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

We develop a broadband channel estimation algorithm for millimeter wave (mmWave) multiple input multiple output (MIMO) systems with few-bit analog-to-digital converters (ADCs). Our methodology exploits the joint sparsity of the mmWave MIMO channel in the angle and delay domains. We formulate the estimation problem as a noisy quantized compressed-sensing problem and solve it using efficient approximate message passing (AMP) algorithms. In particular, we model the angle-delay coefficients using a Bernoulli–Gaussian-mixture distribution with unknown parameters and use the expectation-maximization forms of the generalized AMP and vector AMP algorithms to simultaneously learn the distributional parameters and compute approximately minimum mean-squared error (MSE) estimates of the channel coefficients. We design a training sequence that allows fast, fast Fourier transform based implementation of these algorithms while minimizing peak-to-average power ratio at the transmitter, making our methods scale efficiently to large numbers of antenna elements and delays. We present the results of a detailed simulation study that compares our algorithms to several benchmarks. Our study investigates the effect of SNR, training length, training type, ADC resolution, and runtime on channel estimation MSE, mutual information, and achievable rate. It shows that, in a mmWave MIMO system, the methods we propose to exploit joint angle-delay sparsity allow 1-bit ADCs to perform comparably to infinite-bit ADCs at low SNR, and 4-bit ADCs to perform comparably to infinite-bit ADCs at medium SNR.

Channel Estimation in Broadband Millimeter Wave MIMO Systems With Few-Bit ADCs

In-band full-duplex (IBFD) technology can enable unique system capabilities and network architectures by allowing devices to transmit and receive on the same frequency at the same time. While previously considered impossible, this ability can now be used to optimize resource sharing within the crowded frequency spectrum for various communication systems, including 5G new radio. The potential of these IBFD systems can only be realized if each device incorporates a sufficient number of self-interference cancellation techniques to ensure that its receivers do not saturate. This tutorial survey offers the most comprehensive collection to date of these techniques and discusses how all of them can be implemented within the different domains of a typical transceiver. In addition, the results of a novel IBFD system study are presented for more than 50 demonstrated communication systems with more than 80 different measurement scenarios. The various system parameters are then combined into a new figure of merit, which can be used to propel future research and accelerate the inclusion of IBFD technology within an upcoming wireless standard.

In-Band Full-Duplex Technology: Techniques and Systems Survey

Hybrid analog/digital architectures and receivers with low-resolution analog-to-digital converters (ADCs) are two low power solutions for wireless systems with large antenna arrays, such as millimeter wave and massive multiple-input multiple-output systems. Most prior work represents two extreme cases in which either a small number of radio frequency (RF) chains with full-resolution ADCs, or low-resolution ADC with a number of RF chains equal to the number of antennas is assumed. In this paper, a generalized hybrid architecture with a small number of RF chains and a finite number of ADC bits is proposed. For this architecture, achievable rates with channel inversion and singular value decomposition-based transmission methods are derived. Results show that the achievable rate is comparable to that obtained by full-precision ADC receivers at low and medium SNRs. A trade-off between the achievable rate and power consumption for the different numbers of bits and RF chains is devised. This enables us to draw some conclusions on the number of ADC bits needed to maximize the system energy efficiency. Numerical simulations show that coarse ADC quantization is optimal under various system configurations. This means that hybrid combining with coarse quantization achieves better energy-rate trade-off compared with both hybrid combining with full-resolutions ADCs and 1-bit ADC combining.

Hybrid Architectures With Few-Bit ADC Receivers: Achievable Rates and Energy-Rate Tradeoffs

5G will have to cope with a high degree of heterogeneity in terms of services and requirements. Among these latter, the flexible and efficient use of non-contiguous unused spectrum for different network deployment scenarios is considered a key challenge for 5G systems. To maximize spectrum efficiency, the 5G air interface technology will also need to be flexible and capable of mapping various services to the best suitable combinations of frequency and radio resources. In this work, we propose a comparison of several 5G waveform candidates (OFDM, UFMC, FBMC and GFDM) under a common framework. We assess spectral efficiency, power spectral density, peak-to-average power ratio and robustness to asynchronous multi-user uplink transmission. Moreover, we evaluate and compare the complexity of the different waveforms. In addition to the complexity analysis, in this work, we also demonstrate the suitability of FBMC for specific 5G use cases via two experimental implementations. The benefits of these new waveforms for the foreseen 5G use cases are clearly highlighted on representative criteria and experiments.

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The 5G candidate waveform race: a comparison of complexity and performance

For 5G, it will be important to leverage the available millimeter wave spectrum. To achieve an approximately omnidirectional coverage with a similar effective antenna aperture compared to state-of-the-art cellular systems, an antenna array is required at both the mobile and base station. Due to the large bandwidth and inefficient amplifiers available in CMOS for mmWave, the analog front end of the receiver with a large number of antennas becomes especially power hungry. Two main solutions exist to reduce the power consumption: hybrid beam forming and digital beam forming with low resolution Analog to digital converters (ADCs). In this paper, we compare the spectral and energy efficiency of both systems under practical system constraints. We consider the effects of channel estimation, transmitter impairments, and multiple simultaneous users for a wideband multipath model. Our power consumption model considers components reported in the literature at 60 GHz. In contrast to many other works, we also consider the correlation of the quantization error, and generalize the modeling of it to nonuniform quantizers and different quantizers at each antenna. The result shows that as the signal-to-noise ratio (SNR) gets larger the ADC resolution achieving the optimal energy efficiency gets also larger. The energy efficiency peaks for 5-b resolution at high SNR, since due to other limiting factors, the achievable rate almost saturates at this resolution. We also show that in the multiuser scenario digital beamforming is in any case more energy efficient than hybrid beamforming. In addition, we show that if mixed ADC resolutions are used, we can achieve any desired tradeoff between power consumption and rate close to those achieved with only one ADC resolution.

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A Comparison of Hybrid Beamforming and Digital Beamforming With Low-Resolution ADCs for Multiple Users and Imperfect CSI

For 5G, it will be important to leverage the available millimeter wave spectrum. To achieve an approximately omnidirectional coverage with a similar effective antenna aperture compared with the state-of-the-art cellular systems, an antenna array is required at both the mobile and base stations. Due to the large bandwidth, the analog front-end of the receiver with a large number of antennas becomes especially power hungry. Two main solutions exist to reduce the power consumption: Hybrid BeamForming (HBF) and Digital BeamForming (DBF) with low resolution Analog to Digital Converters (ADCs). An HBF system can also be combined with low resolution ADCs. This paper compares the spectral and energy efficiency based on the RF-frontend configuration. A channel with multipath propagation is used. In contrast to previous publication, we take the spatial correlation of the quantization noise into account. We show that the low resolution ADC DBF is robust to small Automatic Gain Control (AGC) imperfections. We showed that in the low SNR regime, the performance of DBF even with 1–2 bit resolution outperforms HBF. If we consider the relationship of spectral and energy efficiency, DBF with 3–5 bit resolution achieves the best ratio of spectral efficiency per power consumption of the RF receiver frontend over a wide SNR range. The power consumption model is based on components reported in the literature.

Achievable Rate and Energy Efficiency of Hybrid and Digital Beamforming Receivers With Low Resolution ADC

Systems, apparatuses, methods, and computer-readable media, are provided for offloading computationally intensive tasks from one computer device to another computer device taking into account, inter alia, energy consumption and latency budgets for both computation and communication. Embodiments may also exploit multiple radio access technologies (RATs) in order to find opportunities to offload computational tasks by taking into account, for example, network/RAT functionalities, processing, offloading coding/encoding mechanisms, and/or differentiating traffic between different RATs. Other embodiments may be described and/or claimed.

Application computation offloading for mobile edge computing

Embodiments herein may include systems, apparatuses, methods, and computer-readable media, for a multi-access edge computing (MEC) system. An apparatus for MEC may include a communication interface, a local cost measurements module, and a service allocation module. The communication interface may receive, from a UE, a request for a service to be provided to the UE. The local cost measurements module may collect a set of local cost measurements for the service. The service allocation module may determine to allocate the service to a MEC host based on an allocation policy related to a cost for the MEC host to provide the service or a cost for a service provider to provide the service in view of the one or more local cost measurements. Other embodiments may be described and/or claimed.

Kilian Roth

Papers

The 5G candidate waveform race: a comparison of complexity and performance

A Comparison of Hybrid Beamforming and Digital Beamforming With Low-Resolution ADCs for Multiple Users and Imperfect CSI

Achievable Rate and Energy Efficiency of Hybrid and Digital Beamforming Receivers With Low Resolution ADC

Application computation offloading for mobile edge computing

Multi-access edge computing (MEC) service provision based on local cost measurements