Massive multiple-input multiple-output (MIMO) is an important technology in fifth generation (5G) cellular networks and beyond. To help design the beamforming at base station, 5G has introduced new support form of flexible feedback configurable antenna array geometries that allow for arbitrarily massive physical arrays. In this article, we present overview MIMO throughout mobile standards, highlight beam-based system NR, describe how enables through beam management. Finally, conclude with...

Wireless cellular networks have many parameters that are normally tuned upon deployment and re-tuned as the network changes. Many operational affect reference signal received power (RSRP), quality (RSRQ), signal-to-interference-plus-noise-ratio (SINR), and, ultimately, throughput. In this paper, we develop compare two approaches for maximizing coverage minimizing interference by jointly optimizing transmit downtilt (elevation tilt) settings across sectors. To evaluate different parameter...

Network slicing at the radio access network (RAN) domain, called RAN slicing, requires elasticity, efficient resource sharing, and customization. In this scenario, scheduling (RRS) is responsible for dealing with scarce limited frequency spectrum resources available domain while fulfilling slice intents. The wide variety of scenarios supported in 5G beyond networks makes RRS problem scenario a significant challenge. This paper proposes an intent-aware reinforcement learning method to perform...

Low resolution architectures are a power efficient solution for high bandwidth communication at millimeter wave and terahertz frequencies. In such systems, carrier synchronization is important yet has not received much attention. this paper, we develop analyze deep learning estimating the frequency of complex sinusoid in noise from 1-bit samples in-phase quadrature components. Carrier offset estimation used GSM first step towards developing more comprehensive with other kinds signals. We...

Beam codebooks are a recent feature to enable high dimension multiple-input multiple-output in 5G. Codebooks comprised of customizable beamforming weights can be used transmit reference signals and aid the channel state information (CSI) acquisition process. also for quantizing feedback following CSI measurement. In this paper, we unify beam management stages–codebook design, sweeping, feedback, data transmission–to characterize impact throughout We then design neural network find that...

Beam codebooks are a new feature of massive multiple-input multiple-output (M-MIMO) in 5G radio (NR). Codebooks comprised beamforming vectors used to transmit reference signals and obtain limited channel state information (CSI) from receivers via the codeword index. This enables large arrays that cannot otherwise sufficient CSI. The performance, however, is by codebook design. In this paper, we show machine learning can be train site-specific for initial access. We design neural network...

Obtaining accurate and timely channel state information (CSI) is a fundamental challenge for large antenna systems. Mobile systems like 5G use beam management framework that joins the initial access, beamforming, CSI acquisition, data transmission. The design of codebooks these stages, however, challenging due to their interrelationships, varying array sizes, site-specific user distributions. Furthermore, often focused on single-sector operations while ignoring overarching network-...

The detection and estimation of sinusoids is a fundamental signal processing task for many applications related to sensing communications. While algorithms have been proposed this setting, quantization critical, but often ignored modeling effect. In wireless communications, with low resolution data converters relevant reduced power consumption in wideband receivers. Similarly, sampling imaging spectrum allows efficient collection. work, we propose SignalNet, neural network architecture that...

Fifth-generation (5G) cellular communication systems have embraced massive multiple-input-multiple-output (MIMO) in the low- and mid-band frequencies. In a multiband system, base station can serve different users each band, while user equipment operate only single band simultaneously. This paper considers MIMO system where channels are dynamically allocated frequency bands. We treat as scheduling resource allocation problem propose deep reinforcement learning (DRL) agents to perform...

Beam codebooks are a recent feature to enable high dimension multiple-input multiple-output in 5G. Codebooks comprised of customizable beamforming weights can be used transmit reference signals and aid the channel state information (CSI) acquisition process. also for quantizing feedback following CSI acquisition. In this paper, we characterize role each codebook during beam management process design neural network find that improve overall system performance. Evaluating requires considering...

Cellular networks continue to trend rapidly towards more bands and carrier frequencies, along with higher base station density, requiring complex decisions be made when associating a mobile user band cell. This paper develops novel approach optimizing frequency cell selection while taking into account mobility handovers. is problem because of the uncertain link failure events, handover related overheads, significant difference in propagation characteristics between different bands. The...

Codebook-based beam selection is one approach for configuring millimeter wave communication links. The overhead required to reconfigure the transmit and receive pair, though, increases in highly dynamic vehicular systems. Location information coupled with machine learning (ML) recommendation way reduce of pair selection. In this paper, we develop ML-based location-aided approaches decouple between user equipment (UE) base station (BS). We quantify performance gaps due decoupling also...

Large MIMO arrays can improve network performance when configured with accurate channel state information. 5G supports two formats, or types, for feeding back information to the transmitter based on codebooks. Type-I is a direct codebook format containing small set of predefined codewords, while type-II feedback construction-based where represented as sum multipath components complex gains. Type-II involves more overhead than type-I feedback, but it computationally expensive and neither...

This paper presents a novel method for classifying radio frequency (RF) devices from their transmission signals. Given collection of signals identical devices, we accurately classify both the distance and specific device identity. We develop multiple classifier system that discriminates between channels classifies using normalized in-phase quadrature (IQ) samples. Our network uses residual connections classification, reaching 88.33% accuracy 16 unique over 11 different distances two times,...

Low resolution data converters can enable power efficient high bandwidth communication at millimeter-wave and terahertz frequencies. Synchronization of such systems is a critical step in accurate decoding, yet current approaches require long block lengths or fail to reach the Cramer Rao Bound (CRB).́ Prior solutions have traditionally been divided into two distinct focuses: algorithms designed sequences for synchronization. In this paper, we develop jointly optimized neural architecture...

Massive multiple-input multiple-output (MIMO) is an important technology in fifth generation (5G) cellular networks and beyond. To help design the beamforming at base station, 5G has introduced new support form of flexible feedback configurable antenna array geometries. In this article, we present overview MIMO throughout mobile standards, highlight beam-based system NR, describe how enables massive through beam management. Finally, conclude with challenges related to 5G.

Beam management is a strategy to unify beamforming and channel state information (CSI) acquisition with large antenna arrays in 5G. Codebooks serve multiple uses beam including reference signals, CSI reporting, analog training. In this paper, we propose evaluate machine learning-refined codebook design process for extremely multiple-input multiple-output (X-MIMO) systems. We neural network selection the initial access refinement codebooks using end-to-end learning from beamspace...

Wireless cellular networks have many parameters that are normally tuned upon deployment and re-tuned as the network changes. Many operational affect reference signal received power (RSRP), quality (RSRQ), signal-to-interference-plus-noise-ratio (SINR), and, ultimately, throughput. In this paper, we develop compare two approaches for maximizing coverage minimizing interference by jointly optimizing transmit downtilt (elevation tilt) settings across sectors. To evaluate different parameter...

Beam codebooks are a new feature of massive multiple-input multiple-output (M-MIMO) in 5G radio (NR). Codebooks comprised beamforming vectors used to transmit reference signals and obtain limited channel state information (CSI) from receivers via the codeword index. This enables large arrays that cannot otherwise sufficient CSI. The performance, however, is by codebook design. In this paper, we show machine learning can be train site-specific for initial access. We design neural network...