Massive multiple-input multiple-output (MIMO) system is promising in providing unprecedentedly high data rate. To achieve its full potential, the transceiver needs complete channel state information (CSI) to perform transmit/receive precoding/combining. This requirement, however, is challenging in the practical systems due to the unavoidable processing and feedback delays, which oftentimes degrades the performance to a great extent, especially in the high mobility scenarios. In this paper, we develop a deep learning based channel prediction framework that proactively predicts the downlink channel state information based on the past observed channel sequence. In its core, the model adopts a 3-D convolutional neural network (CNN) based architecture to efficiently learn the temporal, spatial and frequency correlations of downlink channel samples, based on which accurate channel prediction can be performed. Simulation results highlight the potential of the developed learning model in extracting information and predicting future downlink channels directly from the observed past channel sequence, which significantly improves the performance compared to the sample-and-hold approach, and mitigates the impact of the dynamic communication environment.

Accurate Channel State Information (CSI) is critical for maximizing the throughput of massive Multi-Input Multi-Output (mMIMO) systems. Due to the environment dynamics and user mobility, CSI aging is a major challenge to achieving the large throughput of mMIMO promised by theory. CSI prediction can be used to overcome this without increasing the signaling overhead. Motivated by the anticipated native support for Artificial Intelligence (AI) in the fifth generation and beyond cellular standards, we propose deep learning CSI prediction solutions based on 3-Dimensional (3D) Complex Convolutional Neural Networks (CCNN). These solutions provide improved capabilities for capturing temporal and spatial correlations, enhancing CSI prediction performance. In particular, they utilize the angle delay decomposition of previously observed CSI to predict the future one. In one architecture, the network, dubbed CSI Prediction Network (CSI-PNet), uses small kernels with circular padding to efficiently capture the correlation between propagation paths in the angle domain. This architecture can be further improved by the use of an attention-like model to vary the weights and enhance prediction performance adaptively. We also propose methods to enhance robustness to noise and time and frequency offsets. We tested these solutions using 3GPP-compatible simulations and field measurements in a commercial network. Our solutions demonstrate stable performance and significantly outperform several benchmarks, especially at low and medium speeds. They strike a balance between performance and architecture complexity, indicating suitability for actual implementation.

As the need for limitless connectivity surges, non-terrestrial networks (NTN) will play a central role in fifth generation (5G) and beyond communications. The 3rd Gener-ation Partnership Project (3GPP) defines NTN as networks, or segments of networks, using an airborne or space-borne vehicle as a relay node or base station. An NTN-enhanced cellular network supplements a conventional terrestrial cellular network. This article provides an overview of NTN-enhanced cellular networks with a particular focus on satellite-mobile direct communications. First, we review satellite system classifications such as Geostation-ary Orbit (GEO), Medium Earth Orbit (MEO), and Low Earth Orbit (LEO), spectrum usage, and key challenges of satellite communications. We then summarize recent 3GPP activities in NTN. In addition, we describe our recent proof-of-concept system involving a satellite channel emulator and modification of the 5G New Radio (NR) protocol stack to handle the challenge of long round-trip time - demonstrating the feasibility of NTN and the adoption of NTN-enhanced cellular networks in 5G and beyond communications. Finally, we highlight the main open issues and future research challenges of NTN-enhanced cellular networks.

As the pace of global 5G network deployments accelerates, the telecommunications industry strives to move from a conventional vertical stack, closed, hardware-based ecosystem to an open, interoperable, modular, cloud-based ecosystem that leverages software-based implementations of various network entities – including core network functions and base stations. Such an open ecosystem could facilitate the implementation of AI techniques and could be a critical advancement in realizing the vision of “zero-touch” wireless networks that support end-to-end automation– stretching from the core network to end-user devices. In this paper, we provide an overview of ongoing discussions along these lines in the context of the O-RAN Alliance along with a comprehensive discussion on various challenges. We then briefly present our vision of the evolution of intelligent networks beyond current 4G/5G networks.

In multiple-input multiple-output (MIMO) systems, the high-resolution channel information (CSI) is required at the base station (BS) to ensure optimal performance, especially in the case of multi-user MIMO (MU-MIMO) systems. In the absence of channel reciprocity in frequency division duplex (FDD) systems, the user needs to send the CSI to the BS. Often the large overhead associated with this CSI feedback in FDD systems becomes the bottleneck in improving the system performance. In this paper, we propose an AI-based CSI feedback based on an auto-encoder architecture that encodes the CSI at UE into a low-dimensional latent space and decodes it back at the BS by effectively reducing the feedback overhead while minimizing the loss during recovery. Our simulation results show that the AI-based proposed architecture outperforms the state-of-the-art high-resolution linear combination codebook using the DFT basis adopted in the 5G New Radio (NR) system.

As the pace of global 5G network deployments accelerates, now is the moment for the cellular industry to realize 6G cellular communication. In this article, modular massive multiple-in-put multiple-output (mmMIMO) is presented as one candidate technology for 6G to improve the spectral efficiency in low-frequency bands. The 5G New Radio pushed the boundary of the cellular system's operating frequency to high-frequen-cy bands, and this trend will continue in the 6G era. However, the technical advances in 5G for low-frequency bands fall short, although low-frequency bands are crucial in serving a large number of users in a wide coverage area. Although it would be ideal if massive MIMO could be utilized in low-frequency bands, it is less practical due to a large antenna form factor size. mmMIMO is a technology to distribute a large active antenna array with smaller standardized antenna modules, just like Lego-type building blocks. Through this, the benefits of massive MIMO can be achieved in low-frequency bands (e.g., sub-1 GHz), unconstrained by spatial limitations. In this article, the concept of mmMIMO, its applicability, and needed research efforts to standardize the technology for 6G are discussed. In addition, through the demonstration of a proof-of-concept system, it is shown that the technology can be within reach at the time of 6G commercialization around 2030. Lastly, the performance gain of mmMIMO is evidenced by system-level simulation.

Higher data rates are required to support exponential growth in wireless traffic, motivating an expansion of the transmission bandwidth for sixth generation (6G) communications. The available bandwidth in the terahertz (THz) band significantly exceeds the available bandwidth in the mmWave band that has been adopted in fifth generation (SG) systems; thus, the THz band is envisioned as a pillar for 6G systems that can support data rates on the order of terabits per second (Tb/s). However, wireless communications in the THz band poses several new challenges. One of these challenges involves the practical constraint of employing a limited oversampling factor to process wideband THz signals, even while leveraging state-of-the-art analog/digital converter techniques. This limited oversampling factor - which can lead to an increased sampling timing offset - degrades the demodulation performance when it is employed in conjunction with a conventional symbol-spaced equalizer. Thus, we employ a fractionally spaced equalizer (FSE) in a THz communication system to overcome the impact of the increased sampling timing offset for a practical system that utilizes a limited sampling rate. Analysis and simulations demonstrate that the FSE can perfectly compensate the timing offset by optimally combining the available samples. Also, an approximation to the noise covariance matrix is proposed to reduce the computational complexity of the frequency-domain FSE.

Techniques for channel state information (CSI) reporting are discussed. One example apparatus at a user equipment can derive, for one or more subframes of a license assisted access (LAA) secondary cell (SCell), one or more channel measurements based on reference signals (e.g., cell-specific reference signals (CRS) or CSI reference signals (CSI-RS)), in those subframes; generate CSI that comprises a channel quality indicator (CQI) based on an average of the one or more channel measurements from multiple subframes comprising a first subframe and a later second subframe, wherein each orthogonal frequency division multiplexing (OFDM) symbol of a second slot of the first subframe is occupied, wherein each of a first three OFDM symbols of the second subframe are occupied, and wherein each OFDM symbol between the first subframe and the second subframe is occupied; and generate a CSI report that indicates the set of CSI parameters.

Current trends in the evolution of mobile communication systems address the data throughput demand by expanding to higher frequency bands as the usable spectrum in lower frequency bands is almost depleted. As the Third Generation Partnership Project (3GPP) specified the support of mmWave band operations for 5G New Radio (NR), it is expected that the next generation mobile communication system, namely 6G, will consider even higher terahertz (THz) spectrum with wider bandwidth to continue supporting exponential growth of data rates. However, the question remains how to deal with various technical challenges stemming from harsh THz radio propagation characteristics as well as the feasibility of radio frequency (RF) components, which we try to answer in this work. To this end, it is our goal to demonstrate the promise of THz spectrum for the next generation communication systems.

Current trends in spectrum regulation show that more and more unlicensed and shared spectrum bands are poised to be opened up for mobile communication. However, the question remains how to best utilize this spectrum and build efficient networks, and if the time has come for newer approaches to be considered for the next generation system. In this work, we propose a coordinated shared spectrum framework that can be considered for next generation cellular standardization. In designing the framework, we aim to improve on the current unlicensed access schemes toward increasing spectral efficiency in highly-dense networks. To this end, we demonstrate that with the proposed framework both throughput and access delay can be significantly improved over the state-of-the-art LAA system. We also show that large statistical multiplexing gains are possible through dynamic sharing instead of static, hard splitting of shared spectrum, as in the current CBRS system.

In this work, we study the benefit of partial relay cooperation. We consider a two-node system consisting of one source and one relay node transmitting information to a common destination. The source and the relay have external traffic and in addition, the relay is equipped with a flow controller to regulate the incoming traffic from the source node. The cooperation is performed at the network level. A collision channel with erasures is considered. We provide an exact characterization of the stability region of the system and we also prove that the system with partial cooperation is always better or at least equal to the system without the flow controller.

Techniques for communication of resource allocation indication for a shortened physical uplink control channel (sPUCCH) or an enhanced physical uplink control channel (ePUCCH) in MulteFire systems. A network device (e.g., an evolved NodeB, user equipment, or other network device) can enable sPUCCH and ePUCCH carrying HARQ-ACK feedback. Resource allocations for sPUCCH and ePUCCH can be configured by one or more of: a higher layer signaling, an acknowledgement resource indicator (ARI), a control channel element (CCE) index, or a combination thereof. Various triggering operations for the sPUCCH and the ePUCCH are also considered.

The 3GPP is in the process of developing the next generation radio access technology, named New Radio (NR), which will be proposed as a candidate technology for IMT-2020. This article outlines the wide bandwidth operation of NR, among other new features being considered, based on the up-to-date discussions and decisions made in 3GPP standardization meetings. The much wider channel bandwidth of NR, compared to LTE, enables more efficient use of resources than the existing carrier aggregation framework with lower control overhead. The support of multiple sub-carrier spacing options allows NR to operate in a wide range of carrier frequency from sub-6 GHz band to mmWave band with appropriate handling of multi-path delay spread and phase noise depending on the carrier frequency. In addition, the introduction of the new bandwidth part concept allows flexible and dynamic configuration of UE's operating bandwidth, which will make NR an energy-efficient solution despite the support of wide bandwidth. Other NR wideband operation related issues, such as the support of UEs with limited RF capability and frequency domain resource indexing, are also explained in this article.

Technology for an eNodeB operable to perform physical random access channel (PRACH) transmissions in an unlicensed frequency band, in the context of 3GPP LTE eLAA, i.e. MuLTEfire, is disclosed. The eNodeB can identify a PRACH configuration being utilized by a MuLTEfire system that operates in an unlicensed spectrum. The PRACH configuration can define a number of continuous physical resource blocks (PRBs) in the unlicensed spectrum to be used for PRACH transmissions. The eNodeB can decode a PRACH transmission received from a user equipment (UE) in accordance with the PRACH configuration. The PRACH transmission can include a PRACH preamble that is transmitted using the number of continuous PRBs defined in the PRACH configuration. The eNB configures the performance of Clear Channel Assessment, CCA, before preamble transmission by the UE. In case the uplink transmission frame is configured with short PUCCH, sPUCCH, only a short CCA is configured. Otherwise, for example when the frame allows ePUCCH to be configured, CCA is followed by a self-deferring period.

Technology for a user equipment (UE) operable to perform a physical random access channel (PRACH) procedure with an eNodeB is disclosed. The UE can select a PRACH preamble for transmission to an eNodeB during the PRACH procedure. The UE can perform a listen-before-talk (LBT) to determine whether an unlicensed channel is available. The UE can detect a LBT failure at the UE. The LBT failure can indicate that the unlicensed channel is unavailable to transmit the PRACH preamble during a PRACH opportunity. The UE can select new PRACH resources for a subsequent PRACH opportunity. The UE can be configured to perform a PRACH preamble transmission during the subsequent PRACH opportunity when the UE is not subject to the LBT failure.

Described is an apparatus of an Evolved Node-B (eNB) operable to communicate with a User Equipment (UE) on a wireless network. The apparatus may comprise a first circuitry and a second circuitry. The first circuitry may be operable to initiate a single- interval Listen-Before-Talk (LBT) procedure within an Orthogonal Frequency-Division Multiplexing (OFDM) symbol of a subframe after a first time period and before a second time period, the single interval LBT procedure having a first duration. The second circuitry may be operable to allocate a second duration within the OFDM symbol for a reservation signal. The second duration may span a symbol time of the OFDM symbol minus the first time period, the first duration, and the second time period.

Methods for low latency PRACH design in unlicensed spectrum are generally described herein. An exemplary apparatus of User Equipment (UE) includes a memory; and processing circuitry, the processing circuitry being used to perform a listen-before-talk (LBT) procedure on one or more channels of an unlicensed spectrum. The processing circuitry is further used to, in response to a clear channel assessment (CCA), encode a first message for a first transmission associated with a low latency random access (RA) procedure on the unlicensed spectrum. The first message includes a physical random-access channel (PRACH) preamble and a message part. The message part includes at least one of a cell radio network temporary identifier (C-RNTI), buffer status report (BSR) information, capability of the UE,and/or an identity of the UE. The processing circuitry is further used to, in response to receipt of an uplink (UL) grant based on the first step of low-latency RA procedure, encode UL data for transmission.