Commercial LTE Network Research Articles

FDD LTE MIMO CLOSED-LOOP VS OPEN-LOOP PERFORMANCE EVALUATION IN COMMERCIAL NETWORK

With a growing network traffic Mobile Network Operators (MNO) looking for ways to increase network capacity and improve customer experience. One of the ways is to find the best parameters from the set defined by 3GPP. In the study, closed-loop MIMO was compared to open-loop MIMO on the LTE FDD network. Network performance was evaluated in 3 different scenarios: slow and fast-moving UE under different SINR levels and large scale on 2T2R and 4T4R cells. The result shows gains of using closed-loop and it is recommended to use it commercial LTE networks.

Field Electromagnetic Strength Variability Measurement and Adaptive Prognostic Approximation with Weighed Least Regression Approach in the Ultra-high Radio Frequency Band

Propagated electromagnetic signal over the cellular radio communication channels and interfaces are usually highly stochastic and complex with unequal noise variation pattern. This is due to multipath nature of the propagation channels and diverse radio propagation mechanisms that impact the signal strength at the receiver en-route the transmitter, and verse versa. This also makes measurement, predictive modeling and estimation based analysis of such signal very challenging and complex as well. One important and popular parametric modelling and estimation technique in mathematics and engineering science, especially for signal processing applications is the least square regression (LSR). The dominance use and popularity of the LSR approach may be attributed to its simplified supporting theory, relatively fast application procedure and ubiquitous application packages. However, LSR is known to be very sensitive to outliers and unusual stochastic signal data. In this work, we propose the application of weighted least square regression method for enhanced propagation practical field strength estimation modelling over cellular radio communication networks interface. The signal data was collected from a commercial LTE networks service provider. Also, we provide statistical computational analyses to compare the resultant estimation outcome of the weighted least square and the standard least approach. From the result, it is found that the WLSR approach is reliably better the most popular standard least square method. The significance and academic of value of this paper is that our proposed and implemented WLSR method can used as replacement of the standard LSR approach for robust mobile signal processing of future communication system networks.

Statistical Learning Based Congestion Control for Real-Time Video Communication

With the increasing demands on interactive video applications, how to adapt video bit rate to avoid network congestion has become critical, since congestion results in self-inflicted delay and packet loss which deteriorate the quality of real-time video service. The existing congestion control is hard to simultaneously achieve low latency, high throughput, good adaptability and fair bandwidth allocation, mainly because of the hardwired control strategy and egocentric convergence objective. To address these issues, we propose an end-to-end statistical learning based congestion control, named Iris. By exploring the underlying principles of self-inflicted delay, we reveal that congestion delay is determined by sending rate, receiving rate and network status, which inspires us to control video bit rate using a statistical-learning congestion control model. The key idea of Iris is to force all flows to converge to the same queue load, and adjust the bit rate by the model. All flows keep a small and fixed number of packets queuing in the network, thus the fair bandwidth allocation and low latency are both achieved. Besides, the adjustment step size of sending rate is updated by online learning, to better adapt to dynamically changing networks. We carried out extensive experiments to evaluate the performance of Iris, with the implementations of transport layer (UDP) and application layer (QUIC) respectively. The testing environment includes emulated network, real-world Internet and commercial LTE networks. Compared against TCP flavors and state-of-the-art protocols, Iris is able to achieve high bandwidth utilization, low latency and good fairness concurrently. Especially over QUIC, Iris is able to increase the video bitrate up to 25%, and PSNR up to 1dB.

상용 LTE망 기반의 무인항공기 관제용 무선통신시스템 구현

상용 LTE망 기반의 무인항공기 관제용 무선통신시스템 구현

Passive Method for Estimating Available Throughput for Autonomous Off-Peak Data Transfer

Large demands for mobile traffic subject base stations to frequent short-term and sharp peak loads. Recent analysis of data traffic on commercial mobile networks reported that the traffic peaks can be reduced by an average of 40% without compromising the quality of experience provided to the end user, if a peak load can be shifted for at most 20 s. To reduce peak traffic, we previously proposed a method for off-peak data transfer, with which user equipment (UE) autonomously delays receiving data, and a peak load on a base station can be shifted. In terms of off-peak transfer of data, a significant problem is determining how each UE estimates available throughput. In this paper we propose a method of passively estimating available throughput of each UE. We evaluated the effectiveness of the proposed method through experiments on experimental and commercial LTE networks. The results indicate that our method obtains more than a 0.7 correlation between actual available throughput and estimated throughput.

Achieving Phase Coherency and Gain Stability in Active Antenna Arrays for Sub-6 GHz FDD and TDD FD-MIMO: Challenges and Solutions

Full-dimension MIMO (FD-MIMO) using planar active antenna systems (AAS) is considered a critical technology for fifth-generation (5G) cellular systems to improve network capacity. An AAS is typically subject to hardware impairments that negatively impact network capacity. Hence, this article focuses on impairments that cause phase and magnitude errors between radio frequency (RF) chains and shows why they are particularly difficult to avoid in practical AAS. Although previous investigations show these impairments to degrade performance, they are not useful in deriving measurable impairment margins for practical FD-MIMO deployments. Knowing impairment limits are critical for system designers to make hardware design tradeoffs such as AAS configuration, component selection, implementation complexity, and cost. Moreover, it also helps set conformance limits for critical lab verification. Therefore, the paper first investigates the impact of the impairments and derives their practical limits for FD-MIMO by explicitly considering the cumulative effects of the channel model, inter-cell interference, link adaptation, and channel aging due to feedback delays. It is shown that a lower number of digitized RF chains can be a better choice under lower impairments. Next, the sources of impairments are investigated by using measurements carried out in the lab and the field during live operation in a commercial LTE network. Phase drift from local oscillators (LO) and internal temperature variations are identified as two significant sources. The tradeoffs and shortcomings of some of the existing solutions in massive MIMO literature are discussed. Finally, in order to address the shortcomings, a novel and practical coherent LO distribution architecture and array calibration mechanism are proposed. This solution is shown to be applicable to both TDD and FDD FD-MIMO. Measurement results are provided to prove the high degree of coherency and stability achieved on a unique array architecture called high definition active antenna system (HDAAS).

An Ensemble Learning Scheme for Indoor-Outdoor Classification Based on KPIs of LTE Network

Wireless Big Data has aroused extensive attention, as mass mobile devices have been developed and deployed for the upcoming 5G era. The context information of these devices is of importance for personalized services in a smart environment. Nevertheless, the constant change of scenes challenges to the network operator. In this paper, we propose an ensemble learning scheme for indoor-outdoor classification for a typical urban area, based on the cellular data captured in a commercial LTE network. The variables are extracted by network key performance indicators (KPIs) and radio propagation knowledge. Based on these main variables, the decision trees grow and split by the Gini index of sampled features. Then, all decision trees are assembled as weak learners to build the ensemble scheme, thus improving the discrimination ability. The self-validation results show the ensemble model achieves extreme accurate (with an out-of-bag error lower than 1%) classification for indoor and outdoor environments. Moreover, the prominent variables are selected based on the variable importance of in the initial training. The reconfigured model based on fewer variables and less weak learners also gains the highest accuracy and relative short compute time, compared with other classical machine learning methods.

Resource usage of LTE networks for machine-to-Machine group communications: Modeling and analysis

Machine nodes (MNs) such as monitoring devices and utility devices can be handled with machine-to-machine (M2M) group communications in commercial 3GPP LTE networks. However, the current LTE networks are designed for human-oriented communication, i.e., human-to-human (H2H) communication, as a main service. Hence, the M2M group communications may utilize a limited amount of radio resource in the LTE networks so that they do not degrade the quality-of-services (QoS) of the H2H communications. Under the resource limitation, the MNs in the M2M communication group may suffer resource contentions when they simultaneously send uplink data packets to a base station (BS). In this paper, we first mathematically model the overall procedure of the M2M group communications. Then, we also optimize the system parameters for the M2M group communications to maximize resource utilization of the LTE networks and minimize the packet transmission delay, while satisfying the resource constraint.

LinkForecast: Cellular Link Bandwidth Prediction in LTE Networks

Accurate cellular link bandwidth prediction can benefit upper-layer protocols significantly. In this paper, we investigate how to predict cellular link bandwidth in LTE networks. We first conduct an extensive measurement study in two major commercial LTE networks in the US, and identify five types of lower-layer information that are correlated with cellular link bandwidth. We then develop a machine learning based prediction framework, LinkForecast , that identifies the most important features (from both upper and lower layers) and uses these features to predict link bandwidth in real time. Our evaluation shows that LinkForecast is lightweight and the prediction is highly accurate: At the time granularity of one second, the average prediction error is in the range of 3.9 to 17.0 percent for all the scenarios we explore. We further investigate the prediction performance when using lower-layer features obtained through standard APIs provided by the operating system, instead of specialized tools. Our results show that, while the features thus obtained have lower fidelity compared to those from specialized tools, they lead to similar prediction accuracy, indicating that our approach can be easily used over commercial off-the-shelf mobile devices.

A Network-Aware Encoding Rate Control Algorithm for Real-Time Up-Streaming Video Services

Real-time personal broadcasting and video social network services on which a user’s mobile device serves as the content provider have received a considerable amount of attention. This letter presents an up-streaming video service in which a mobile device records and encodes video streams on the spot and transmits them to a receiver through an uplink interface. Unlike existing streaming services, the receiver in this service receives and plays video streams in real time without buffering them. Considering the requirements of real-time characteristics and frequent network state changes, this letter proposes a new encoding rate control algorithm for an up-streaming video service based on the estimated network condition. The sender estimates the network status based on the average inter-arrival time of video frames periodically measured and transmitted by the receiver. The network-aware encoding rate control algorithm was implemented on a mobile device running the Android OS. The effectiveness of the algorithm was proved through experiments performed on a commercial LTE network and in an ordinary office WiFi environment.

On the Split-TCP Performance over Real 4G LTE and 3G Wireless Networks

The global mobile traffic is growing exponentially, and currently more than 90 percent of the internet traffic depends on TCP for reliable transmission. However, it is well known that TCP performs quite poorly over unreliable wireless networks, while its dynamic TCP flow control is sensitive to congestion events and tends to underutilize the available network capacity. Despite these known limitations, the industry believes that significant network performance enhancement can be achieved through TCP optimization, and in particular through solutions centered on Split-TCP. In this article we share a sample of TCP throughput performance measurements after implementing Split-TCP on commercial 4G LTE and 3G networks. Experimental results show that Split-TCP provides average TCP throughput gains on the order of 60 percent over a 4G LTE network and on the order of 5 percent over a 3G network. Furthermore, TCP throughput gains superior to 200 percent were measured for individual TCP connections over the 4G LTE network. We expect such throughput gains to be even greater when advanced radio technologies, such as 5G, are deployed. For these reasons, Split-TCP has the potential to be widely deployed in both current and next generation networks.

A Priority-Based Bandwidth Management Method in Public Safety Networks

After Sewol ferry disaster occurred in April 2014, Korean government began investing to deploy LTE-based public safety network until the year of 2017. In order to reduce the operating and capital costs, resource sharing scheme among public safety network and commercial LTE networks is considered as one of the viable approaches. This thesis proposes a method of allocating bandwidth of public safety network based on various priorities required for disaster scenarios and stages in a resource sharing environment. In order to obtain the highest efficiency, we formulate the bandwidth allocation problem as a Fractional Knapsack Problem. Greedy algorithm was applied to solve the problem. For performance evaluation, we created several disaster scenarios and set suitable parameters for each scenario based on a disaster manual. The proposed method is compared with two typical methods, which are Class-based bandwidth allocation and Uniform bandwidth allocation. The results showed that the better performance in terms of the sum of the values and the amount of lost bytes.

LTE enhancements for public safety and security communications to support group multimedia communications

Currently public safety and security communication systems depend on reliable and secure PMR networks that are mainly devoted to provide voice services. However, the evolutionary trend for professional mobile radio (PMR) networks is toward the provision of new value-added multimedia services such as video streaming, in order to improve situational awareness and enhance life-saving operations. The challenge here is to exploit the future commercial broadband networks to deliver voice and multimedia services satisfying PMR service requirements. In particular, a viable solution now seems to be the adaption of the new Long Term Evolution technology to provide IP-based broadband services with the security and reliability typical of PMR networks. This article outlines different alternatives to achieve this goal and, in particular, proposes a proper solution for providing multimedia services with PMR standards over commercial LTE networks.

Tutorial on LTE/LTE-A Cellular Network Dimensioning Using Iterative Statistical Analysis

LTE is the fastest growing cellular technology and is expected to increase its footprint in the coming years, as well as progress toward LTE-A. The race among operators to deliver the expected quality of experience to their users is tight and demands sophisticated skills in network planning. Radio network dimensioning (RND) is an essential step in the process of network planning and has been used as a fast, but indicative, approximation of radio site count. RND is a prerequisite to the lengthy process of thorough planning. Moreover, results from RND are used by players in the industry to estimate preplanning costs of deploying and running a network; thus, RND is, as well, a key tool in cellular business modelling. In this work, we present a tutorial on radio network dimensioning, focused on LTE/LTE-A, using an iterative approach to find a balanced design that mediates among the three design requirements: coverage, capacity, and quality. This approach uses a statistical link budget analysis methodology, which jointly accounts for small and large scale fading in the channel, as well as loading due to traffic demand, in the interference calculation. A complete RND manual is thus presented, which is of key importance to operators deploying or upgrading LTE/LTE-A networks for two reasons. It is purely analytical, hence it enables fast results, a prime factor in the race undertaken. Moreover, it captures essential variables affecting network dimensions and manages conflicting targets to ensure user quality of experience, another major criterion in the competition. The described approach is compared to the traditional RND using a commercial LTE network planning tool. The outcome further dismisses the traditional RND for LTE due to unjustified increase in number of radio sites and related cost, and motivates further research in developing more effective and novel RND procedures.

LTE-R의 도시철도 터널 환경 적용성 분석

Unlike commercial LTE network, LTE-R railway network is arranged along a railroad track and the base stations of the network (RUs) are also installed on the waysides. For urban railway systems that are composed of underground tunnels, the leakage coaxial cables are widely used due to the radio propagation characteristics in tunnels. In theory, the tunnel sections are interpreted as the waveguide with blank spaces and for this reason, the tunnel sections are expected to be better than open ground sections in terms of the radio propagation characteristics. In this paper, we analyze the radio propagation characteristics based on this theory by replacing the leakage coaxial cables in the network with Yagi antennas. The test has been carried out in the 2.2km tunnel in the Daebul test track of KORAIL with 2.6GHz LTE-R Network. The LTE-R applicability in urban railways has been tested through the analysis on the radio propagation characteristics with the unmanned train operation system in Daebul tunnel.

Interference Analysis of LTE Network and RF Optimization

The reasons interfering LTE network are analyzed. Combining with the actual data of existing commercial LTE network, RF optimization scheme of LTE network to suppress the interference is promoted. According to the data released by road test, the proposed RF optimization scheme can improve the network coverage and network performance, and can play a reference role to other similar cases.

Networks and devices for the 5G era

Mobile services based on 4G LTE services are steadily expanding across global markets, providing subscribers with the type of responsive Internet browsing experience that previously was only possible on wired broadband connections. With more than 200 commercial LTE networks in operation as of August 2013 [1], LTE subscriptions are expected to exceed 1.3 billion by the end of 2018 [2]. LTE's rapid uptake, based on exponential growth in network data traffic, has opened the industry's eyes to an important reality: the mobile industry must deliver an economically sustainable capacity and performance growth strategy; one that offers increasingly better coverage and a superior user experience at lower cost than existing wireless systems, including LTE. This strategy will be based on a combination of network topology innovations and new terminal capabilities. Simple network economics also require that the industry's strategy enable new services, new applications, and ultimately new opportunities to monetize the user experience. To address these pressing requirements, many expert prognosticators are turning their attention to future mobile broadband technologies and standards (i.e., 5G) as well as evolutions of the 3GPP's existing LTE standard and IEEE 802.11 standards.

First LTE-Advanced Commercial Network Deployed [Mobile Radio

The Russian operator YOTA Networks and Huawei Technologies Company, Inc. announced the launch of what they claim is the world's first long-term-evolution-advanced (LTE-A) commercial network in Moscow. Huawei modernized its end-toend single radio-access network (RAN) LTE/Evolved Packet Core solution for LTE-A [in terms of 3rd Generation Partnership Project (3GPP) rev10]. The solution features carrier aggregation technology, which provides downlink peak rates of up to 300 Mb/s, depending on the capacity of the radio channel. Huawei also announced that it has successfully conducted what it claims is the world's first LTE-A uplink coordinated multipoint (CoMP) trial on several commercial LTE networks in Europe and Asia. The results showed that uplink CoMP can effectively double data rates at cell edges for a single user, improving network performance in terms of coverage, spectrum efficiency, and throughput.

First Commercial LTE Network [Mobile Radio

TeliaSonera has launched the first fourth-generation (4G) services commercially to customers in Stockholm, Sweden, and Oslo, Norway. TeliaSonera's current 4G networks cover the central city areas of Stockholm and Oslo. The Stockholm 4G city network is supplied by Ericsson, and the Oslo 4G city network is supplied by Huawei. The modems at launch come from Samsung. The 4G network roll-out will continue to Sweden's 25 largest municipalities and recreation areas and to Norway's four largest municipalities.