Millimeter wave (mmWave) communications have recently attracted large research interest, since the huge available bandwidth can potentially lead to the rates of multiple gigabit per second per user Though mmWave can be readily used in stationary scenarios, such as indoor hotspots or backhaul, it is challenging to use mmWave in mobile networks, where the transmitting/receiving nodes may be moving, channels may have a complicated structure, and the coordination among multiple nodes is difficult To fully exploit the high potential rates of mmWave in mobile networks, lots of technical problems must be addressed This paper presents a comprehensive survey of mmWave communications for future mobile networks (5G and beyond) We first summarize the recent channel measurement campaigns and modeling results Then, we discuss in detail recent progresses in multiple input multiple output transceiver design for mmWave communications After that, we provide an overview of the solution for multiple access and backhauling, followed by the analysis of coverage and connectivity Finally, the progresses in the standardization and deployment of mmWave for mobile networks are discussed

Millimeter Wave Communications for Future Mobile Networks

The increasing wireless data traffic demands have driven the need to explore suitable spectrum regions for meeting the projected requirements. In the light of this, millimeter wave (mmWave) communication has received considerable attention from the research community. Typically, in fifth generation (5G) wireless networks, mmWave massive multiple-input multiple-output (MIMO) communications is realized by the hybrid transceivers which combine high dimensional analog phase shifters and power amplifiers with lower-dimensional digital signal processing units. This hybrid beamforming design reduces the cost and power consumption which is aligned with an energy-efficient design vision of 5G. In this paper, we track the progress in hybrid beamforming for massive MIMO communications in the context of system models of the hybrid transceivers’ structures, the digital and analog beamforming matrices with the possible antenna configuration scenarios and the hybrid beamforming in heterogeneous wireless networks. We extend the scope of the discussion by including resource management issues in hybrid beamforming. We explore the suitability of hybrid beamforming methods, both, existing and proposed till first quarter of 2017, and identify the exciting future challenges in this domain.

https://biblio.ugent.be/publication/8585223/file/8585225.pdf

A Survey on Hybrid Beamforming Techniques in 5G: Architecture and System Model Perspectives

In future Internet-of-Things networks, sensors or even access points can be mounted on ground/aerial vehicles for smart-city surveillance or environment monitoring. For such high-mobility sensing , it is impractical to collect data from a large population of sensors using any traditional orthogonal multi-access scheme due to the excessive latency. To tackle the challenge, a technique called over-the-air computation (AirComp) was recently developed to enable a data-fusion center to receive a desired function of sensing data from concurrent sensor transmissions, by exploiting the superposition property of a multi-access channel. This paper aims at further developing multiple-input-multiple output (MIMO) AirComp for enabling high-mobility multimodal sensing . Specifically, we design MIMO-AirComp equalization and channel feedback techniques for spatially multiplexing multifunction computation. Given the objective of minimizing the computation error, a close-to-optimal equalizer is derived in closed-form using differential geometry. The solution can be computed as the weighted centroid of points on a Grassmann manifold, where each point represents the subspace spanned by the channel matrix of a sensor. As a by-product, the problem of MIMO-AirComp equalization is proved to have the same form as the classic problem of multicast beamforming, establishing the AirComp-multicasting duality . Its significance lies in making the said Grassmannian-centroid solution transferable to the latter problem which otherwise is solved using the computation-intensive semidefinite relaxation method. Last, building on the AirComp architecture, an efficient channel-feedback technique is designed for direct acquisition of the equalizer at the access point from simultaneous feedback by all sensors. This overcomes the difficulty of provisioning orthogonal feedback channels for many sensors.

MIMO Over-the-Air Computation for High-Mobility Multimodal Sensing

Driven by the explosive data traffic and new quality of service requirement of mobile users, the communication industry has been experiencing a new evolution by means of network infrastructure densification. With the increase of the density as well as the variety of access points (APs), the network benefits from proximal transmissions and increased spatial reuse of system resources, thus introducing a new paradigm named ultra-dense networks (UDNs). Since the limited available resources are shared by ubiquitous APs in UDNs, the demand for efficient resource allocation schemes becomes even more compelling. However, the large scale of UDNs impedes the exploration of effective resource allocation approaches particularly on the computational complexity and significance overhead or feedback. In this paper, we provide a survey-style introduction to resource allocation approaches in UDNs. Specifically, we first present some common scenarios of UDNs with the relevant special issues. Second, we provide a taxonomy to classify the resource allocation methods in the existing literatures. Then, to alleviate the main difficulties of UDNs, some prevailing and feasible solutions are elaborated. Next, we present some emerging technologies thriving UDNs with special RA features discussed. Additionally, the challenges and open research directions are outlined in this field.

Resource Allocation for Ultra-Dense Networks: A Survey, Some Research Issues and Challenges

Massive MIMO is one of the promising techniques to improve spectral efficiency and network performance for reaching its targeted multi-gigabit throughput in 5G systems. For 5G New Radio (NR) systems, one of the key differences compared to 4G systems is the utilization of high frequency millimeter wave (mmWave) bands in addition to sub-6GHz bands. To keep the complexity and implementation cost low, hybrid analog-digital beam-forming with large-scale antenna array has become a common design approach to address the issue of higher propagation loss as well as to improve spectral efficiency in mmWave communication in 5G NR. The 5G NR standard is designed to adapt to different beam-forming architecture and deployment scenarios. This paper provides the overview on beam management procedure according to the current 5G standardization progress. We discuss some major challenges of millimeter-wave communications encountered in the current 5G NR standard and present some expected enhancements considered for the future beyond-5G standard.

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Beam Management in Millimeter-Wave Communications for 5G and Beyond

Instead of successive interference cancellation (SIC) for uplink non-orthogonal multiple access systems with fixed decoding order based on the statistical channel state information (CSI), we focus on decoding with the dynamic order according to the instantaneous CSI. After modeling the channel fluctuation of all the users with different transmit powers and different path losses, a dynamic SIC receiver is proposed based on the instantaneous received power of different users. The outage probability of the proposed system is theoretically analyzed and the closed-form expressions for a three-user system are derived. Simulations are performed to validate the accuracy of the theoretical results.

Theoretical Analysis of the Dynamic Decode Ordering SIC Receiver for Uplink NOMA Systems

Millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) seamlessly integrates two wireless technologies, mmWave communications and massive MIMO , which provides spectrums with tens of GHz of total bandwidth and supports aggressive space division multiple access using large-scale arrays. Though it is a promising solution for next-generation systems, the realization of mmWave massive MIMO faces several practical challenges. In particular, implementing massive MIMO in the digital domain requires hundreds to thousands of radio frequency chains and analog-to-digital converters matching the number of antennas. Furthermore, designing these components to operate at the mmWave frequencies is challenging and costly. These motivated the recent development of the hybrid-beamforming architecture, where MIMO signal processing is divided for separate implementation in the analog and digital domains, called the analog and digital beamforming , respectively. Analog beamforming using a phase array introduces uni-modulus constraints on the beamforming coefficients. They render the conventional MIMO techniques unsuitable and call for new designs. In this paper, we present a systematic design framework for hybrid beamforming for multi-cell multiuser massive MIMO systems over mmWave channels characterized by sparse propagation paths. The framework relies on the decomposition of analog beamforming vectors and path observation vectors into Kronecker products of factors being uni-modulus vectors. Exploiting properties of Kronecker mixed products, different factors of the analog beamformer are designed for either nulling interference paths or coherently combining data paths. Furthermore, a channel estimation scheme is designed for enabling the proposed hybrid beamforming. The scheme estimates the angles-of-arrival (AoA) of data and interference paths by analog beam scanning and data-path gains by analog beam steering. The performance of the channel estimation scheme is analyzed. In particular, the AoA spectrum resulting from beam scanning, which displays the magnitude distribution of paths over the AoA range, is derived in closed form. It is shown that the inter-cell interference level diminishes inversely with the array size, the square root of pilot sequence length, and the spatial separation between paths, suggesting different ways of tackling pilot contamination.

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Hybrid Beamforming via the Kronecker Decomposition for the Millimeter-Wave Massive MIMO Systems

Contrary to the most existing works about the full-duplex (FD) relaying with perfect channel state information (CSI), this paper studies the outage performance of the two-way FD decode-and-forward relay network under the joint effects of the residual self-interference and imperfect CSI. We first derive the exact closed-form expressions of the system outage probability, based on which we obtain the outage probability under the perfect self-interference cancellation to investigate the impacts of the imperfect CSI on the system performance. In addition, to gain more insights about the imperfect CSI, we analyze the optimal power allocation scheme and an optimal relay node placement strategy, which minimize the system outage probability. The results reveal that the imperfect CSI will only affect the optimal power allocation, and the optimal relay node placement is related to the power ratio between the user nodes. Finally, analytical evaluations are performed to verify the theoretical results, and Monte Carlo simulations guarantee the correctness of the analytical evaluations.

Outage Performance of the Full-Duplex Two-Way DF Relay System Under Imperfect CSI

In wireless networks, the performance is degraded by the intensity of the interference received from concurrent transmissions. Considering a stochastic cache-enabled network where some users have caching ability to store the most popular packets, we propose a novel interference management scheme to eliminate the interference by exploiting the content diversity. First, cache-enabled users can exploit cached packets as side information to cancel the interference. Second, considering that different access points may transmit the same contents to different users simultaneously, they should be regarded as useful signals rather than interference. The performance improvement with these two content diversity schemes is theoretically analyzed in this paper. The probabilities for the interference cancellation case and the signal enhancement case are derived, respectively, followed by the investigation of the signal to interference plus noise ratio improvement with our proposed content diversity schemes. Based on this, the effective content capacity of the system is analyzed. In addition to the simulations to validate the accuracy of the theoretical analysis, the impacts of caching ability and the proposed interference management schemes on the effective content capacity are investigated.

Interference Management in Cache-Enabled Stochastic Networks: A Content Diversity Approach

In this paper, we develop an orthogonal-frequency-division-multiplexing (OFDM)-based over-the-air (OTA) aggregation solution for wireless federated learning (FL). In particular, the local gradients in massive IoT devices are modulated by an analog waveform and are then transmitted using the same wireless resources. To this end, achieving perfect waveform superposition is the key challenge, which is difficult due to the existence of frame timing offset (TO) and carrier frequency offset (CFO). In order to address these issues, we propose a two-stage waveform pre-equalization technique with a customized multiple access protocol that can estimate and then mitigate the TO and CFO for the OTA aggregation. Based on the proposed solution, we develop a hardware transceiver and application software to train a real-world FL task, which learns a deep neural network to predict the received signal strength with global positioning system information. Experiments verify that the proposed OTA aggregation solution can achieve comparable performance to offline learning procedures with high prediction accuracy.

Xiaofan Li

Papers

Theoretical Analysis of the Dynamic Decode Ordering SIC Receiver for Uplink NOMA Systems

Hybrid Beamforming via the Kronecker Decomposition for the Millimeter-Wave Massive MIMO Systems

Outage Performance of the Full-Duplex Two-Way DF Relay System Under Imperfect CSI

Interference Management in Cache-Enabled Stochastic Networks: A Content Diversity Approach

Over-the-Air Aggregation for Federated Learning: Waveform Superposition and Prototype Validation