Performance and Cramer–Rao Bounds for DoA/RSS Estimation and Transmitter Localization Using Sectorized Antennas

Werner, Janis; Wang, Jun; Hakkarainen, Aki; Čabrić, Danijela; Valkama, Mikko

doi:10.1109/tvt.2015.2445317

Cited by 66 publications

(41 citation statements)

References 24 publications

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“…An extended Kalman filter fused with the hybrid DoA and ToA is used in [226] for 5G localization. A similar technique is presented in [227] in case of a non-cooperative transmitter. 5G Network localization with the dense deployment of users is investigated in [225] using a variant of MDS i.e., Isomap.…”

Section: Mds Based Localization For Future 5gmentioning

confidence: 99%

A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques

Saeed

Nam

Al-Naffouri

et al. 2019

IEEE Commun. Surv. Tutorials

144

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Current and future wireless applications strongly rely on precise real-time localization. A number of applications such as smart cities, Internet of Things (IoT), medical services, automotive industry, underwater exploration, public safety, and military systems require reliable and accurate localization techniques. Generally, the most popular localization/ positioning system is the Global Positioning System (GPS). GPS works well for outdoor environments but fails in indoor and harsh environments. Therefore, a number of other wireless local localization techniques are developed based on terrestrial wireless networks, wireless sensor networks (WSNs) and wireless local area networks (WLANs). Also, there exist localization techniques which fuse two or more technologies to find out the location of the user, also called signal of opportunity based localization. Most of the localization techniques require ranging measurements such as time of arrival (ToA), time difference of arrival (TDoA), direction of arrival (DoA) and received signal strength (RSS). There are also range-free localization techniques which consider the proximity information and do not require the actual ranging measurements. Dimensionality reduction techniques are famous among the range free localization schemes. Multidimensional scaling (MDS) is one of the dimensionality reduction technique which has been used extensively in the recent past for wireless networks localization. In this paper, a comprehensive survey is presented for MDS and MDS based localization techniques in WSNs, Internet of Things (IoT), cognitive radio networks, and 5G networks. 2 MDS is much popular among all these techniques because of its simplicity and many application areas. MDS analysis finds the spatial map for objects given that the similarity or dissimilarity information between the objects is available [16].In the recent past, MDS is widely used for localization and mapping of wireless sensor networks (WSNs) and the internet of things (IoT). In [17] a proximity information based sensor network localization is proposed, where the main idea is to construct a local configuration of sensor nodes by using classical MDS (CMDS). The MDS based localization algorithms in [17] and [18] are centralized with higher computational complexity [7]. Semi-centralized (or clustered) MDS techniques are developed to compute local coordinates of nodes, which then are refined to find the final position of the nodes [19], [20]. In [21], [22] and [23] the authors proposed manifold learning to estimate the sensor nodes position in wireless sensor networks. In [24] the authors proposed Nystrom approximation for the proximity information matrix in MDS to reduce its size for better localization accuracy in sensor networks. Distributed MDS based localization algorithm is proposed in [25] with noisy range measurements, where the authors assume that the distances are corrupted with independent Gaussian random noise. MDS methods with different refinement schemes have also been proposed in the literature t...

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Section: Mds Based Localization For Future 5gmentioning

confidence: 99%

A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques

Saeed

Nam

Al-Naffouri

et al. 2019

IEEE Commun. Surv. Tutorials

144

View full text Add to dashboard Cite

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“…Assuming fixed µ k 's and T sen , the problem (P2) becomes convex with respect to P k . Therefore, the optimal P k 's that minimize (36) are the solutions to the Karush-Kuhn-Tucker (KKT) optimality necessary and sufficient conditions…”

Section: B Solving (P2)mentioning

confidence: 99%

“…where [x] + = max(x, 0). On the other hand, assuming fixed P k 's and T sen , the optimal µ k 's that minimize (36) are the solutions to ∂L/∂µ k = 0 for k = 1, . .…”

Section: B Solving (P2)mentioning

confidence: 99%

Beam Selection and Discrete Power Allocation in Opportunistic Cognitive Radio Systems With Limited Feedback Using ESPAR Antennas

Yazdani

Vosoughi

Gong

2020

IEEE Trans. Cogn. Commun. Netw.

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We consider an opportunistic cognitive radio (CR) system consisting of a primary user (PU), secondary transmitter (SUtx), and secondary receiver (SUrx), where SUtx is equipped with an electrically steerable parasitic array radiator (ESPAR) antenna with beam steering capability for sensing and communication, and there is a limited feedback channel from SUrx to SUtx. Taking a holistic approach, we develop a framework for integrated sector-based spectrum sensing and sector-based data communication. Upon sensing the channel busy, SUtx determines the beam corresponding to PU's orientation. Upon sensing the channel idle, SUtx transmits data to SUrx, using the selected beam corresponding to the strongest channel between SUtx and SUrx. We formulate a constrained optimization problem, where SUtx-SUrx link ergodic capacity is maximized, subject to average transmit power and interference constraints, and the optimization variables are sensing duration, thresholds of channel quantizer at SUrx, and transmit power levels at SUtx. Since this problem is non-convex we develop a suboptimal computationally efficient iterative algorithm to find the solution. Our numerical results quantify the capacity improvement provided by the ESPAR antenna and demonstrate that our CR system yields lower outage and symbol error probabilities, compared with a CR system that its SUtx has an omni-directional antenna.Index Terms-Beam selection, cognitive radio, constrained ergodic capacity maximization, discrete power allocation, ESPAR antenna, imperfect channel sensing, error-free bandwidth limited feedback channel, reconfigurable antennas.

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“…As in the case of known signal, here we insert P * s in (15), and thus the optimal φ and consequently optimal P s can be estimated by solving the following line-search problem,…”

Section: Propositionmentioning

confidence: 99%

“…The cornerstone of any spectrum cartography technique is a collaboration of sensors to estimate source parameters, e.g. location and power [9]- [15]. The authors of [9] employ sparse signal processing techniques to localize and estimate the power of multiple incumbent transmitters.…”

mentioning

confidence: 99%

Cooperative Estimation of Power and Direction of Transmission for a Directive Source

Maleki¹,

Ciblat²,

Chatzinotas³

et al. 2016

IEEE Trans. Cogn. Commun. Netw.

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Reliable spectrum cartography of directive sources depends on an accurate estimation of the direction of transmission (DoT) as well as the transmission power. Joint estimation of power and DoT of a directive source using ML estimation techniques is considered in this paper. We further analyze the parametric identifiability conditions of the problem, develop the estimation algorithm, and derive the Cramer-Rao-Bound (CRB) for the two situations: a) where the source signal is known to the sensors, and b) where the sensors are not aware of the source signal but its distribution. Particularly, we devise a specific sensor placement/selection setup for the symmetric antenna patterned sources which leads to identifiability of the problem. Finally, numerical results verifies the efficiency and accuracy of the provided estimation algorithms in this paper. Index TermsCooperative estimation, direction of transmission (DoT), power estimation, directive source, spectrum cartography, cognitive radio.

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Performance and Cramer–Rao Bounds for DoA/RSS Estimation and Transmitter Localization Using Sectorized Antennas

Cited by 66 publications

References 24 publications

A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques

A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques

Beam Selection and Discrete Power Allocation in Opportunistic Cognitive Radio Systems With Limited Feedback Using ESPAR Antennas

Cooperative Estimation of Power and Direction of Transmission for a Directive Source

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