Measurement clustering criteria for localization of multiple transmitters

Abstract

Abstract-We consider the problem of localizing multiple cochannel transmitters belonging to a licensed or primary network using signal strength measurements taken by a group of unlicensed or secondary nodes. Traditional localization techniques can be applied to multiple transmitter localization, provided that: (1) the total number of cochannel transmitters in the system is known, and (2) an appropriate set of clustered measurements is available. In this paper, we present two criteria to determine the total number of cochannel transmitters in the primary system. The first criterion is called the net MMSE criterion, which uses the Cramér-Rao lower bound on localization accuracy. The second criterion is the information theoretic criterion, minimum description length. Both of these criteria lead to measurement clustering algorithms in a natural way. Although we consider only signal strength measurements, the approach can be generalized to include other types of observations (e.g., time and angle information) with independent measurements in additive noise. Our numerical results demonstrate the effectiveness of the proposed approach to measurement clustering.

On whitespace identification using randomly deployed sensors

“…In Fig. 4, we plot the probability that the sum absolute error in localizing the transmitters is < (n), given by (4). We set (n) = log(n)/n, and compare the performance of three different scalings for r s : log(n)/n, (log(n)/n) 2 , and log(n)/n, for M = 1 and M = 4 transmitters.…”

“…One approach uses the receive signal strength (RSS) measurements obtained from the sensors to estimate the number of transmitters and their powers by minimizing the sum of the MSE in the location and power estimates [4]. The problem of localizing a transmitter using binary observations instead of using analog RSS measurements has also been considered [5]- [7].…”

On white-space detection, localization and coverage

“…For this purpose, typically, large number of sensors are deployed and a centralized decision is made about the transmitter location using sensor measurements. For example, receive signal strength (RSS) measurements obtained from the sensors are used to estimate the number of transmitters and their powers by minimizing the sum of the MSE in the location and power estimates in [4]. Binary observations, instead of analog RSS measurements, have also been used for determining the transmitter location [5], [6].…”

Multiple Transmitter Localization and Communication Footprint Identification Using Sparse Reconstruction Techniques

“…These works considered the transmit powers and number of transmitters to be known. In [3], the number of transmitters is estimated by minimizing the mean square error in location estimate and power estimate. All these above mentioned methods transmit the Receive Signal Strength (RSS) measurements to a central node prior to location estimation.…”