Legacy Long Term Evolution Research Articles

Narrowband IoT Signal Identification in LTE Networks Using Convolutional Neural Networks

Narrowband Internet of Things (NB-IoT) is an emerging standard serving massive wireless communications devices. It is implemented based on the legacy long-term evolution (LTE) technology and thus shares many system configurations with it. In fact, NB-IoT is deployed on some of the spectrum allocated to LTE. This sometimes introduces interference to the frequency bands with LTE transmission. Signal identification has been found as a critical and effective method for spectrum awareness and the improvement of resource allocation performance thus mitigating potential interference. While not been studied in previous work, this article fills the hole in identifying NB-IoT transmissions in different communications scenarios. In particular, we develop a convolutional neural network (CNN)-based signal identification method to distinguish NB-IoT signals from other cellular signals. The performance of the signal identification method is tested with different CNN training setups. Our experiments demonstrate that the proposed model can successfully identify the existence of NB-IoT signal with 98.13% accuracy in the Rayleigh fading channel where the signal-to-noise ratio (SNR) = 10 dB. Our results also show that the proposed signal identification method is able to provide promising identification accuracy under various and unknown SNR environments in both additive white Gaussian noise (AWGN) and Rayleigh fading channels.

A Sparsity Adaptive Algorithm to Recover NB-IoT Signal From Legacy LTE Interference

As a forerunner in 5G technologies, Narrowband Internet of Things (NB-IoT) will be inevitably coexisting with the legacy Long-Term Evolution (LTE) system. Thus, it is imperative for NB-IoT to mitigate LTE interference. By virtue of the strong temporal correlation of the NB-IoT signal, this letter develops a sparsity adaptive algorithm to recover the NB-IoT signal from legacy LTE interference, by combining K-means clustering and sparsity adaptive matching pursuit (SAMP). In particular, the support of the NB-IoT signal is first estimated coarsely by K-means clustering and SAMP algorithm without sparsity limitation. Then, the estimated support is refined by a repeat mechanism. Simulation results demonstrate the effectiveness of the developed algorithm in terms of recovery probability and bit error rate, compared with competing algorithms.

Unitary Matrix Method for PAPR Reduction of IDFT-VFDM Signals

To enable the frequency reuse between the new radio (NR) and the long-term evolution (LTE) systems, inverse discrete Fourier transform-based Vandermonde-subspace frequency division multiplexing (IDFT-VFDM) has been proposed to exploit the guard intervals of the conventional orthogonal frequency division multiplexing (OFDM) system. One important issue of the IDFT-VFDM system is the high peak-to-average power ratio (PAPR), which distorts the transmitted signal and causes severe performance degradation. Compared to OFDM, the method to reduce the PAPR in IDFT-VFDM requires unique design to guarantee zero interference to the legacy LTE system. To deal with this problem, a unitary matrix based method is proposed to design the precoder at the NR users to reduce the PAPR, which can also guarantee the minimum residual interference to the LTE system. Simulation results are demonstrated to verify the effectiveness of the proposed scheme.

IDFT-VFDM for Supplementary Uplink and LTE-NR Co-Existence

During the first phase of the deployment of new radio (NR) networks, base station (BS) and user equipment (UE) are expected to operate alongside the pre-existing long-term evolution (LTE) networks. This paper proposes a solution to be adopted by NR UE to perform an uplink transmission towards NR BS over the same time and frequency resources as the legacy LTE system, which would extend the uplink coverage when operating at the supplementary uplink band. In order to guarantee the absence of interference towards LTE BS, we design a new waveform termed as inverse discrete Fourier transform-based Vandermonde-subspace frequency division multiplexing (IDFT-VFDM) with the following important features. On one hand, an NR UE communicating with an NR BS through IDFT-VFDM would not generate any interference at the legacy LTE BS, regardless of the number of antennas present at both ends of the interference channel. On the other hand, an IDFT-VFDM signal can always be designed to occupy the same signal bandwidth as a legacy single-carrier frequency division multiple access signal for LTE uplink transmission. Numerical results demonstrate the merit of IDFT-VFDM and confirm its potential as a candidate solution to achieve LTE-NR co-existence in multi-antenna multi-user scenarios.

Investigations of Component Carrier Selection Algorithms in Long Term Evolution-Advanced

<p>Given that the demand for real-time multimedia contents that require significantly high data rate are getting of high popularity, a new mobile cellular technology known as Long term Evolution-Advanced (LTE-A) was standardized. The LTE-A is envisaged to support high peak data rate by aggregating more than one Component Carriers (CCs) of the same or different frequency bandwidths. Since the inter-band non-contiguous carrier aggregation is likely to be used due to the current frequency allocation, this paper provides a performance study of a number of CC selection algorithms for use in the inter-band non-contiguous downlink LTE-A. It should be noted that CC selection is of paramount importance in the LTE-A operating in backward compatible mode as the LTE-A contains a mixture of the legacy Long Term Evolution (LTE) users that support packets (re)transmission on a single CC and the LTE-A users that utilize more than one CCs for packets (re)transmission. Simulation results demonstrated the efficacy of the Channel-Throughput Aware (CTA) algorithm for maximizing the system capacity without compromising the required Quality of Service of real-time video users.</p>

A Novel Design of Downlink Control Information Encoding and Decoding Based on Polar Codes

In legacy long term evolution (LTE) networks, multiple transmission modes are defined to cater to diverse wireless environment and improve the spectrum utilization. However, constrained by user equipment (UE) processing capability on blind detection of downlink control information (DCI), two transmission modes are allowed to be configured to UE simultaneously. In recent 5G standardization, the polar codes have supplanted the tail biting convolution codes (TBCC), becoming the channel coding scheme for downlink control information (DCI). Motivated by its successive decoding property, a novel design of DCI encoding and decoding is proposed in this paper. The proposed scheme could support dynamic configuration of transmission modes with decreasing the complexity of blind detection. Evaluation results from link level simulations show that the performance loss compared to conventional encoding/decoding scheme is generally negligible and the proposed scheme can comply with the false alarm rate (FAR) target of 5G standardization.

Autonomous Self-Backhauled LTE Mesh Network With QoS Guarantee

Public safety communication systems are currently evolving due to emergence of long term evolution (LTE) as a mature solution to replace the legacy ones while providing new services. However, LTE is initially designed for commercial cellular network and needs to be furthermore evolved to tackle the substantial requirements of public safety use cases. For instance, opportunistic deployments require modifications to enable the autonomous operation and meshing of moving base stations while satisfying heterogeneous frequency band availability. In this article, we present a novel radio access network infrastructure architecture that enables multi-hop LTE mesh networking for nomadic and autonomous base stations via in-band self-backhauling. Furthermore, we investigate the coordination and orchestration functionality within the proposed architecture and propose a hierarchical resource scheduling algorithm in order to efficiently meet quality of service (QoS) requirements for real-time traffic while maximizing the throughput for elastic flows. To demonstrate the feasibility and reliability of our proposed architecture, we implement the corresponding self-backhauling air-interface based on OpenAirInterface platform and compare it with the legacy LTE air-interface. Finally, we evaluate the efficiency and adaptability of our proposed resource scheduling algorithm in various network topology and heterogeneous traffic flows with QoS requirements.

Scalable group-based machine-to-machine communications in LTE-advanced networks

The legacy long term evolution (LTE) networks suffer from scalability problems when a massive number of Internet of Things devices enter the network simultaneously. In this paper, we investigate the root causes of the overload problems due to a massive number of machine devices when accessing to the LTE network, and evaluate current standardized solutions of 3GPP in terms of overload aspects. As a result, we derive the limitations of 3GPP standardized solutions, and then suggest a novel group-based communication method and a set of required functions for the group-based communication. The simulation results show that our proposed group-based communication dramatically decreases the signaling load when compared to the legacy LTE and other 3GPP solutions.

Benchmarking Practical RRM Algorithms for D2D Communications in LTE Advanced

Device-to-device (D2D) communication integrated into cellular networks is an advanced tool to take advantage of the proximity of devices and allow for reusing cellular resources and thereby to increase the user bitrates and the system capacity. However, the introduction of D2D in legacy long term evolution (LTE) cellular spectrum requires to revisit and modify the existing radio resource management and power control (PC) techniques in order to fully realize the potential of the proximity and reuse gains and to limit the interference to the cellular layer. In this paper, we examine the performance of the legacy LTE PC tool box and benchmark it against an utility optimal iterative scheme. We find that the open loop PC scheme of LTE performs well for cellular users both in terms of the used transmit power levels and the achieved signal-to-interference-and-noise-ratio distribution. However, the performance of the D2D users as well as the overall system throughput can be boosted by the utility optimal scheme, by taking better advantage of both the proximity and the reuse gains. Therefore, in this paper we propose a hybrid PC scheme, in which cellular users employ the legacy LTE open loop PC, while D2D users exploits the utility optimizing distributed PC scheme. We also recognize that the hybrid scheme is not only nearly optimal, and can balance between spectral and energy efficiency, but it also allows for a distributed implementation at the D2D users, while preserving the LTE PC scheme for the cellular users.

System Selection Algorithm for Heterogenous Radio Access Networks

of new radio technologies in the mobile world has been steadily gaining momentum as an alternative to meet the ever increasing demands of customers. This has especially been motivated by the existence of applications that make available to ordinary users a host of services that require higher spectral efficiency and data rates. LTE (Long Term Evolution) and LTE Advanced (LTE-A) with an enhanced air interface and optimized packet data architecture, an all IP network, is envisioned to provide enhanced data rates, reduced latency and cost efficient operations. The deployment of LTE concurrently with the existing legacy cellular systems, such as UMTS in the same cell sites, has proven to enhance the network resources available to the operators. Such deployment, however, is accompanied with many challenges such as mobility and load balancing. The diversity and availability of services which can be supported by several radio access networks, such as legacy 3G and LTE, make the management of radio access selection rather complex. In this paper, we propose a multi-criterion cell selection algorithm for multi radio environment (3G and LTE) based on service request, user profile and user equipment capabilities.