Showing papers on "Communication channel published in 2017"

Cell-Free Massive MIMO Versus Small Cells

Abstract: A Cell-Free Massive MIMO (multiple-input multiple-output) system comprises a very large number of distributed access points (APs), which simultaneously serve a much smaller number of users over the same time/frequency resources based on directly measured channel characteristics. The APs and users have only one antenna each. The APs acquire channel state information through time-division duplex operation and the reception of uplink pilot signals transmitted by the users. The APs perform multiplexing/de-multiplexing through conjugate beamforming on the downlink and matched filtering on the uplink. Closed-form expressions for individual user uplink and downlink throughputs lead to max–min power control algorithms. Max–min power control ensures uniformly good service throughout the area of coverage. A pilot assignment algorithm helps to mitigate the effects of pilot contamination, but power control is far more important in that regard. Cell-Free Massive MIMO has considerably improved performance with respect to a conventional small-cell scheme, whereby each user is served by a dedicated AP, in terms of both 95%-likely per-user throughput and immunity to shadow fading spatial correlation. Under uncorrelated shadow fading conditions, the cell-free scheme provides nearly fivefold improvement in 95%-likely per-user throughput over the small-cell scheme, and tenfold improvement when shadow fading is correlated.

Optical Communication in Space: Challenges and Mitigation Techniques

Abstract: In recent years, free space optical (FSO) communication has gained significant importance owing to its unique features: large bandwidth, license free spectrum, high data rate, easy and quick deployability, less power, and low mass requirements. FSO communication uses optical carrier in the near infrared band to establish either terrestrial links within the Earth’s atmosphere or inter-satellite/deep space links or ground-to-satellite/satellite-to-ground links. It also finds its applications in remote sensing, radio astronomy, military, disaster recovery, last mile access, backhaul for wireless cellular networks, and many more. However, despite of great potential of FSO communication, its performance is limited by the adverse effects (viz., absorption, scattering, and turbulence) of the atmospheric channel. Out of these three effects, the atmospheric turbulence is a major challenge that may lead to serious degradation in the bit error rate performance of the system and make the communication link infeasible. This paper presents a comprehensive survey on various challenges faced by FSO communication system for ground-to-satellite/satellite-to-ground and inter-satellite links. It also provides details of various performance mitigation techniques in order to have high link availability and reliability. The first part of this paper will focus on various types of impairments that pose a serious challenge to the performance of optical communication system for ground-to-satellite/satellite-to-ground and inter-satellite links. The latter part of this paper will provide the reader with an exhaustive review of various techniques both at physical layer as well as at the other layers (link, network, or transport layer) to combat the adverse effects of the atmosphere. It also uniquely presents a recently developed technique using orbital angular momentum for utilizing the high capacity advantage of optical carrier in case of space-based and near-Earth optical communication links. This survey provides the reader with comprehensive details on the use of space-based optical backhaul links in order to provide high capacity and low cost backhaul solutions.

Power of Deep Learning for Channel Estimation and Signal Detection in OFDM Systems

Abstract: This article presents our initial results in deep learning for channel estimation and signal detection in orthogonal frequency-division multiplexing (OFDM). OFDM has been widely adopted in wireless broadband communications to combat frequency-selective fading in wireless channels. In this article, we take advantage of deep learning in handling wireless OFDM channels in an end-to-end approach. Different from existing OFDM receivers that first estimate CSI explicitly and then detect/recover the transmitted symbols with the estimated CSI, our deep learning based approach estimates CSI implicitly and recovers the transmitted symbols directly. To address channel distortion, a deep learning model is first trained offline using the data generated from the simulation based on the channel statistics and then used for recovering the online transmitted data directly. From our simulation results, the deep learning based approach has the ability to address channel distortions and detect the transmitted symbols with performance comparable to minimum mean-square error (MMSE) estimator. Furthermore, the deep learning based approach is more robust than conventional methods when fewer training pilots are used, the cyclic prefix (CP) is omitted, and nonlinear clipping noise is presented. In summary, deep learning is a promising tool for channel estimation and signal detection in wireless communications with complicated channel distortions and interferences.

Deep learning for wireless physical layer: Opportunities and challenges

Abstract: Machine learning (ML) has been widely applied to the upper layers of wireless communication systems for various purposes, such as deployment of cognitive radio and communication network. However, its application to the physical layer is hampered by sophisticated channel environments and limited learning ability of conventional ML algorithms. Deep learning (DL) has been recently applied for many fields, such as computer vision and natural language processing, given its expressive capacity and convenient optimization capability. The potential application of DL to the physical layer has also been increasingly recognized because of the new features for future communications, such as complex scenarios with unknown channel models, high speed and accurate processing requirements; these features challenge conventional communication theories. This paper presents a comprehensive overview of the emerging studies on DL-based physical layer processing, including leveraging DL to redesign a module of the conventional communication system (for modulation recognition, channel decoding, and detection) and replace the communication system with a radically new architecture based on an autoencoder. These DL-based methods show promising performance improvements but have certain limitations, such as lack of solid analytical tools and use of architectures that are specifically designed for communication and implementation research, thereby motivating future research in this field.

Enhancing the Physical Layer Security of Non-Orthogonal Multiple Access in Large-Scale Networks

Abstract: This paper investigates the physical layer security of non-orthogonal multiple access (NOMA) in large-scale networks with invoking stochastic geometry. Both single-antenna and multiple-antenna aided transmission scenarios are considered, where the base station (BS) communicates with randomly distributed NOMA users. In the single-antenna scenario, we adopt a protected zone around the BS to establish an eavesdropper-exclusion area with the aid of careful channel ordering of the NOMA users. In the multiple-antenna scenario, artificial noise is generated at the BS for further improving the security of a beamforming-aided system. In order to characterize the secrecy performance, we derive new exact expressions of the security outage probability for both single-antenna and multiple-antenna aided scenarios. For the single-antenna scenario, we perform secrecy diversity order analysis of the selected user pair. The analytical results derived demonstrate that the secrecy diversity order is determined by the specific user having the worse channel condition among the selected user pair. For the multiple-antenna scenario, we derive the asymptotic secrecy outage probability, when the number of transmit antennas tends to infinity. Monte Carlo simulations are provided for verifying the analytical results derived and to show that: 1) the security performance of the NOMA networks can be improved by invoking the protected zone and by generating artificial noise at the BS and 2) the asymptotic secrecy outage probability is close to the exact secrecy outage probability.

Orthogonal Time Frequency Space Modulation

Abstract: A new two-dimensional modulation technique called Orthogonal Time Frequency Space (OTFS) modulation designed in the delay-Doppler domain is introduced. Through this design, which exploits full diversity over time and frequency, OTFS coupled with equalization converts the fading, time-varying wireless channel experienced by modulated signals such as OFDM into a time-independent channel with a complex channel gain that is roughly constant for all symbols. Thus, transmitter adaptation is not needed. This extraction of the full channel diversity allows OTFS to greatly simplify system operation and significantly improves performance, particular in systems with high Doppler, short packets, and large antenna arrays. Simulation results indicate at least several dB of block error rate performance improvement for OTFS over OFDM in all of these settings. In addition these results show that even at very high Dopplers (500 km#x002F;h), OTFS approaches channel capacity through linear scaling of throughput with the MIMO order, whereas the performance of OFDM under typical design parameters breaks down completely.

A Unified Transmission Strategy for TDD/FDD Massive MIMO Systems With Spatial Basis Expansion Model

Abstract: This paper proposes a unified transmission strategy for multiuser time division duplex (TDD)/frequency division duplex (FDD) massive multiple-input–multiple-output (MIMO) systems, including uplink (UL)/downlink (DL) channel estimation and user scheduling for data transmission. With the aid of antenna array theory and array signal processing, we build a spatial basis expansion model (SBEM) to represent the UL/DL channels with far fewer parameter dimensions. Hence, both the UL and DL channel estimations of multiusers can be carried out with a small amount of training resource, which significantly reduces the training overhead and feedback cost. Meanwhile, the pilot contamination problem in the UL training is immediately relieved by exploiting the spatial information of users. To enhance the spectral efficiency, we also design a greedy user scheduling scheme during the data transmission period. Compared with existing low-rank models, the newly proposed SBEM offers an alternative for channel acquisition without the need for channel statistics and can be applied to both TDD and FDD systems. Various numerical results are provided to corroborate the proposed studies.

Channel Estimation and Performance Analysis of One-Bit Massive MIMO Systems

Abstract: This paper considers channel estimation and system performance for the uplink of a single-cell massive multiple-input multiple-output system. Each receiver antenna of the base station is assumed to be equipped with a pair of one-bit analog-to-digital converters to quantize the real and imaginary part of the received signal. We first propose an approach for channel estimation that is applicable for both flat and frequency-selective fading, based on the Bussgang decomposition that reformulates the nonlinear quantizer as a linear function with identical first- and second-order statistics. The resulting channel estimator outperforms previously proposed approaches across all SNRs. We then derive closed-form expressions for the achievable rate in flat fading channels assuming low SNR and a large number of users for the maximal ratio and zero forcing receivers that takes channel estimation error due to both noise and one-bit quantization into account. The closed-form expressions, in turn, allow us to obtain insight into important system design issues such as optimal resource allocation, maximal sum spectral efficiency, overall energy efficiency, and number of antennas. Numerical results are presented to verify our analytical results and demonstrate the benefit of optimizing system performance accordingly.

Channel Estimation for Hybrid Architecture-Based Wideband Millimeter Wave Systems

Abstract: Hybrid analog and digital precoding allows millimeter wave (mmWave) systems to achieve both array and multiplexing gain. The design of the hybrid precoders and combiners, though, is usually based on the knowledge of the channel. Prior work on mmWave channel estimation with hybrid architectures focused on narrowband channels. Since mmWave systems will be wideband with frequency selectivity, it is vital to develop channel estimation solutions for hybrid architectures-based wideband mmWave systems. In this paper, we develop a sparse formulation and compressed sensing-based solutions for the wideband mmWave channel estimation problem for hybrid architectures. First, we leverage the sparse structure of the frequency-selective mmWave channels and formulate the channel estimation problem as a sparse recovery in both time and frequency domains. Then, we propose explicit channel estimation techniques for purely time or frequency domains and for combined time/frequency domains. Our solutions are suitable for both single carrier-frequency domain equalization and orthogonal frequency-division multiplexing systems. Simulation results show that the proposed solutions achieve good channel estimation quality, while requiring small training overhead. Leveraging the hybrid architecture at the transceivers gives further improvement in estimation error performance and achievable rates.

Throughput Analysis of Massive MIMO Uplink With Low-Resolution ADCs

Abstract: We investigate the uplink throughput achievable by a multiple-user (MU) massive multiple-input multiple-output (MIMO) system, in which the base station is equipped with a large number of low-resolution analog-to-digital converters (ADCs). Our focus is on the case where neither the transmitter nor the receiver have any a priori channel state information. This implies that the fading realizations have to be learned through pilot transmission followed by channel estimation at the receiver, based on coarsely quantized observations. We propose a novel channel estimator, based on Bussgang’s decomposition, and a novel approximation to the rate achievable with finite-resolution ADCs, both for the case of finite-cardinality constellations and of Gaussian inputs, that is accurate for a broad range of system parameters. Through numerical results, we illustrate that, for the 1-bit quantized case, pilot-based channel estimation together with maximal-ratio combing, or zero-forcing detection enables reliable multi-user communication with high-order constellations, in spite of the severe nonlinearity introduced by the ADCs. Furthermore, we show that the rate achievable in the infinite-resolution (no quantization) case can be approached using ADCs with only a few bits of resolution. We finally investigate the robustness of low-ADC-resolution MU-MIMO uplink against receive power imbalances between the different users, caused for example by imperfect power control.

Uplink Performance of Wideband Massive MIMO With One-Bit ADCs

Abstract: Analog-to-digital converters (ADCs) stand for a significant part of the total power consumption in a massive multiple-input multiple-output (MIMO) base station. One-bit ADCs are one way to reduce power consumption. This paper presents an analysis of the spectral efficiency of single-carrier and orthogonal-frequency-division-multiplexing (OFDM) transmission in massive MIMO systems that use one-bit ADCs. A closed-form achievable rate, i.e., a lower bound on capacity, is derived for a wideband system with a large number of channel taps that employ low-complexity linear channel estimation and symbol detection. Quantization results in two types of error in the symbol detection. The circularly symmetric error becomes Gaussian in massive MIMO and vanishes as the number of antennas grows. The amplitude distortion, which severely degrades the performance of OFDM, is caused by variations between symbol durations in received interference energy. As the number of channel taps grows, the amplitude distortion vanishes and OFDM has the same performance as single-carrier transmission. A main conclusion of this paper is that wideband massive MIMO systems work well with one-bit ADCs.

Analysis and synthesis of networked control systems: A survey of recent advances and challenges.

Abstract: A networked control system (NCS) is a control system which involves a communication network. In NCSs, the continuous-time measurement is usually sampled and quantized before transmission. Then, the measurement is transmitted to the remote controller via the communication channel, during which the signal may be delayed, lost or even sometimes not allowed for transmission due to the communication or energy constraints. In recent years, the modeling, analysis and synthesis of networked control systems (NCSs) have received great attention, which leads to a large number of publications. This paper attempts to present an overview of recent advances and unify them in a framework of network-induced issues such as signal sampling, data quantization, communication delay, packet dropouts, medium access constraints, channel fading and power constraint, and present respective solution approaches to each of these issues. We draw some conclusions and highlight future research directions in end.

Radar-Communications Convergence: Coexistence, Cooperation, and Co-Design

Abstract: In this paper, we introduce a radar information metric, the estimation rate, that allows the radar user to be considered in a multiple-access channel enabling performance bounds for joint radar-communications coexistence to be derived. Traditionally, the two systems were isolated in one or multiple dimensions. We categorize new attempts at spectrum-space-time convergence as either coexistence, cooperation, or co-design. The meaning and interpretation of the estimation rate and what it means to alter it are discussed. Additionally, we introduce and elaborate on the concept of “not all bits are equal,” which states that communications rate bits and estimation rate bits do not have equal value. Finally, results for joint radar-communications information bounds and their accompanying weighted spectral efficiency measures are presented.

Resource Allocation for D2D-Enabled Vehicular Communications

Abstract: The widely deployed cellular network, assisted with device-to-device (D2D) communications, can provide a promising solution to support efficient and reliable vehicular communications. Fast channel variations caused by high mobility in a vehicular environment need to be properly accounted for when designing resource allocation schemes for the D2D-enabled vehicular networks. In this paper, we perform spectrum sharing and power allocation based only on slowly varying large-scale fading information of wireless channels. Pursuant to differing requirements for different types of links, i.e., high capacity for vehicle-to-infrastructure (V2I) links and ultrareliability for vehicle-to-vehicle (V2V) links, we attempt to maximize the ergodic capacity of the V2I connections while ensuring reliability guarantee for each V2V link. Sum ergodic capacity of all V2I links is first taken as the optimization objective to maximize the overall V2I link throughput. Minimum ergodic capacity maximization is then considered to provide a more uniform capacity performance across all V2I links. Novel algorithms that yield optimal resource allocation and are robust to channel variations are proposed. Their desirable performance is confirmed by computer simulation.

Air–Ground Channel Characterization for Unmanned Aircraft Systems—Part I: Methods, Measurements, and Models for Over-Water Settings

Abstract: The use of unmanned aerial systems (UASs), which are also known as unmanned aerial vehicles, and by the term “drones” in the popular press, is growing rapidly. To ensure safety, UAS control and nonpayload communication (CNPC) links must operate very reliably in a variety of conditions. This requires an accurate quantitative characterization of the air–ground (AG) channel, and this channel characterization is the focus of this paper. After providing motivation and background, we describe our methods and modeling approach, followed by a description of our simultaneous dual-band (L-band ∼970 MHz, C-band ∼5 GHz) measurement campaign and the over-water (OW) measurement sites. Example results for path loss and root-mean-square delay spread are provided, as well as the results for channel stationarity distance (SD), used in calculating small-scale Rician $K$ - factor and correlations between the two receiver antennas that we employed in each frequency band. Two distinct SD measures—the power delay profile (PDP) correlation coefficient and the spatial autocorrelation matrix collinearity—were used and found to be of the same order. Path-loss exponents are near that of free space, but significant two-ray cancelation effects for these OW settings warrant more accurate models, which we provide. Delay spreads in the OW channels are also dominated by the two-ray components and are hence typically very small (∼10 ns) but can exceed 350 ns. A third intermittent multipath component (MPC) is also present a nonnegligible fraction of time; hence, we provide statistical wideband AG channel models to represent this. Future papers in this series will report results for the AG channel with ground sites in other types of environments.

Transmission device with channel equalization and control and methods for use therewith

Abstract: Aspects of the subject disclosure may include, for example, a transmission device that includes at least one transceiver configured to modulate data to generate a plurality of first electromagnetic waves in accordance with channel control parameters. A plurality of couplers are configured to couple at least a portion of the plurality of first electromagnetic waves to a transmission medium, wherein the plurality of couplers generate a plurality of second electromagnetic waves that propagate along the outer surface of the transmission medium. A training controller is configured to generate the channel control parameters based on channel state information received from at least one remote transmission device. Other embodiments are disclosed.

Air–Ground Channel Characterization for Unmanned Aircraft Systems—Part III: The Suburban and Near-Urban Environments

Abstract: Applications for unmanned aircraft systems (UAS), or “drones,” are increasing rapidly. In order to provide safe and reliable links to integrate UAS into the National Airspace System (NAS), control and nonpayload communication (CNPC) system requirements are being specified. A comprehensive knowledge of the air-to-ground (AG) channels in the bands of interest (C-band and L-band) plays an essential role. The NASA Glenn Research Center has sponsored an AG channel measurement campaign for most of the typical ground site (GS) local environments, including over water [8] , hilly/mountainous [9] , suburban, and near-urban. As a continuation of our prior study, this paper addresses the suburban and near-urban scenarios. Our developed AG channel models include path loss, small-scale fading Ricean K factors, spatial and interfrequency correlations for multiple aircraft antennas, root-mean-square (RMS) delay spread, and wideband tapped delay line (TDL) models. The path loss is described by either log-distance or two-ray models, with small corrections for flight direction. The K factors were 12 (14) dB in L-band and 27.4 (28.5) dB in C-band in near-urban (suburban) environments. The interband signals were uncorrelated, but the intra-band signals were highly correlated, with the median correlation coefficient greater than 0.85. The C-band RMS delay spread was on average 10 to 60 ns, with maximum of approximately 4 μs. The TDL models are composed of the line-of-sight (LOS) component, a ground reflection, and up to seven intermittent multipath components (MPCs). Relative power, phase, occurrence probability, duration, and excess delays for these intermittent MPCs are quantified. An algorithm to simulate the AG channel impulse response (CIR) via the TDL models is provided.

AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks

Abstract: Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.

The Impact of Beamwidth on Temporal Channel Variation in Vehicular Channels and Its Implications

Abstract: Millimeter wave (mmWave) has great potential in realizing high data rates, thanks to the large spectral channels. It is considered as a key technology for fifth-generation (5G) wireless networks and is already used in wireless LAN (e.g., IEEE 802.11ad). Using mmWave for vehicular communications, however, is often viewed with some skepticism due to a misconception that the Doppler spread would become too large at these high frequencies. This is not necessarily true when directional beams are employed. In this paper, closed-form expressions relating the channel coherence time and beamwidth are derived. Unlike prior work that assumed perfect beam pointing, the pointing error due to the receiver motion is incorporated to show that there exists a nonzero optimal beamwidth that maximizes the coherence time. We define a novel concept of beam coherence time, which is an effective measure of beam alignment frequency. Using the derived correlation function, the channel coherence time, and the beam coherence time, an overall performance metric considering both the channel time variation and the beam alignment overhead is derived. Using this metric, it is shown that beam realignment in every beam coherence time performs better than beam realignment in every channel coherence time.

A novel millimeter-wave channel simulator and applications for 5G wireless communications

Abstract: This paper presents details and applications of a novel channel simulation software named NYUSIM, which can be used to generate realistic temporal and spatial channel responses to support realistic physical-and link-layer simulations and design for fifth-generation (5G) cellular communications. NYUSIM is built upon the statistical spatial channel model for broadband millimeter-wave (mmWave) wireless communication systems developed by researchers at New York University (NYU). The simulator is applicable for a wide range of carrier frequencies (500 MHz to 100 GHz), radio frequency (RF) bandwidths (0 to 800 MHz), antenna beamwidths (7° to 360° for azimuth and 7° to 45° for elevation), and operating scenarios (urban microcell, urban macrocell, and rural macrocell), and also incorporates multiple-input multiple-output (MIMO) antenna arrays at the transmitter and receiver. This paper also provides examples to demonstrate how to use NYUSIM for analyzing MIMO channel conditions and spectral efficiencies, which show that NYUSIM is an alternative and more realistic channel model compared to the 3rd Generation Partnership Project (3GPP) and other channel models for mmWave bands.

End-to-End Simulation of 5G mmWave Networks

Abstract: Due to its potential for multi-gigabit and low latency wireless links, millimeter wave (mmWave) technology is expected to play a central role in 5th generation cellular systems. While there has been considerable progress in understanding the mmWave physical layer, innovations will be required at all layers of the protocol stack, in both the access and the core network. Discrete-event network simulation is essential for end-to-end, cross-layer research and development. This paper provides a tutorial on a recently developed full-stack mmWave module integrated into the widely used open-source ns--3 simulator. The module includes a number of detailed statistical channel models as well as the ability to incorporate real measurements or ray-tracing data. The Physical (PHY) and Medium Access Control (MAC) layers are modular and highly customizable, making it easy to integrate algorithms or compare Orthogonal Frequency Division Multiplexing (OFDM) numerologies, for example. The module is interfaced with the core network of the ns--3 Long Term Evolution (LTE) module for full-stack simulations of end-to-end connectivity, and advanced architectural features, such as dual-connectivity, are also available. To facilitate the understanding of the module, and verify its correct functioning, we provide several examples that show the performance of the custom mmWave stack as well as custom congestion control algorithms designed specifically for efficient utilization of the mmWave channel.

Multi-Resolution Codebook and Adaptive Beamforming Sequence Design for Millimeter Wave Beam Alignment

Abstract: Millimeter wave (mm-wave) communication is expected to be widely deployed in fifth generation (5G) wireless networks due to the substantial bandwidth available for licensed and unlicensed use at mm-wave frequencies. To overcome the higher path loss observed at mm-wave bands, most prior work focused on the design of directional beamforming using analog and/or hybrid beamforming techniques in large-scale multiple-input multiple-output systems. Obtaining potential gains from highly directional beamforming in practical systems hinges on sufficient levels of channel estimation accuracy, where the problem of channel estimation becomes more challenging due to the substantial training overhead needed to sound all directions using a high-resolution narrow beam. In this paper, we consider the design of multi-resolution beamforming sequences to enable the system to quickly search out the dominant channel direction for single-path channels. The resulting design generates a multilevel beamforming sequence that strikes a balance between minimizing the training overhead and maximizing beamforming gain, where a subset of multilevel beamforming vectors is chosen adaptively to maximize the average data rate within a constrained time. We propose an efficient method to design a hierarchical multi-resolution codebook utilizing a Butler matrix, i.e., a generalized discrete Fourier transform matrix. Numerical results show the effectiveness of the proposed algorithm.

Multi-User Precoding and Channel Estimation for Hybrid Millimeter Wave Systems

Abstract: In this paper, we develop a low-complexity channel estimation for hybrid millimeter wave (mmWave) systems, where the number of radio frequency (RF) chains is much less than the number of antennas equipped at each transceiver. The proposed mmWave channel estimation algorithm first exploits multiple frequency tones to estimate the strongest angle-of-arrivals (AoAs) at both base station (BS) and user sides for the design of analog beamforming matrices. Then, all the users transmit orthogonal pilot symbols to the BS along the directions of the estimated strongest AoAs in order to estimate the channel. The estimated channel will be adopted to design the digital zero-forcing (ZF) precoder at the BS for the multi-user downlink transmission. The proposed channel estimation algorithm is applicable to both the non-sparse and sparse mmWave channel environments. Furthermore, we derive a tight achievable rate upper bound of the digital ZF precoding with the proposed channel estimation algorithm scheme. Our analytical and simulation results show that the proposed scheme obtains a considerable achievable rate of fully digital systems, where the number of RF chains equipped at each transceiver is equal to the number of antennas. Besides, considering the effect of various types of errors, i.e., random phase errors, transceiver analog beamforming errors, and equivalent channel estimation errors, we derive a closed-form approximation for the achievable rate of the considered scheme. We illustrate the robustness of the proposed channel estimation and multi-user downlink precoding scheme against the system imperfection.

Fast Channel Tracking for Terahertz Beamspace Massive MIMO Systems

Abstract: The recent concept of beamspace multiple input multiple output (MIMO) with discrete lens array can utilize beam selection to reduce the number of radio-frequency chains (RF) required in terahertz (THz) massive MIMO systems. However, to achieve the capacity-approaching performance, beam selection requires information on a beamspace channel of large size. This is difficult to obtain since the user mobility usually leads to the fast variation of THz beamspace channels, and the conventional real-time channel estimation schemes involve unaffordable pilot overhead. To solve this problem, in this paper, we propose the a priori aided (PA) channel tracking scheme. Specifically, by considering a practical user motion model, we first excavate a temporal variation law of the physical direction between the base station and each mobile user. Then, based on this law and the special sparse structure of THz beamspace channels, we propose to utilize the obtained beamspace channels in the previous time slots to predict the prior information of the beamspace channel in the following time slot without channel estimation. Finally, aided by the obtained prior information, the time-varying beamspace channels can be tracked with low pilot overhead. Simulation results verify that to achieve the same accuracy, the proposed PA channel tracking scheme requires much lower pilot overhead and signal-to-noise ratio (SNR) than the conventional schemes.

Deep Learning Based MIMO Communications.

Abstract: We introduce a novel physical layer scheme for single user Multiple-Input Multiple-Output (MIMO) communications based on unsupervised deep learning using an autoencoder. This method extends prior work on the joint optimization of physical layer representation and encoding and decoding processes as a single end-to-end task by expanding transmitter and receivers to the multi-antenna case. We introduce a widely used domain appropriate wireless channel impairment model (Rayleigh fading channel), into the autoencoder optimization problem in order to directly learn a system which optimizes for it. We considered both spatial diversity and spatial multiplexing techniques in our implementation. Our deep learning-based approach demonstrates significant potential for learning schemes which approach and exceed the performance of the methods which are widely used in existing wireless MIMO systems. We discuss how the proposed scheme can be easily adapted for open-loop and closed-loop operation in spatial diversity and multiplexing modes and extended use with only compact binary channel state information (CSI) as feedback.

On Indoor Millimeter Wave Massive MIMO Channels: Measurement and Simulation

Abstract: The millimeter wave (mmWave) communications and massive multiple-input multiple-output (MIMO) are both widely considered to be the candidate technologies for the fifth generation mobile communication system. It is thus a good idea to combine these two technologies to achieve a better performance for large capacity and high data-rate transmission. However, one of the fundamental challenges is the characterization of mmWave massive MIMO channel. Most of the previous investigations in mmWave channel only focus on single-input single-output links or MIMO links, whereas the research of massive MIMO channels mainly focus on a frequency band below 6 GHz. This paper investigates the channel behaviors of massive MIMO at a mmWave frequency band around 26 GHz. An indoor mmWave massive MIMO channel measurement campaign with 64 and 128 array elements is conducted, based on which, path loss, shadow fading, root-mean-square (RMS) delay spread, and coherence bandwidth are extracted. Then, by using our developed ray-tracing simulator calibrated by the measurement data, we make the extensive ray-tracing simulations with 1024 antenna elements in the same indoor scenario, and get insights into the variation tendency of mean delay and the RMS delay with different array elements. It is observed that the measurement and the ray-tracing-based simulation results have reached a good agreement.

Method and apparatus for use with a radio distributed antenna having a fiber optic link

Abstract: Aspects of the subject disclosure may include, for example, a transceiver that converts first modulated channel signals in a first spectral segment to the first modulated channel signals in a second spectral segment based on signal processing of the first modulated channel signals and without modifying the signaling protocol of the first modulated channel signals. The transceiver transmits, via a fiber optic cable, a transmission signal including a first reference signal with the first modulated channel signals in the second spectral segment to a network element of a plurality of network elements of the distributed antenna system for wireless distribution of the first modulated channel signals to mobile communication devices in the first spectral segment. The first reference signal enables the distributed antenna system to reduce a phase error during processing of the first modulated channel signals from the second spectral segment to the first spectral segment.