scholarly journals Power Minimization Using Rate Splitting With Statistical CSI in Cloud-Radio Access Networks

2021 ◽  
Vol 2 ◽  
Author(s):  
Alaa Alameer Ahmad ◽  
Hayssam Dahrouj ◽  
Anas Chaaban ◽  
Tareq Y. Al-Naffouri ◽  
Aydin Sezgin ◽  
...  
Keyword(s):  
Mean Squared Error ◽  
Sample Average Approximation ◽  
Base Stations ◽  
Practical Case ◽  
Central Processor ◽  
Power Minimization ◽  
Estimation Errors ◽  
Minimum Mean Squared Error ◽  
Radio Access ◽  
Rate Splitting

Minimizing the power consumption in mobile communication networks while ensuring a minimum quality of service (QoS) for applications is essential in light of the unprecedented expected increase in the number of connected devices and the associated data traffic beyond the fifth generation of wireless networks (B5G). This paper considers a cloud-radio access network (C-RAN) model where a central processor (CP) is connected to the base stations (BSs) via limited capacity fronthaul links. In the context of our C-RAN setting, we consider the practical case where the CP has only statistical knowledge of channel state information (CSI). While conventional wireless systems adopt the treating interference as noise (TIN) strategy to deal with the interference in the network, this paper instead considers that the CP applies the rate splitting (RS) strategy by dividing each user’s message into two parts: a private part to be decoded by the intended user only and a common part to be decoded by a subset of users, for the sole reason of interference mitigation in the network. To best account for the channel estimation errors, this paper addresses the problem of transmit power minimization under minimum QoS constraints on the achievable ergodic rate per user, so as to determine the beamforming vectors of the private and common messages as well as the rate allocated to all the users. The considered problem is of stochastic, complex, and non-convex nature. This paper addresses the problem intricacies through an iterative approach that leverages both the sample average approximation (SAA) technique and the weighted minimum mean squared error (WMMSE) algorithm to obtain a stationary point of the optimization problem in the asymptotic regime. The numerical results demonstrate the gain achieved with the RS strategy as compared to TIN, especially under high QoS requirements.

MIMO Precoding for Correlated Fading Channels

2016 ◽  
Vol 25 (05) ◽  
pp. 1650041
Author(s):  
Bruno Felipe Costa ◽  
Taufik Abrão
Keyword(s):  
Fading Channels ◽  
Mean Squared Error ◽  
Mimo System ◽  
Index Formula ◽  
Mimo Detection ◽  
Estimation Errors ◽  
Minimum Mean Squared Error ◽  
Correlated Fading ◽  
Correlated Fading Channels ◽  
The Impact

This contribution proposes a precoder-decoder design aiming to improve the performance of multiple-input–multiple-output (MIMO) detectors under correlated fading channels. The MIMO detection principle namely minimum mean squared error (MMSE) detector is analyzed under such channel condition. The proposed approach deploys the channel state information (CSI) aiming to estimate the level of spatial correlation channel, namely normalized correlation index [Formula: see text] and uses this information to improve the MIMO system performance. Furthermore, the impact of the [Formula: see text] estimation errors on the performance, as well the performance degradation for different levels of correlation have been analyzed and compared with the classical MMSE-MIMO detector operating under uncorrelated channels and perfect channel estimation.

Multi-AUV Aided Cooperative 3D-localization for Underwater Sensor Networks

2020 ◽  
Vol 13 (1) ◽  
pp. 80-90 ◽  
Author(s):  
Meiyan Zhang ◽  
Wenyu Cai
Keyword(s):  
Sensor Networks ◽  
Mean Squared Error ◽  
Autonomous Underwater Vehicles ◽  
Estimation Method ◽  
Location Estimation ◽  
Underwater Sensor Networks ◽  
Coverage Ratio ◽  
Minimum Mean Squared Error ◽  
3D Localization ◽  
Localization Scheme

Background: Effective 3D-localization in mobile underwater sensor networks is still an active research topic. Due to the sparse characteristic of underwater sensor networks, AUVs (Autonomous Underwater Vehicles) with precise positioning abilities will benefit cooperative localization. It has important significance to study accurate localization methods. Methods: In this paper, a cooperative and distributed 3D-localization algorithm for sparse underwater sensor networks is proposed. The proposed algorithm combines with the advantages of both recursive location estimation of reference nodes and the outstanding self-positioning ability of mobile AUV. Moreover, our design utilizes MMSE (Minimum Mean Squared Error) based recursive location estimation method in 2D horizontal plane projected from 3D region and then revises positions of un-localized sensor nodes through multiple measurements of Time of Arrival (ToA) with mobile AUVs. Results: Simulation results verify that the proposed cooperative 3D-localization scheme can improve performance in terms of localization coverage ratio, average localization error and localization confidence level. Conclusion: The research can improve localization accuracy and coverage ratio for whole underwater sensor networks.

scholarly journals Attack-resilient minimum mean-squared error estimation

2014 ◽  
Author(s):  
James Weimer ◽  
Nicola Bezzo ◽  
Miroslav Pajic ◽  
Oleg Sokolsky ◽  
Insup Lee
Keyword(s):  
Error Estimation ◽  
Mean Squared Error ◽  
Minimum Mean Squared Error ◽  
Squared Error

scholarly journals Location-Aided Uplink Transmission for User-Centric Cell-Free Massive MIMO Systems: A Fairness Priority Perspective

2022 ◽  
Author(s):  
Chen Wei ◽  
Kui Xu ◽  
Zhexian Shen ◽  
Xiaochen Xia ◽  
Wei Xie ◽  
...  
Keyword(s):  
Large Scale ◽  
Mean Squared Error ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Access Point ◽  
Estimation Accuracy ◽  
Minimum Mean Squared Error ◽  
Input Multiple Output ◽  
User Centric ◽  
Assignment Scheme

Abstract In this paper, we investigate the uplink transmission for user-centric cell-free massive multiple-input multiple-output (MIMO) systems. The largest-large-scale-fading-based access point (AP) selection method is adopted to achieve a user-centric operation. Under this user-centric framework, we propose a novel inter-cluster interference-based (IC-IB) pilot assignment scheme to alleviate pilot contamination. Considering the local characteristics of channel estimates and statistics, we propose a location-aided distributed uplink combining scheme based on a novel proposed metric representing inter-user interference to balance the relationship among the spectral efficiency (SE), user equipment (UE) fairness and complexity, in which the normalized local partial minimum mean-squared error (LP-MMSE) combining is adopted for some APs, while the normalized maximum ratio (MR) combining is adopted for the remaining APs. A new closed-form SE expression using the normalized MR combining is derived and a novel metric to indicate the UE fairness is also proposed. Moreover, the max-min fairness (MMF) power control algorithm is utilized to further ensure uniformly good service to the UEs. Simulation results demonstrate that the channel estimation accuracy of our proposed IC-IB pilot assignment scheme outperforms that of the conventional pilot assignment schemes. Furthermore, although the proposed location-aided uplink combining scheme is not always the best in terms of the per-UE SE, it can provide the more fairness among UEs and can achieve a good trade-off between the average SE and computational complexity.

scholarly journals Target and Equalizer Design for High-Density Bit-Patterned Media Recording

1970 ◽  
Vol 6 (2) ◽  
pp. 128-135
Author(s):  
Santi Koonkarnkhai ◽  
Phongsak Keeratiwintakorn ◽  
Piya Kovintavewat
Keyword(s):  
Partial Response ◽  
Mean Squared Error ◽  
Bit Patterned Media ◽  
Patterned Media ◽  
Media Noise ◽  
Minimum Mean Squared Error ◽  
Squared Error ◽  
Cross Track ◽  
Partial Response Maximum Likelihood ◽  
Better Than

In bit-patterned media recording (BPMR) channels, the inter-track interference (ITI) is extremely severe at ultra high areal densities, which significantly degrades the system performance. The partial-response maximum-likelihood (PRML) technique that uses an one-dimensional (1D) partial response target might not be able to cope with this severe ITI, especially in the presence of media noise and track mis-registration (TMR). This paper describes the target and equalizer design for highdensity BPMR channels. Specifically, we proposes a two-dimensional (2D) cross-track asymmetric target, based on a minimum mean-squared error (MMSE) approach, to combat media noise and TMR. Results indicate that the proposed 2D target performs better than the previously proposed 2D targets, especially when media noise and TMR is severe.

Joint Dimensioning of Outdoor Heterogeneous Radio Access Networks (HetNet) using Monte Carlo Simulation

MACRo 2015 ◽  
2015 ◽  
Vol 1 (1) ◽  
pp. 135-144
Author(s):  
Péter Ratkóczy ◽  
Attila Mitcsenkov
Keyword(s):  
Monte Carlo Simulation ◽  
Small Cell ◽  
Access Networks ◽  
Base Stations ◽  
Small Cells ◽  
Traffic Demand ◽  
Radio Access Networks ◽  
Traffic Capacity ◽  
Radio Access ◽  
Cell Densities

AbstractThe experienced mobile traffic increase in the recent years made traffic capacity the bottleneck instead of the coverage constraints, calling for significantly higher density of the base stations. Heterogeneous radio access networks (HetNet) provide a possible solution to this problem, combining various wireless technologies. In this paper we investigated the joint dimensioning of the co-existent radio access networks, the relation between the required macro and small cell densities to meet a certain traffic demand, and compared the two main, competing technological solutions, namely small cells and Wi-Fi, suitable to complement an LTE (macrocell) network.

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