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v2009.01.01 - Convex Optimization

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5.4. EDM DEFINITION 375<br />

by translated ellipsoids of graduated orientation and eccentricity as in<br />

Figure 102.<br />

Depicted in Figure 101 is one cell phone x 1 whose signal power is<br />

automatically and repeatedly measured by 6 base stations ◦ nearby. 5.17<br />

Those signal power measurements are transmitted from that cell phone to<br />

base station ˇx 2 who decides whether to transfer (hand-off or hand-over)<br />

responsibility for that call should the user roam outside its cell. 5.18<br />

Due to noise, at least one distance measurement more than the minimum<br />

number of measurements is required for reliable localization in practice;<br />

3 measurements are minimum in two dimensions, 4 in three. 5.19 Existence<br />

of noise precludes measured distance from the input data. We instead assign<br />

measured distance to a range estimate specified by individual upper and<br />

lower bounds: d i1 is the upper bound on distance-square from the cell phone<br />

to i th base station, while d i1 is the lower bound. These bounds become the<br />

input data. Each measurement range is presumed different from the others.<br />

Then convex problem (841) takes the form:<br />

minimize trG<br />

G∈S 7 , X∈R2×7 subject to d i1 ≤ tr(GΦ i1 ) ≤ d i1 , i = 2... 7<br />

tr ( )<br />

Ge i e T i = ‖ˇx i ‖ 2 , i = 2... 7<br />

tr(G(e i e T j + e j e T i )/2) = ˇx T i ˇx j , 2 ≤ i < j = 3... 7<br />

X(:, 2:7) = [ ˇx 2 ˇx 3 ˇx 4 ˇx 5 ˇx 6 ˇx 7 ]<br />

[ ] I X<br />

X T<br />

≽ 0 (851)<br />

G<br />

where<br />

Φ ij = (e i − e j )(e i − e j ) T ∈ S N + (796)<br />

5.17 Cell phone signal power is typically encoded logarithmically with 1-decibel increment<br />

and 64-decibel dynamic range.<br />

5.18 Because distance to base station is quite difficult to infer from signal power<br />

measurements in an urban environment, localization of a particular cell phone • by<br />

distance geometry would be far easier were the whole cellular system instead conceived so<br />

cell phone x 1 also transmits (to base station ˇx 2 ) its signal power as received by all other<br />

cell phones within range.<br />

5.19 In Example 4.4.1.2.2, we explore how this convex optimization algorithm fares in the<br />

face of measurement noise.

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