Millimeter wave (mmWave) cellular systems will enable gigabit-per-second data rates thanks to the large bandwidth available at mmWave frequencies. To realize sufficient link margin, employ directional beamforming with antenna arrays both transmitter and receiver. Due high cost power consumption of gigasample mixed-signal devices, precoding likely be divided among analog digital domains. The number antennas presence requires development mmWave-specific channel estimation algorithms. This...

Frequencies from 100 GHz to 3 THz are promising bands for the next generation of wireless communication systems because wide swaths unused and unexplored spectrum. These frequencies also offer potential revolutionary applications that will be made possible by new thinking, advances in devices, circuits, software, signal processing, systems. This paper describes many technical challenges opportunities sensing above GHz, presents a number discoveries, novel approaches, recent results aid...

Antenna arrays will be an important ingredient in millimeter-wave (mmWave) cellular systems. A natural application of antenna is simultaneous transmission to multiple users. Unfortunately, the hardware constraints mmWave systems make it difficult apply conventional lower frequency multiuser MIMO precoding techniques at mmWave. This paper develops low-complexity hybrid analog/digital for downlink Hybrid involves a combination analog and digital processing that inspired by power consumption...

Hybrid analog/digital multiple-input multiple-output architectures were recently proposed as an alternative for fully digital-precoding in millimeter wave wireless communication systems. This is motivated by the possible reduction number of RF chains and analog-to-digital converters. In these architectures, analog processing network usually based on variable phase shifters. this paper, we propose hybrid switching networks to reduce complexity power consumption structures We define a model...

We provide a comprehensive overview of mathematical models and analytical techniques for millimeter wave (mmWave) cellular systems. The two fundamental physical differences from conventional sub-6-GHz systems are: 1) vulnerability to blocking 2) the need significant directionality at transmitter and/or receiver, which is achieved through use large antenna arrays small individual elements. compare both these factors, present baseline approach based on stochastic geometry that allows...

Millimeter-wave communication is one way to alleviate the spectrum gridlock at lower frequencies while simultaneously providing high-bandwidth channels. MmWave makes use of MIMO through large antenna arrays both base station and mobile provide sufficient received signal power. This article explains how beamforming precoding are different in mmWave systems than their lower-frequency counterparts, due hardware constraints channel characteristics. Two potential architectures reviewed: hybrid...

Employing large intelligent surfaces (LISs) is a promising solution for improving the coverage and rate of future wireless systems. These comprise massive numbers nearly-passive elements that interact with incident signals, example by reflecting them, in smart way improves system performance. Prior work focused on design LIS reflection matrices assuming full channel knowledge. Estimating these channels at LIS, however, key challenging problem. With number elements, estimation or beam...

Hybrid analog/digital precoding offers a compromise between hardware complexity and system performance in millimeter wave (mmWave) systems. This type of allows mmWave systems to leverage large antenna array gains that are necessary for sufficient link margin, while permitting low cost power consumption hardware. Most prior work has focused on hybrid narrowband systems, with perfect or estimated channel knowledge at the transmitter. MmWave however, will likely operate wideband channels...

Supporting high mobility in millimeter wave (mmWave) systems enables a wide range of important applications, such as vehicular communications and wireless virtual/augmented reality. Realizing this practice, though, requires overcoming several challenges. First, the use narrow beams sensitivity mmWave signals to blockage greatly impact coverage reliability highly-mobile links. Second, users dense deployments need frequently hand-off between base stations (BSs), which is associated with...

Hybrid analog/digital precoding architectures can address the tradeoff between achievable spectral efficiency and power consumption in large-scale MIMO systems. This makes them a promising candidate for millimeter wave systems, which deploy large antenna arrays at both transmitter receiver to guarantee sufficient received signal power. Most prior work on hybrid focused narrowband channels assumed fully connected architectures. Millimeter (mmWave) though, are expected be wideband with...

Hybrid analog and digital precoding allows millimeter wave (mmWave) systems to achieve both array multiplexing gain. The design of the hybrid precoders combiners, though, is usually based on knowledge channel. Prior work mmWave channel estimation with architectures focused narrowband channels. Since will be wideband frequency selectivity, it vital develop solutions for architectures-based systems. In this paper, we a sparse formulation compressed sensing-based problem architectures. First,...

The millimeter-wave (mmWave) band offers the potential for high-bandwidth communication channels in cellular networks. It is not clear, however, whether both high data rates and coverage terms of signal-to-noise-plus-interference ratio can be achieved interference-limited mmWave networks due to differences propagation conditions antenna topologies. This article shows that dense achieve higher comparable relative conventional microwave Sum rate gains using more advanced beamforming techniques...

Next-generation cellular standards may leverage the large bandwidth available at millimeter wave (mmWave) frequencies to provide gigabit-per-second data rates in outdoor wireless systems. A main challenge realizing mmWave is achieving sufficient operating link margin, which enabled via directional beamforming with antenna arrays. Due high cost and power consumption of high-bandwidth mixed-signal devices, will likely include a combination analog digital processing. In this paper, we develop...

Millimeter wave (mmWave) systems will likely employ directional beamforming with large antenna arrays at both the transmitters and receivers. Acquiring channel knowledge to design these beamformers, however, is challenging due small signal-to-noise ratio before beamforming. In this paper, we propose evaluate a downlink system operation for multi-user mmWave based on compressed sensing estimation conjugate analog Adopting achievable sum-rate as performance metric, show how many measurements...

Machine learning tools are finding interesting applications in millimeter wave (mmWave) and massive MIMO systems. This is mainly thanks to their powerful capabilities unknown models tackling hard optimization problems. To advance the machine research mmWave/massive MIMO, however, there a need for common dataset. dataset can be used evaluate developed algorithms, reproduce results, set benchmarks, compare different solutions. In this work, we introduce DeepMIMO dataset, which generic...

Hybrid analog/digital architectures and receivers with low-resolution analog-to-digital converters (ADCs) are two low power solutions for wireless systems large antenna arrays, such as millimeter wave massive multiple-input multiple-output systems. Most prior work represents extreme cases in which either a small number of radio frequency (RF) chains full-resolution ADCs, or ADC RF equal to the antennas is assumed. In this paper, generalized hybrid architecture finite bits proposed. For...

Predicting the millimeter wave (mmWave) beams and blockages using sub-6 GHz channels has potential of enabling mobility reliability in scalable mmWave systems. Prior work focused on extracting spatial channel characteristics at band then use them to reduce beam training overhead. This approach still requires refinement does not normally account for different dielectric properties bands. In this paper, we first prove that under certain conditions, there exist mapping functions can predict...

Precoding/combining and large antenna arrays are essential in millimeter wave (mmWave) systems. In traditional MIMO systems, precoding/combining is usually done digitally at baseband with one radio frequency (RF) chain analog-to-digital converter (ADC) per antenna. The high cost power consumption of RF chains ADCs mmWave frequencies make an all-digital processing approach prohibitive. When only a limited number available, hybrid architectures that split the into analog digital domains...

The fifth generation of wireless communications (5G) promises massive increases in traffic volume and data rates, as well improved reliability voice calls. Jointly optimizing beamforming, power control, interference coordination a 5G network to enhance the communication performance end users poses significant challenge. In this paper, we formulate joint design non-convex optimization problem maximize signal plus noise ratio (SINR) solve using deep reinforcement learning. By greedy nature...

Can we map the channels at one set of antennas and frequency band to another antennas- possibly a different location band? If this channel-to-channel mapping is possible, can expect dramatic gains for massive MIMO systems. For example, in FDD MIMO, uplink be mapped downlink or subset all other antennas. This significantly reduce (or even eliminate) training/feedback overhead. In context cell-free/distributed systems, channel leveraged fronthaul signaling overheadIn paper, introduce new...

As a promising candidate for future wireless systems, large intelligent surfaces (LISs) recently emerged to serve considerate improvements in both spectral and energy efficiencies. These consist of numbers passive elements capable intelligently reflecting the incident signals. Since LIS employs elements, critical challenges are inherent channel training/estimation process order properly design reflection matrices. One challenge particularly is how acquire knowledge with low training overhead...

Employing large intelligent surfaces (LISs) is a promising solution for improving the coverage and rate of future wireless systems. These comprise massive number nearly-passive elements that interact with incident signals, example by reflecting them, in smart way improves system performance. Prior work focused on design LIS reflection matrices assuming full knowledge channels. Estimating these channels at LIS, however, key challenging problem, associated training overhead given elements....

This paper investigates a novel research direction that leverages vision to help overcome the critical wireless communication challenges. In particular, this considers millimeter wave (mmWave) systems, which are principal components of 5G and beyond. These systems face two important challenges: (i) large training overhead associated with selecting optimal beam (ii) reliability challenge due high sensitivity link blockages. Interestingly, most devices employ mmWave arrays will likely also use...

Artificial intelligence (AI) based downlink channel state information (CSI) prediction for frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems has attracted growing attention recently. However, existing works focus on the CSI users under a given environment and is hard to adapt in new especially when labeled data limited. To address this issue, we formulate as deep transfer learning (DTL) problem, propose direct-transfer algorithm fully-connected neural...

The promising coverage and spectral efficiency gains of intelligent reflecting surfaces (IRSs) are attracting increasing interest. To adopt these in practice, however, several challenges need to be addressed. One main is how configure the coefficients on passive without requiring massive channel estimation or beam training overhead. Earlier work suggested leveraging supervised learning tools predict IRS reflection matrices. While this approach has potential reducing overhead, it requires...