Time domain analysis of the received signal has also been used in the literature (example Moe Win) for cooperative localization.

"Time domain" does not only look to the total received power (RSSI),but it also it studies the relation between multipath competent of the received signal.

Check some articles from M. Win, example below:

Win, Moe Z., et al. "Network localization and navigation via cooperation." Communications Magazine, IEEE 49.5 (2011): 56-62.

You can also use sound signals.

To estimate the distance between two sensor nodes except RSSI , you can use other methods which have been widely used by the researchers like "time difference of arrival"(TDOA),  angle of arrival (AOA).  There are no of litterateurs available online on these techniques.

Thank you. 

Time of arrival (ToA) is another option, which uses the absolute time of arrival at a certain base station rather than the measured time difference between departing from one and arriving at the other station as in the case of TDOA. GPS uses ToA.

Response Time, Noise related parameters will be effective

you may further follow the link

http://www.sciencedirect.com/science/article/pii/S2090447913000695

Article A hybrid ACO/PSO based algorithm for QoS multicast routing problem

All the above techniques are true to measure the pseudo-range between two nodes. However, TOA technique needs clock synchronization between the two nodes. BTW I want to correct one thing, we can't measure the exact distance between two nodes, only we can measure the pseudo-range between the nodes.

Generally speaking, in literature, has been proved  that time-based techniques (TOA & TDOA) can achieve better location accuracy,  for node localisation, 

Time, angle, phase can be used to estimate the distance between the nodes. Nowadays, this time information is "easy" to obtain from the PHY layer.

If you can provide fine clock sync network or clique-wide, then you might want to use TOA or TDOA. Otherwise, protocols from the TWR family (TWR, SDS-TWR, SDS-TWR-MA, PDS-TWR) should do the trick.

Cheers!

Thanks everyone for your valuable suggestion. It really helps and also give me the realization of the goodness of such platform where we could collaborate our ideas. Thanks a lot.....

For certain models for the node placement, exact analytical expressions are available for the distance distributions. Here are two common ones:

For the binomial point process, see

S. Srinivasa and M. Haenggi, “Distance Distributions in Finite Uniformly Random Networks: Theory and Applications,” IEEE Transactions on Vehicular Technology, vol. 59, pp. 940-949, Feb. 2010.

For the Poisson point process, see

M. Haenggi, “On Distances in Uniformly Random Networks,” IEEE Transactions on Information Theory, vol. 51, pp. 3584-3586, Oct. 2005.

For example, in a two-dimensional uniform Poisson point process of intensity \lambda, the distance from a node to its nearest neighbor is Rayleigh distributed with mean 1/(2\sqrt{\lambda}).

You may take a look a paper written by Nouha Baccour, "Radio Link Quality Estimation in Wireless Sensor Network: a Survey", ACM Transactions on Sensor Networks (TOSN), Volume 8 Issue 4, September 2012 , Article No. 34.

you can also use location coordinates, it give less errors.

Outdoor localization system using RSSI Measurement of wireless sensor network by Oguejiofor, O.S in the International Journal of Innovative Technology and Exploring Engineering might be helpful.

Attached is a thesis that might also be helpful.

I suggest to make your question more concrete. It is not clear whether you want to measure the distance between nodes in a realistic network or just calculate the distance distribution in some random distribution. I am not familiar with the former. For the latter, I also suggest the papers of  Prof. Haenggi.

Please take a look on the following paper. 

Article Optimal Number of Relays in Cooperative Communication in Wir...

@Yin Chen: I want to measure the distance between nodes in a realistic sensor network ....

This is very good question,  Different parameters can be used to determine the distance between two nodes.

I hereby give two methods to measure the distance between two nodes.

No#1.

-Radio frequency [received signal strength indicator (RSSI)]

-Memory allocation

-Residual Energy of nodes.

No#2.

You know that the characteristic value for the power spectral density of

a received signal is the RSSI value. A receiver gets this value from the measured incoming signal strength and signal amplification of the receiver part.

You should know that electromagnetic waves drop the power while being propagated through the air. The waves will propagate in spherical form where radius ‘r’ of the sphere is the distance between receiver and transmitter. If antenna gain, transmitting power and frequency are known then following formula can be used to determine the distance between two nodes.

P_R=P_T (G_T G_R λ^2)/((4π)^2 r^n )

Where,

For the estimated power PR in dependence of gain of both antennas, GT and GR and wavelength λ;

n=2 for open space propagation.

In the second case,

The required parameters are antenna gain, transmitting power and frequency.

I will recommend you to read the following material that is helpful but especially focus on the work of Professor M.Haenggi

Article Distance Distributions in Finite Uniformly Random Networks: ...

Conference Paper Measuring the distance between wireless sensor nodes with st...

Please read attached paper for getting more idea regarding parameters.

Hi,

   You can use the following distance formula

The Euclidean distance between points p and q is the length of the line segment connecting them (\overline{\mathbf{p}\mathbf{q}}).

In Cartesian coordinates, if p = (p1, p2,..., pn) and q = (q1, q2,..., qn) are two points in Euclidean n-space, then the distance from p to q, or from q to p is given by:

\mathrm{d}(\mathbf{p},\mathbf{q}) = \mathrm{d}(\mathbf{q},\mathbf{p}) = \sqrt{(q_1-p_1)^2 + (q_2-p_2)^2 + \cdots + (q_n-p_n)^2} = \sqrt{\sum_{i=1}^n (q_i-p_i)^2}.

Here is a great article on this subject. 

http://www.moxa.com/newsletter/connection/2008/03/Figure_out_transmission_distance_from_wireless_device_specs.htm

Euclidean distance