A real-time DOA-based smart antenna processor

This paper presents a stochastic geometry-based model of the multiple-input-multiple-output channel, as seen by the user terminal based on the extraction of cluster parameters from wideband data measured at 1.9 GHz in short-range outdoor macrocellular environments. Clusters are first identified through data visual inspection. Then, a statistical characterization is carried out based on a delay-oriented classification of the clusters. Extraction results show that at each location, six to eight clusters are present, with average cluster delay and azimuth root mean square spreads of about 10-15 ns and 10 • -20 • , respectively. A cluster-oriented geometry-based model is then developed and validated with measurement results, including spatial correlations for broadside and inline receive antenna configurations.Index Terms-Clustering, multiple-input multiple-output (MIMO) channels, radio propagation, suburban areas, urban areas.

show abstract

“…The CAS is calculated in a similar way as the CDS, as outlined by the formal definition given in [13]. The cluster K-factor is estimated by [14] …”

Section: A Cluster Identificationmentioning

confidence: 99%

Modeling Outdoor Macrocellular Clusters Based on 1.9-GHz Experimental Data

Oestges

Clerckx

2007

IEEE Trans. Veh. Technol.

View full text Add to dashboard Cite

show abstract

“…The first type is the “Subspace Decomposition Based Algorithm” such as Multiple Signal Classification (MUSIC) [1,2] and Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) [3]. This type is the most widely used in practical systems [4,5] at present because its accuracy is acceptable in some cases and its computational complexity is low enough so that timeliness of the system can be guaranteed. In particular the ESPRIT can calculate the DOA explicitly.…”

Section: Introductionmentioning

confidence: 99%

A Novel Modification of PSO Algorithm for SML Estimation of DOA

Chen

Liu

et al. 2016

Sensors

View full text Add to dashboard Cite

This paper addresses the issue of reducing the computational complexity of Stochastic Maximum Likelihood (SML) estimation of Direction-of-Arrival (DOA). The SML algorithm is well-known for its high accuracy of DOA estimation in sensor array signal processing. However, its computational complexity is very high because the estimation of SML criteria is a multi-dimensional non-linear optimization problem. As a result, it is hard to apply the SML algorithm to real systems. The Particle Swarm Optimization (PSO) algorithm is considered as a rather efficient method for multi-dimensional non-linear optimization problems in DOA estimation. However, the conventional PSO algorithm suffers two defects, namely, too many particles and too many iteration times. Therefore, the computational complexity of SML estimation using conventional PSO algorithm is still a little high. To overcome these two defects and to reduce computational complexity further, this paper proposes a novel modification of the conventional PSO algorithm for SML estimation and we call it Joint-PSO algorithm. The core idea of the modification lies in that it uses the solution of Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) and stochastic Cramer-Rao bound (CRB) to determine a novel initialization space. Since this initialization space is already close to the solution of SML, fewer particles and fewer iteration times are needed. As a result, the computational complexity can be greatly reduced. In simulation, we compare the proposed algorithm with the conventional PSO algorithm, the classic Altering Minimization (AM) algorithm and Genetic algorithm (GA). Simulation results show that our proposed algorithm is one of the most efficient solving algorithms and it shows great potential for the application of SML in real systems.

show abstract

“…Multiple Signal Classfication (MUSIC) [13], [14] and Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) [15] have been widely employed in real systems [11], [12] for DOA estimation because the resolution of them are acceptable and the computational complexity are not so high. However, they cannot deal with coherent signals directly which happens for example in multipath propagations.…”

Section: Introductionmentioning

confidence: 99%

A Novel AWSF Algorithm for DOA Estimation in Virtual MIMO Systems

Chen¹,

Pan

Tian³

et al. 2013

IEEE J. Select. Areas Commun.

View full text Add to dashboard Cite

Both Multiple Input and Multiple Output (MIMO) and Smart Antenna (SA) have been widely accepted as promising schemes to improve the spectrum efficiency and coverage of mobile communication systems. This paper addresses the issue of Direction of Arrival (DOA) estimation in Virtual MIMO (VMIMO) systems which adopt SA simultaneously. First of all, we propose a VMIMO scheme for DOA estimation in which a set of User Equipments (UEs) are grouped together to simultaneously communicate with the Base Station (BS) on a given Resource Block (RB). In this scheme, the BS has multiple antennas and can estimate DOA of each UE in the group simultaneously. However, in practical environment because of reflection and refraction of signals, the received signals may be coherent. It is desirable that the DOA estimation in VMIMO could provide high resolution when the number of independent signals is unknown, which can not be achieved by existing algorithms. In order to solve this problem, we propose an Automatic Weighted Subspace Fitting (AWSF) algorithm that can detect the number of independent signals automatically and show accurate DOA estimation. Then with consideration of computational cost and sampling cost while using the AWSF algorithm, we propose a utility factor to determine the optimal number of UEs in VMIMO scheme, i.e., the order of VMIMO. Finally, the performance of the proposed AWSF algorithm and the efficiency of the utility factor criterion are demonstrated by simulations.

show abstract

A real-time DOA-based smart antenna processor

Cited by 73 publications

References 21 publications

Modeling Outdoor Macrocellular Clusters Based on 1.9-GHz Experimental Data

Modeling Outdoor Macrocellular Clusters Based on 1.9-GHz Experimental Data

A Novel Modification of PSO Algorithm for SML Estimation of DOA

A Novel AWSF Algorithm for DOA Estimation in Virtual MIMO Systems

Contact Info

Product

Resources

About