Location-Aided Pilot Contamination Elimination for Massive MIMO Systems

Muppirisetty, L. Srikar; Wymeersch, Henk; Karout, Johnny; Fodor, Gábor

doi:10.1109/glocom.2015.7417117

Cited by 20 publications

(19 citation statements)

References 16 publications

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“…For instance, in the physical layer, network processes that can be benefited include spatial spectrum sensing for cognitive radio and interference coordination in 5G, slow adaptive modulation and coding or channel estimation, beamforming, pilot decontamination in MIMO systems as described in [264], [265], and Channel State Information (CSI) estimation [266]- [269]. Medium Access Control (MAC) layer applications include resource scheduling algorithms (e.g., for frequency reuse), inter-cell interference coordination techniques, and multicasting algorithms.…”

Section: Technology Roadmap and Industry Trendsmentioning

confidence: 99%

A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation

Laoudias¹,

Moreira

Kim

et al. 2018

IEEE Commun. Surv. Tutorials

369

171

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Abstract-Location information for events, assets, and individuals, mostly focusing on two dimensions so far, has triggered a multitude of applications across different verticals, such as consumer, networking, industrial, health care, public safety, and emergency response use cases. To fully exploit the potential of location awareness and enable new advanced location-based services, localization algorithms need to be combined with complementary technologies including accurate height estimation, i.e., three dimensional location, reliable user mobility classification, and efficient indoor mapping solutions. This survey provides a comprehensive review of such enabling technologies. In particular, we present cellular localization systems including recent results on 5G localization, and solutions based on Wireless Local Area Networks (WLAN), highlighting those that are capable of computing 3D location in multi-floor indoor environments. We overview range-free localization schemes, which have been traditionally explored in Wireless Sensor Networks (WSN) and are nowadays gaining attention for several envisioned Internet of Things (IoT) applications. We also present user mobility estimation techniques, particularly those applicable in cellular networks, that can improve localization and tracking accuracy. Regarding the mapping of physical space inside buildings for aiding tracking and navigation applications, we study recent advances and focus on smartphone-based indoor Simultaneous Localization and Mapping (SLAM) approaches.The survey concludes with service availability and system scalability considerations, as well as security and privacy concerns in location architectures, discusses the technology roadmap, and identifies future research directions.

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Section: Technology Roadmap and Industry Trendsmentioning

confidence: 99%

A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation

Laoudias¹,

Moreira

Kim

et al. 2018

IEEE Commun. Surv. Tutorials

369

171

View full text Add to dashboard Cite

show abstract

“…In some scenarios, especially when the BS is elevated and seldom obstructed, propagation can be dominated by scatterers in the vicinity of the users, giving rise a limited AoA spread [26], [40]- [44], as assumed in this work. We note 1 The constant α depends on cell-edge signal-to-noise ratio (SNR), as specified in the numerical results.…”

Section: B Channel Modelmentioning

confidence: 99%

Location-Aided Pilot Contamination Avoidance for Massive MIMO Systems

Muppirisetty

Charalambous

Karout

et al. 2018

IEEE Trans. Wireless Commun.

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ilot contamination, defined as the interference during the channel estimation process due to reusing the same pilot sequences in neighboring cells, can severely degrade the performance of massive multiple-input multiple-output systems.ilot contamination, defined as the interference during the channel estimation process due to reusing the same pilot sequences in neighboring cells, can severely degrade the performance of massive multiple-input multiple-output systems.P In this paper, we propose a location-based approach to mitigating the pilot contamination problem for uplink multiple-input multiple-output systems. Our approach makes use of the approximate locations of mobile devices to provide good estimates of the channel statistics between the mobile devices and their corresponding base stations. Specifically, we aim at avoiding pilot contamination even when the number of base station antennas is not very large, and when multiple users from different cells, or even in the same cell, are assigned the same pilot sequence. First, we characterize a desired angular region of the target user at the serving base station based on the number of base station antennas and the location of the target user, and make the observation that in this region the interference is close to zero due to the spatial separability. Second, based on this observation, we propose pilot coordination methods for multi-user multi-cell scenarios to avoid pilot contamination. The numerical results indicate that the proposed pilot contamination avoidance schemes enhance the quality of the channel estimation and thereby improve the percell sum rate offered by target base stations.

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“…and ∆ ∈ R 3×L is a matrix in which the l-th column is given by a location-shift δ l and L is the number of components in which each channel vector h n is decomposed. This minimization problem is very difficult to solve since the terms in the summation (6) are given by the product of the variable β l and the non-convex functionã R (x, δ l |n) and, additionally, the solution may depend on the selection of L. In order to circumvent these challenges, we propose an indirect approach, in which we exploit the channel parametrization given in [9], [10] to generate a set of location images {x l }, withx l…”

Section: System Modelmentioning

confidence: 99%

“…[1] With 5G, the fifth-generation of mobile system [2], [3], there is a surge of interests towards location-awareness for mobile communications. In contrast to the past, new technologies such as millimeter-wave (mmWave) and three dimensional (3D) multiple-input and multiple-output (MIMO) quest for precise and real-time user-equipment (UE) location information for the development of highly directional [4] and dynamic beamforming [5], [6].…”

Section: Introductionmentioning

confidence: 99%

On the utilization of MIMO-OFDM channel sparsity for accurate positioning

Saloranta

Destino

2016

2016 24th European Signal Processing Conference (EUSIPCO)

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Recent results have revealed that MIMO channels at high carrier frequencies exhibit sparsity structure, i.e., a few dominant propagation paths. Also channel parameters, namely angular information and propagation delay can be modelled with the physical location of the transmitter, receiver and scatters. In this paper, we leverage these features into the development of a single base-station localization algorithm, and show that the location of an unknown device can be estimated with an accuracy below a meter based on pilot signalling with a OFDM transmission. The method relies on the utilization of the "Adaptive-LASSO" optimization method, in which an ℓ1based minimization problem is solved by adapting the sparsifying matrix (dictionary) and the sparse vector jointly. Then the location of the device is estimated from the parameters of the sparsifying matrix. Finally, the positioning method is evaluated in different channel setting utilizing a ray-tracing channel model at 28GHz.

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Location-Aided Pilot Contamination Elimination for Massive MIMO Systems

Cited by 20 publications

References 16 publications

A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation

A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation

Location-Aided Pilot Contamination Avoidance for Massive MIMO Systems

On the utilization of MIMO-OFDM channel sparsity for accurate positioning

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