Future 5th generation (5G) networks are expected to enable three key services -enhanced mobile broadband (eMBB), massive machine type communications (mMTC) and ultra-reliable and low latency communications (URLLC). As per the 3rd generation partnership project (3GPP) URLLC requirements, it is expected that the reliability of one transmission of a 32 byte packet will be at least 99.999% and the latency will be at most 1 ms. This unprecedented level of reliability and latency will yield various new applications such as smart grids, industrial automation and intelligent transport systems. In this survey we present potential future URLLC applications, and summarize the corresponding reliability and latency requirements. We provide a comprehensive discussion on physical (PHY) and medium access control (MAC) layer techniques that enable URLLC, addressing both licensed and unlicensed bands. The paper evaluates the relevant PHY and MAC techniques for their ability to improve the reliability and reduce the latency. We identify that enabling long-term evolution (LTE) to coexist in the unlicensed spectrum is also a potential enabler of URLLC in the unlicensed band, and provide numerical evaluations. Lastly, the paper discusses the potential future research directions and challenges in achieving the URLLC requirements.

In recent years, the Internet of Things (IoT) has been studied in the context of the Metaverse to provide users with immersive cyber-virtual experiences in mixed-reality environments. This survey introduces six typical IoT applications in the Metaverse, including collaborative healthcare, education, smart city, entertainment, real estate, and socialization. In the IoT-inspired Metaverse, we also comprehensively survey four pillar technologies that enable augmented reality (AR) and virtual reality (VR), namely, responsible artificial intelligence (AI), high-speed data communications, cost-effective mobile edge computing (MEC), and digital twins. According to the physical-world demands, we outline the current industrial efforts and seven key requirements for building the IoT-inspired Metaverse: immersion, variety, economy, civility, interactivity, authenticity, and independence. In addition, this survey describes the open issues in the IoT-inspired Metaverse, which need to be addressed to eventually achieve the convergence of physical and cyber worlds.

In this paper, a novel three-dimensional (3-D) indoor positioning scheme is proposed for millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems. Its operation is based upon a hybrid received signal strength and angle of arrival (RSS-AoA) positioning scheme, which employs only a single access point equipped with a large-scale uniform cylindrical array. To reduce the high computational complexity imposed by the large number of antennas used in mmWave massive MIMO (M³-MIMO) systems, we firstly propose a novel channel compression method. By proper quantization and selection of the received mmWave signals, which exhibit quasioptical and sparse multipath characteristics, the channel compression method reduces the dimension of the received signal space while maintaining the accuracy of the position estimation. Then, we propose a beamspace transformation approach to transform signal vectors in the element space to the beamspace, and thus the computational complexity of the angle estimation is significantly reduced. Finally, a novel hybrid RSS-AoA positioning scheme is designed for the computations of the 3-D coordinates of the target mobile terminal. Simulation results have shown that the proposed indoor positioning scheme is capable of achieving high accuracy as well as significantly lower computational complexity as compared to other previously known indoor positioning techniques.

Non-orthogonal multiple access (NOMA) is one promising technology, which provides high system capacity, low latency, and massive connectivity, to address several challenges in the fifth-generation wireless systems. In this paper, we first reveal that the NOMA techniques have evolved from single-carrier NOMA (SC-NOMA) into multi-carrier NOMA (MC-NOMA). Then, we comprehensively investigated on the basic principles, enabling schemes and evaluations of the two most promising MC-NOMA techniques, namely sparse code multiple access (SCMA) and pattern division multiple access (PDMA). Meanwhile, we consider that the research challenges of SCMA and PDMA might be addressed with the stimulation of the advanced and matured progress in SC-NOMA. Finally, yet importantly, we investigate the emerging applications, and point out the future research trends of the MC-NOMA techniques, which could be straightforwardly inspired by the various deployments of SC-NOMA.

Massive connectivity and low latency are two important challenges for the Internet of Things (IoT) to achieve the quality of service provisions required by the numerous devices it is designed to service. Motivated by these challenges, in this paper we introduce a new millimeter-wave nonorthogonal multiple access (mmWave-NOMA) transmission scheme designed for cellular machine-to-machine (M2M) communication systems for IoT applications. It consists of one base station (BS) and numerous multiple machine type communication (MTC) devices operating in a cellular communication environment. We consider its down-link performance and assume that multiple MTC devices share the same communication resources offered by the proposed mmWave-NOMA transmission scheme, which can support massive connectivity. For this system, a novel MTC pairing scheme is introduced the design of which is based upon the distance between the BS and the MTC devices aiming at reducing the system overall overhead for massive connectivity and latency. In particular, we consider three different MTC device pairing schemes, namely: 1) random near and the random far MTC devices; 2) nearest near and the nearest far MTC devices (NNNF); and 3) nearest near and the farthest far MTC device. For all three pairing schemes, their performance is analyzed by deriving closed-form expressions of the outage probability and the sum rate. Furthermore, performance comparison studies of the three MTC device pairing schemes have been carried out. The validity of the analytical approach has been verified by means of extensive computer simulations. The obtained performance evaluation results have demonstrated that the proposed cellular M2M communication system employing the mmWave-NOMA transmission scheme improves outage probability as compared to equivalent systems using mmWave with orthogonal multiple access schemes.

The near-field effect of short-range multiple-input multiple-output (MIMO) systems imposes many challenges on direction-of-arrival (DoA) estimation. Most conventional scenarios assume that the far-field planar wavefronts hold. In this paper, we investigate the DoA estimation problem in short-range MIMO communications, where the effect of near-field spherical wave is non-negligible. By converting it into a regression task, a novel DoA estimation framework based on complex-valued deep learning (CVDL) is proposed for the near-field region in shortrange MIMO communication systems. Under the assumption of a spherical wave model, the array steering vector is determined by both the distance and the direction. However, solving this regression task containing a massive number of variables is challenging, since datasets need to capture numerous complicated feature representations. To overcome this, a virtual covariance matrix (VCM) based on received signals is constructed, and thus such features extracted from the VCM can deal with the complicated coupling relationship between the direction and the distance. Although the emergence of wireless big data driven by future communication networks promotes deep learning-based wireless signal processing, the learning algorithms of complexvalued signals are still ongoing. This paper proposes a onedimensional (1-D) residual network that can directly tackle complex-valued features due to the inherent 1-D structure of signal subspace vectors. In addition, we put forth a cropped VCM based policy which can be applied to different antenna sizes. The proposed method is able to fully exploit the complex-valued information. Our simulation results demonstrate the superiority of the proposed CVDL approach over the baseline schemes in terms of the accuracy of DoA estimation.