Narrowband Internet Of Things System Research Articles

5G NB-IoT System Integrated with High-Performance Fiber Sensor Inspired by Cirrus and Spider Structures.

Real-time telemedicine detection can solve the problem of the shortage of public medical resources caused by the coming aging society. However, the development of such an integrated monitoring system is hampered by the need for high-performance sensors and the strict-requirement of long-distance signal transmission and reproduction. Here, a bionic crack-spring fiber sensor (CSFS) inspired by spider leg and cirrus whiskers for stretchable and weavable electronics is reported. Trans-scale conductive percolation networks of multilayer graphene around the surface of outer spring-like Polyethylene terephthalate (PET) fibers and printing Ag enable a high sensitivity of 28475.6 and broad sensing range over 250%. The electromechanical changes in different stretching stages are simulated by Comsol to explain the response mechanism. The CSFS is incorporated into the fabric and realized the human-machine interactions (HMIs) for robot control. Furthermore, the 5G Narrowband Internet of Things (NB-IoT) system is developed for human healthcare data collection, transmission, and reproduction together with the integration of the CSFS, illustrating the huge potential of the approach in human-machine communication interfaces and intelligent telemedicine rehabilitation and diagnosis monitoring.

A Design for Increasing the Capacity Fourfold in NB-IoT Systems using A Modified Symbol Time Compression Approach

One of the most significant obstacles facing the Internet of Things (IoT) is how to offer support for communication to an expanding number of linked items. Narrow-band Internet of Things (NB-IoT), which is currently an aspect of fifth-generation (5G), is a new narrow-band wireless communication technology that has evolved in recent years to address this issue. To save power, NB-IoT currently exploits modulation schemes that are characterized by low order to deliver low data rate. However, as the number of applications dependent on data rate increases, NB-IoT needs to use data rate improvement technologies that do not consume additional power. This paper proposes a design for quadrupling the total number of linked items in the NB-IoT system using a symbol time compression methodology. A modified symbol time compression (MSTC) approach is specifically suggested, which could preserve 75% of the bandwidth (BW) by reducing the symbol time to a quarter (25%). This study suggests a design that uses the MSTC method four times in orthogonal frequency division multiplexing (4-MSTC-OFDM) to take advantage of the unused bandwidth and has the capability to deliver a quadruple quantity of information in comparison to the standard OFDM system. Simulations show that the suggested design (4-MSTC-OFDM) lowers the signal-to-noise ratio (SNR) by 3.9 dB (at BER = 10-6) and 4.4 dB (at BER = 10-4) compared to the OFDM system with 16-QAM (16-QAM-OFDM) when sending the same amount of data over the Rayleigh fading channel and additive white Gaussian noise channel (AWGN). Moreover, the results of simulations indicate that the proposed design possesses an identical BER as the conventional OFDM technique, implying that using the suggested method does not degrade the BER.

Design and FPGA-Based Hardware Implementation of NB-IoT Physical Uplink Shared Channel Transmitter and Physical Downlink Shared Channel Receiver

With the anticipated growth of the internet of things (IoT) market, many low-power wide-area (LPWA) technologies have been introduced to connect a wide range of IoT devices with varying performance requirements. The narrowband internet of things (NB-IoT) is a 3rd generation partnership project (3GPP) standardized LPWA technology that meets most IoT service requirements. In this paper, the design and implementation of the physical uplink transmitting chain as well as the physical downlink receiving chain of the NB-IoT user equipment (UE) are presented. Both chains’ main blocks are designed to follow the 3GPP NB-IoT LTE standard Release 14 (Rel-14). The whole design is experimentally implemented on the Virtex 7 (VC 709) Connectivity kit, and all performance metrics are reported. Moreover, an NB-IoT base station is implemented and integrated with the two prototyped UEs to set-up an NB-IoT system, which is employed to send data from one UE to another UE through the NB-IoT base station using two FPGAs (one to implement the sending UE and the other one to implement the receiving UE) and three universal software radio peripherals (USRPs) B200 (one to implement the RF front-end of the transmitting UE FPGA, one to implement the base station RF front-end, and one to implement the RF front-end of the receiving UE FPGA). Experimental results show that the implemented NB-IoT system is working successfully, as the two NB-IoT UEs communicate together successfully through the NB-IoT base station and exchange the data properly.

Interference Avoidance Resource Allocation for D2D-Enabled 5G Narrowband Internet of Things

In dense, interference-prone 5G narrowband Internet of Things (NB-IoT) networks, device-to-device (D2D) communication can reduce the network bottleneck. We propose an interference-avoidance resource allocation for D2D-enabled 5G NB-IoT systems that consider the less favorable cell edge narrowband user equipment (NUEs). To reduce interference power and boost data rate, we divided the optimization problem into three subproblems to lower the algorithm’s computational complexity. First, we leverage the channel gain factor to choose the probable reuse channel with better Quality of Service (QoS) control in an orthogonal deployment method with channel state information (CSI). Second, we used a bisection search approach to determine an optimal power control that maximizes the network sum rate, and third, we used the Hungarian algorithm to construct a maximum bipartite matching strategy to select the optimal pairing pattern between the sets of NUEs and the D2D pairs. According to numerical data, the proposed approach increases the 5G NB-IoT system’s performance in terms of D2D sum rate and overall network signal-to-interference plus noise ratio (SINR). The D2D pair’s maximum power constraint, as well as the D2D pair’s location, pico-base station (PBS) cell radius, number of potential reuse channels, and D2D pair cluster distance, all influence the D2D pair’s performance. The simulation results demonstrate the efficacy of our proposed scheme.

Performance evaluation of random access in narrow band Internet of Things

Low power wide area network (LPWAN) is one of the enabling technologies for Internet of Things (IoT). 3GPP has introduced a new standard called Narrow Band Internet of Things (NB-IoT) for LPWAN. This paper develops an analytical model to estimate the throughput of User Equipments (UEs) in NB-IoT system. We carry out Markov chain analysis of our model under steady state conditions by considering different Coverage Enhancement (CE) levels, number of preamble transmission attempts, and size of the back-off window as state variables. The Markov chain model is used to derive the transmission and the success probabilities of random access procedure for UEs in different CE levels. Further, we derive the throughput of the packets transmitted by the UEs in different CE levels. The analytical model is validated against simulation for a different set of combinations of parameters. We show that the throughput of NB-IoT critically depends on the allocation of the number of sub-carriers to different CE levels.

Complexity-Efficient Coherent Physical Cell Identity Detection Method for Cellular IoT Systems

Narrowband Internet of Things (NB-IoT) is one of the low-power wide-area network technologies that aim to support enormous connection, deep coverage, low power consumption, and low cost. Therefore, low cost of implementation and maintenance is one of the key challenges of NB-IoT terminals. This paper presents a low-complexity formulation for narrowband secondary synchronization signal (NSSS) detection in the NB-IoT system, supported by a coherent algorithm that requires a priori knowledge of the channel. By exploiting a symmetric conjugate feature of the NSSS sequence, a joint physical cell ID and radio frame number detection method with low complexity is proposed for coherent detection. The probability of erroneous detection of the presented NSSS detection method is computed, and the analytical model is verified by means of simulation. Numerical experiments will demonstrate that the proposed detection scheme remarkably reduces the computational complexity with almost the same detection ability compared to the existing detection scheme.

Persistent Periodic Uplink Scheduling Algorithm for Massive NB-IoT Devices.

Narrowband Internet of Things (NB-IoT) is one of the low-power wide-area network (LPWAN) technologies that aim to support enormous connections, featuring wide-area coverage, low power consumption, and low costs. NB-IoT could serve a massive number of IoT devices, but with very limited radio resources. Therefore, how to enable a massive number of IoT devices to transmit messages periodically, and with low latency, according to transmission requirements, has become the most crucial issue of NB-IoT. Moreover, IoT devices are designed to minimize power consumption so that the device battery can last for a long time. Similarly, the NB-IoT system must configure different power-saving mechanisms for different types of devices to prolong their battery lives. In this study, we propose a persistent periodic uplink scheduling algorithm (PPUSA) to assist a plethora of Internet of Things (IoT) devices in reporting their sensing data based on their sensing characteristics. PPUSA explicitly considers the power-saving mode and connection suspend/resume procedures to reduce the IoT device’s power consumption and processing overhead. PPUSA allocates uplink resource units to IoT devices systematically so that it can support the periodic–uplink transmission of a plethora of IoT devices while maintaining low transmission latency for bursty data. The simulation results show that PPUSA can support up to 600,000 IoT devices when the NB-IoT uplink utilization is 80%. In addition, it takes only one millisecond for the transmission of the bursty messages.

Optimum DCT type-I based transceiver model and effective channel estimation for uplink NB-IoT system

Single-tone and multi-tone transmissions in the narrowband Internet of Things (NB-IoT) uplink system can be accomplished by employing different orthogonal basis. In this paper, we develop an uplink NB-IoT baseband system model and derive the corresponding analytical signal model based on the discrete cosine transform type-I (DCT-I) domain. Basically, the circular convolution and channel matrix diagonalization issues for designing DCT-based systems are addressed without exploiting any redundancy (a prefix and a suffix sequences, and zero-padding (ZP)) into each transmitted data symbol blocks. In our proposed DCT-I based transceiver, we employ a standard cyclic prefix (CP) and apply discrete Fourier transform (DFT) and inverse DFT (IDFT) operations directly to make the channel matrix circulant and diagonal, resulting in the use of one-tap frequency-domain channel equalizer without incorporating extra front-end prefilter at the receiver. Furthermore, we propose novel least squares (LS) and linear minimum mean square error (LMMSE) channel estimators by considering the energy concentration and spectral compaction properties of DCT-I for the uplink NB-IoT system. The expressions for the DCT-I domain LS and LMMSE estimators are derived for channel frequency response estimation and mean square error computation. Finally, the viability of the proposed CP-DCT-I-NB-IoT uplink system, as well as the channel estimators, are tested compared with the standardized CP-DFT-NB-IoT and ZP-DCT type-2 even based single-carrier frequency-division multiple access (SC-FDMA) systems through rigorous computer simulations.

Layer based security in Narrow Band Internet of Things (NB-IoT)

In the recent years, the growth of technology and the resulting transformation is happening at a rapid pace. In this junction, IoT has provided a great platform and bridge between these technologies. A lot of research regarding the application of IoT Systems has been done in the recent years but one area that lacks research is security issues in Narrow Band Internet of Things (NB-IoT).It is noticed that security and Privacy in NB-IoT system is a challenging task for researchers and academia. Application of NB-IoT in Defense security opened a new way for the researchers but at the same time security threat can lead to drastic loss. Nowadays, MEMS-NB-IoT device (Bug)/ BOT are being used for carrying out any malicious security attack. This can be a serious area of concern in the case of defense security. These MEMS device are very dangerous and it can spoof data from any type of network. The size of this device is very small, it can travel to any location for monitoring the enemy movement, and it is very difficult to identify these types of bugs. These BOT device very sensitive at Perception and Network Layered. In this paper, we have provided detail analysis of IoT/NB-IoT Layered architecture. A novel proposal depicting security attack in a Smart home system with IoT and NB-IoT enabled devices is presented. The Secrecy Rate (SR), the Secrecy Outage Probability (SOP) is being calculated, and performance analysis of IoT system in the presence of Bugs for a smart home system is carried out. Simulations have been performed and the performance analysis done is based on Security non-outage probability vs security rate with real time analysis.

Connectivity Performance Evaluation for Grant-Free Narrowband IoT With Widely Linear Receivers

Future wireless cellular communication networks are expected to provide connectivity for massive machine-type communication (mMTC) devices. The main challenge of supporting mMTC traffic for a cellular network lies in the high density of these devices, which individually have relatively little data to transmit. This suggests the use of low overhead, grant-free access scheme for uplink data transmission, which, however, suffers from packet collisions when devices attempt to access the channel. In this article, we suggest the use of real-valued transmission together with widely linear (WL) reception for improving resource access and thus data throughput in the uplink of mMTC traffic scenarios. We show that not surprisingly, the WL scheme can virtually double the number of receive antennas at the base station (BS). We analyze the effect of this on the supported user density and data throughput for grant-free uplink transmission. As a specific example, we consider the narrowband Internet-of-Things (NB-IoT) cellular communication system, which already includes real-valued modulation modes. Our numerical results show that the supported user density and data throughput of grant-free NB-IoT systems can be significantly improved due to the use of WL receivers. For example, considering an NB-IoT system with 1% packet drop probability, we obtain a tenfold (for single-antenna BS) and a sixfold (for dual-antenna BS) increase in the supported user density by using WL receivers instead of their conventional linear counterparts.

Complexity-Effective Sequential Detection of Synchronization Signal for Cellular Narrowband IoT Communication Systems

Narrowband Internet of Things (NB-IoT) is one of the most promising low-power wide-area technologies to support low cost, massive connection, deep coverage, and low-power consumption. This article proposes a complexity-effective narrowband secondary synchronization signal (NSSS) detection scheme for the cellular NB-IoT communication system. By taking advantage of the NSSS sequence, the search space of NSSS hypotheses is reduced by decoupling the detection of complementary Walsh sequence and Zadoff-Chu sequence in a sequential manner. Such a detection strategy allows reduced-complexity NSSS detection in the NB-IoT system. Both numerical and simulation results are presented to verify the effectiveness of the proposed NSSS detection scheme. The simulation results show that the proposed NSSS detector achieves a considerable complexity reduction at the cost of some performance degradation, compared to the conventional NSSS detector.

Optimization of Large-scaled Random Access Congestion Control Oriented to Narrow Band Internet of Things

Narrow band internet of things (NB-IoT), as an important low-power wide-area coverage of 5G with independent intellectual property rights, has great potential in small data monitoring of urban power transmission and distribution. However, it is extremely easy to cause congestion and overloading of the system upon large-scaled terminal requests for random access, which will decrease network access performance and bring great challenges to promote NB-IoT in urban power Internet of Things. On this basis, a mathematical model of network load was constructed to estimate and predict load changes. Then, a dynamic adjustment functional model was set up according to dynamic adjustment of access parameter optimization based on loads. Based on above idea, a random access algorithm based on dynamic parameter adjustment in accordance to dynamic priority was developed. It increases the success rate of devices access to NB-IoT system, decreases access delay of devices, and relieves network congestion. According to simulation results, the proposed algorithm has higher access success rate, lower total delay. And it guarantees delay for important node users and more optimized network performances compared with traditional network access algorithms.

An Efficient NPRACH Receiver Design For NB-IoT Systems

Narrowband Internet of Things (NB-IoT) is a powerful technology for massive machine-type communications, which is imperative in the forthcoming 5G wireless communications. Unlike the long-time evolution (LTE) protocol, in the NB-IoT protocol specified by the third generation partnership project (3GPP), the narrowband physical random access channel (NPRACH) is newly introduced and its receiver performance is critical to the success of an NB-IoT system. In this article, an optimal activity detection scheme is first designed by using the Neyman–Pearson criterion. Then, a low-complexity iterative search algorithm is developed for the joint estimation of residual carrier frequency offset (RCFO) and timing advanced (TA), avoiding the effect of phase ambiguity. Finally, simulation results collaborate on the effectiveness and efficiency of the proposed receiver.

On the Latency-Energy Performance of NB-IoT Systems in Providing Wide-Area IoT Connectivity

Narrowband Internet-of-Things (NB-IoT) offers a significant link budget improvement in comparison with the legacy networks by introducing different coverage classes, allowing repeated transmissions, and tuning the repetition order based on the path-loss in communications. However, those repetitions necessarily increase energy consumption and latency in the whole NB-IoT system. The extent to which the whole system is affected depends on the scheduling of the uplink and downlink channels. We address this question, not treated previously, by developing a tractable model of NB-IoT connectivity, comprising message exchanges in random-access, control, and data channels. The model is then used to analyze the impact of channel scheduling and interaction of coverage classes on the performance of IoT devices through the derivation of the expected latency and battery lifetime. These results are subsequently employed in determining the optimized operation points, i.e., (i) scheduling of data and control channels for a given set of users and respective coverage classes, or (ii) determining the optimal set of coverage classes and served users per coverage class for a given scheduling strategy. Simulations results show the validity of the analysis and confirm that channel scheduling and coexistence of coverage classes significantly affect latency and battery lifetime performance of NB-IoT devices.

Mobile IoT Systems in the Urban Area

An important element of Internet of Things systems (IoT) is wireless data transmission. Narrowband Internet of Things (NB-IoT) and LTE Cat M1 (LTE-M) are the new standards for such transmission intended for LTE cellular networks. Cellular network operators has recently launched such transmission. The article presents the results of measurements of NB-IoT transmission parameters in this network, inside the building and in open urban areas. The main features of the NB-IoT system and measuring equipment are briefly discussed.

An Efficient Polar Coding Scheme for Uplink Data Transmission in Narrowband Internet of Things Systems

Narrowband Internet of Things (NB-IoT) is an emerging IoT cellular-based wireless technology that builds based on the existing LTE standard to extend its network coverage suited for Low Power Wide Area Network (LPWAN) connectivity. In the NB-IoT system, LTE turbo codes and Cyclic Redundancy Check (CRC) codes are adopted as the main channel coding technique for Narrowband Physical Uplink Shared Channel (NPUSCH). However, turbo codes require iterative decoding algorithm at the expense of high computation complexity of decoding hence is crucial to achieving the LPWAN requirement of NB-IoT systems. Polar codes are best suited in this regard due to its capacity approaching and complexity reduction in short block length code. In this paper, we proposed an efficient polar coding technique using the Belief Propagation (BP) decoding algorithm for uplink data transmission on the NPUSCH channel. Furthermore, the BP algorithm is incorporated with the CRC stoppage criterion to decrease the number of decoding iteration and reduce computational complexity. In this scheme, single-tone numerology of NPUSCH using 3.75 kHz and 15 kHz subcarrier spacing is adopted. Then, the encoded data is generated with different NPUSCH resources. The theoretical formulation and simulation demonstrate that the proposed scheme provides better error rate performance over the adopted LTE turbo codes and other polar decoding algorithms while reducing the computational complexity.

A Non-orthogonal Random Access Scheme Based on NB-IoT

Narrowband Internet of Things (NB-IoT) is a Quasi-5G technology that will provide coverage for massive number of low-power consumption applications. Hence, the potential massive random access (RA) users call for a new RA scheme. In this paper, based on the key ideas of non-orthogonal multiple access and successive interference cancellation, the NB-IoT non-orthogonal random access (NB-NORA) scheme has been proposed to provide a more effective access performance for NB-IoT system. Further, the RA preamble (MSG1) transmission collision probability and initial layer 3 message (MSG3) outage performances are analyzed based on stochastic geometry, which is compared with the traditional NB-IoT orthogonal random access (NB-ORA) scheme. Simulation results show that the maximum throughput of MSG1 within NB-NORA scheme is double that within NB-ORA scheme, and the successful RA probability of NB-NORA is increased by about 75%.

Anti-Quantum Fast Authentication and Data Transmission Scheme for Massive Devices in 5G NB-IoT System

The narrowband Internet of Things (NB-IoT) system has become an integral part of the future fifth generation (5G) network. Although the NB-IoT system has gradually been improved in the traditional LTE network currently, the NB-IoT system does not have an effective access authentication scheme in the future 5G network. According to the current 3rd Generation Partnership Project (3GPP) standard, NB-IoT devices still use the traditional access authentication method to perform mutual authentication with the network, which may bring a large amount of signaling and communication overhead. This problem will be magnified in a large-scale device environment in the future 5G network. In this article, a quantum resistance access authentication and data distribution scheme is proposed for large-scale NB-IoT devices. The scheme can simultaneously implement access authentication and data transmission of a group of NB-IoT devices based on the lattice-based homomorphic encryption technology. Our scheme not only greatly reduce the network burden but also achieve strong security, including privacy protection and anti-quantum attacks. The performance analysis results show that our scheme has the ideal efficiency.

NOMA Aided Narrowband IoT for Machine Type Communications With User Clustering

To support machine type communications (MTCs) in next generation mobile networks, Narrowband-Internet of Things (NB-IoT) has been released by the third generation partnership project (3GPP) as a promising solution to provide extended coverage and low energy consumption for low cost MTC devices. However, the existing orthogonal multiple access (OMA) scheme in NB-IoT cannot provide connectivity for a massive number of MTC devices. In parallel with the development of NB-IoT and non-OMA (NOMA), introduced for the fifth generation wireless networks, is deemed to significantly improve the network capacity by providing massive connectivity through sharing the same spectral resources. To leverage NOMA in the context of NB-IoT, we propose a power domain NOMA scheme with user clustering for an NB-IoT system. In particular, the MTC devices are assigned to different ranks within the NOMA clusters where they transmit over the same frequency resources. Then, we formulate an optimization problem to maximize the total throughput of the network by optimizing the resource allocation of MTC devices and NOMA clustering while satisfying the transmission power and quality of service requirements. We prove the NP-hardness of the proposed optimization problem. We further design an efficient heuristic algorithm to solve the proposed optimization problem by jointly optimizing NOMA clustering and resource allocation of MTC devices. Furthermore, we prove that the reduced optimization problem of power control is a convex optimization task. Simulation results are presented to demonstrate the efficiency of the proposed scheme.

Performance Analysis and Uplink Scheduling for QoS-Aware NB-IoT Networks in Mobile Computing

Low-power wide-area (LPWA) communication has gained increasing attention in recent years with the rapid growth of fifth generation evolution (5G), the Internet of Things (IoT), and mobile computing. Narrowband Internet of Things (NB-IoT) is one kind of LPWA technology based on cellular IoT, which supports massive connections, wide area coverage, ultra-low power consumption, and ultra-low cost. Research on NB-IoT communication is increasingly attractive. Network calculus theory facilitates the performance analysis and network optimization of the NB-IoT system. We aim to analyze and optimize the NB-IoT networks. In this paper, we construct a random access traffic model including the NB-IoT user equipment (UE) arrival process and eNB service process. Then, we utilize the stochastic network calculus (SNC) to analyze the network delay in NB-IoT traffic model. Random latency bounds in different arrival processes are derived. Simulations show that SNC can evaluate the system delay under different distributions effectively. For the condition that numerous UEs access simultaneously following the Beta distribution, we first propose an improved K-means algorithm to cluster the NB-IoT terminals. Then, we raise the scheduling strategy on the basis of priority. It consists of the priority generation algorithm IPGNTQ and the NB-IoT task scheduling algorithm SANTQ. The extensive experiment results verify that our proposed optimized strategy can alleviate the network congestion effectually. Moreover, we compare our proposed optimized scheme with four existing uplink traffic scheduling schemes, showing that ours outperforms all of them.