on cell traffic. In addition, we investigate a more advanced adaptive resource sharing strategy for more efficient resource utilization among relays in a cell. Finally, the performances of the different relay deployment strategies are compared using simulation results.

Performance upper bounds for coordinated beam selection in LTE-Advanced

Abstract: Coordinated Multipoint (CoMP) transmission techniques have been considered as tools to improve cell-edge and average data throughput for LTE-Advanced. First investigations of CoMP techniques in homogeneous hexagonal macro layouts have shown that interference coordination needs to involve dominant interferers to allow significant gain. Therefore, in the present paper the application of CoMP in a heterogeneous network is considered where a planned macro deployment coexists with randomly placed femtocells resulting in a scenario where dominant interference can potentially be mitigated more effectively. The impacts of a heterogeneous layout on the interference characteristics in the downlink are evaluated by simulation and an assessment of gains achieved through coordination is provided.