I have a bunch of questions concerning Timing Advance in GSM :
When is it defined ?
Is it the phone or the BTS who's in charge of defining it's value ?
is it dynamic, does it depends on certain situations ?
Let's say that I figured out a way to get the exact value of the Timing Advance (GSM Layer 1 Transmission level) from the phone's modem :
In order to verify my solution, I'm supposed to put my phone over and over in a situation where he have to use/change the Timing Advance while I log its value...
How can I do that ?
Thanks
In the GSM cellular mobile phone standard, timing advance value corresponds to the length of time a signal takes to reach the base station from a mobile phone. GSM uses TDMA technology in the radio interface to share a single frequency between several users, assigning sequential timeslots to the individual users sharing a frequency. Each user transmits periodically for less than one-eighth of the time within one of the eight timeslots. Since the users are at various distances from the base station and radio waves travel at the finite speed of light, the precise arrival-time within the slot can be used by the base station to determine the distance to the mobile phone. The time at which the phone is allowed to transmit a burst of traffic within a timeslot must be adjusted accordingly to prevent collisions with adjacent users. Timing Advance (TA) is the variable controlling this adjustment.
Technical Specifications 3GPP TS 05.10[1] and TS 45.010[2] describe the TA value adjustment procedures. The TA value is normally between 0 and 63, with each step representing an advance of one bit period (approximately 3.69 microseconds). With radio waves travelling at about 300,000,000 metres per second (that is 300 metres per microsecond), one TA step then represents a change in round-trip distance (twice the propagation range) of about 1,100 metres. This means that the TA value changes for each 550-metre change in the range between a mobile and the base station. This limit of 63 × 550 metres is the maximum 35 kilometres that a device can be from a base station and is the upper bound on cell placement distance.
A continually adjusted TA value avoids interference to and from other users in adjacent timeslots, thereby minimizing data loss and maintaining Mobile QoS (call quality-of-service).
Timing Advance is significant for privacy and communications security, as its combination with other variables can allow GSM localization to find the device's position and tracking the mobile phone user. TA is also used to adjust transmission power in Space-division multiple access systems.
This limited the original range of a GSM cell site to 35km as mandated by the duration of the standard timeslots defined in the GSM specification. The maximum distance is given by the maximum time that the signal from the mobile/BTS needs to reach the receiver of the mobile/BTS on time to be successfully heard. At the air interface the delay between the transmission of the downlink (BTS) and the uplink (mobile) has an offset of 3 timeslots. Until now the mobile station has used a timing advance to compensate for the propagation delay as the distance to the BTS changes. The timing advance values are coded by 6 bits, which gives the theoretical maximum BTS/mobile separation as 35km.
By implementing the Extended Range feature, the BTS is able to receive the uplink signal in two adjacent timeslots instead of one. When the mobile station reaches its maximum timing advance, i.e. maximum range, the BTS expands its hearing window with an internal timing advance that gives the necessary time for the mobile to be heard by the BTS even from the extended distance. This extra advance is the duration of a single timeslot, a 156 bit period. This gives roughly 120 km range for a cell.[3] and is implemented in sparsely populated areas and to reach islands for example.
Hope this Answer the question:)
It's defined everytime the BTS needs to set the define the phone's transmission power, which happens quite often.
It's the core system (BTS in GSM) who totally in charge of defining it's value.
It's very dynamic, and change a lot. Globally, the GSM core system is constantly trying to find the exact distance between the BTS and the MS, so it constantly make a kind of "ping" to calculate it. The result of such operations is generally not that accurate since there are a lot of obstacles between the mobile and the BTS (it's not a direct link in an open space).
Such operations happens a lot, so use your smartphone. Simply.
Related
I'm wondering about a method to find an unknown frequency. I want to intercept the data from my hydro meter, but I don't know the exact frequency. I'm pretty sure it's in the range 902-928 MHz, but my rtlsdr only has a bandwidth of about 2 or 3 MHz. I'm new to radio stuff and signal processing, so I'm wondering how I hone in on the data. I read the meter also uses frequency hopping.
Ideally I'd like to setup my rtlsdr dongle to rotate on bands like so:
listen on 902 for an hour
listen on 904 for an hour
listen on 906 for an hour
...
listen on 928 for an hour
Then I want to only record something when there is a "blip" - this way I could take these recordings and analyze them.
Is there a better way?
Does your hydro meter have an FCC ID? If it has, then there's extensive documentation on the system on the FCC's website, including a detailed description which frequencies, bandwidths and powers the device uses, and possibly also which modulation.
Your meter probably works in an ISM band, meaning that unless you put everything in an RF-proof box, there will be a lot of stuff going through the ether around the frequencies you want to observer, so your 1h listening mode doesn't sound too promising. Also, there's no guarantee there's a "blip" – transmit power might be really low and spread out over a larger bandwidth (search for "spread spectrum" technology to understand how).
If observation is your best approach, I'd go for using gr-osmosdr and the osmocom_fft -W tool that comes with it.
I am working on a RFID project. The RFID tags that i am using are UHF whose frequency range is given i.e. 860-960 MHZ. How can i find the exact frequency on which a tag is working?. Does the value of frequency change with distance?. The only thing i have is RSSI, which i can measured from my equipment at any distance from the tag within the reading capacity of the reading.
Passive RFID tags do not select their frequency. It is completely determined by the reader generating a carrier signal. The 860-960 MHz range indicates it's a passive UHF tag. Depending on your physical location and regulatory requirements, the tag will respond at a single channel (frequency) within that band. Most tag readers report tag reads with optional meta data, such as the channel the tag was read on.
If the reader doesn't support this, you would need some advanced instrumentation to sniff the transaction. This can be accomplished with a filed probe, directional coupler + diode detector, or real time spectrum analyzer.
For reference, readers in the EU will operate at 865-868MHz and in NA at 902-928MHz.
I want to build a Javascript/HTML5 geolocation based social network and I wonder the best choice of possible architectures. Client-server can be simple to develop but drawback is the system ressources that could be very high, especially because the application must manage moves (worst case: a user that is in a car must see others users that are around him in cars).
Basicaly, in a client-server architecture, server tasks will be :
collects and stores latitude and longitude of the users (could have thousands of them)
makes geo distance search for that user (to get the list of users present around him in a radius)
builds and sends to the client an XML file with position of the users in the list
These 3 operation must be done periodically, every 3 or 5 seconds because I want a "live" map that shows users in the list moving in their environnement (city, town).
All these 3 points could be optimized :
client send his position when moving of 10 meters to reduce amount of data to process
"spherical rectangle" search in MyISAM table with spatial index (use of MBRContains) to off load MySQL database.
common output file : the XML that is sent can be the same if 2 users are located in a radius of x meters (the 2 users are close each-other).
It is hard to make load estimation at this stage but I think client-server architecture is not appropriate for that type of application and peer2peer could be a nice answer if 2 clients could communicate when they are near each other.
My point is:
Is there any methode to make possible a client to blind search other clients that are located in a certain radius without the help of a central server ? (it is possible with UDP broadcast :-)
edit : Correction. UDP Brodcast allow a client to poll a machine wherever it is, in certain range or IP address.
Thank you for your help,
Florent
You will have to have central peers/servers, because you need to centralize some information to be able to perform you functionalities.
I would go for the following:
Assign square miles (or whatever size you want) to specific servers.
Have devices send a 'I am here' message with their coordinates to some dispatcher that will forward these to the correct square mile server for handling.
Have servers register when a device enters a square mile they manage. This could be a central map to make sure a device is registered to one and only one square.
Forward this message to all other devices in the square.
And/or make sure you include to which square this message is intended and make sure the devices checks it before displays it to the user.
Tune the size of the square and the rate of 'I am here' message. That's it.
The answer actually depends on many things so I'll help out with basic strategy. To understand things out you'll need to understand how does Kademlia works (Kademlia is a DHT P2P network that stores information).
In Kademlia at first startup each node picks random ID which is a 160 bit number that represents point in a space of all possible 160 bit IDs.
The ID of the information that needs to be stored is obtained with SHA-1 function (it receives arbitrary string, and outputs 160 bit number that is treated like ID of the information that needs to be stored)
After that you have the ID of the information, you publish it, the information is physically stored on a node that has it's ID close to information ID.
(The illustration is taken from here)
The information is queried via it's ID. Both the information lookups or node lookups takes O(log(N)) hops to obtain the required information. The "XOR" metric is used in Kademlia (in your case it can be ordinary Euclidian metric).
Each node maintains an array of buckets, each bucket contains addresses of nodes that are appropriate to the current bucket. The appropriate'ness is a measure of how close the IDs are. consider example:
0 160
Node 1 ID: 1101000101011111101110101001010...
Node 2 ID: 1101011101011111101110101001010...
Node 3 ID: 1101000101011001101110101001010...
After applying XOR metric to Nodes #1,2 i.e (computing the number that represents the virtual distance between these nodes) we get:
index - 012345678901234
xor - 000001100000000... (the difference is in 5-th msb bit)
order - msb lsb
After applying Xor metric to Nodes #1,3 we get:
index - 012345678901234
xor - 000000000000011... (the difference is in 13-th msb bit)
order - msb lsb
Apparently Node 1 is closer to Node 3 since it has difference in less significant bits than the distance from Node 1 to Node 2. And therefore from a point of view of a Node 1, it's neighbor Node 3 goes to 13-th bucket(higher index means closer IDs), and Node 2 goes to to 5-th bucket which contains a group of nodes that are 5 MSB radixes away from a current node ID.
Such data structure allows each node to know it's surroundings in variety of 160 levels of distances.
Back to your example, to allow efficient geospacial queries you'll need to replace Kademlias XOR metric with ordinary Euclidian metric. In this case you will have your ID's as a 3D or 2D vectors, and unfortunately due to fact that Euclidian metric results with floating point numbers which are not directly suitable for this type of algorithm so you will need to convert them to a discrete binary numbers somehow in a way similar to what XOR function does. After that, finding node's neighboring nodes is a trivial task.
Hope this helps. Oh by the way look to HyperDex, new searchable distributed datastore closely tied to euclidian metric, might help...
Most people are limited to about 5 or 6 locations on a daily basis (work, home, school, store, etc). I want to speed up address display by caching a few of these most visited locations. I've been able to get the address info using both google maps GPS and JSON and Locator.reverseGeocode. What would be the best way to cache this information and to check proximity quickly? I found this GPS distance calculation example and have it working. Is there a faster way to check for proximity?
Please see similar question first: Optimization of a distance calculation function
There are several things we can change in distance calculations to improve performance:
Measure device speed and decrease or increase period of proximity test accordingly
Trigonometric calculations takes most of performence, but it may done much faster. First make bold distance calculations using lookup table method, then if distance is less than proximity limit + uncertainty limit, use CORDIC method for more precise calculation.
Use constants for Math.PI/180.0 and 180.0/Math.PI
several links that may be helpful:
Very useful explanations of CORDIC, especially doc from Parallax for dummies
Fast transcendent / trigonometric functions for Java
Cordic.java at Trac by Thomas B. Preusser
Cordic.java at seng440 proj
Sin/Cos look-up table source at processing.org by toxi
How does retiming work in systolic arrays (used in signal processors)? I read that there is some notion of negative delay which is used, but how can a delay be negative and if that is just an abstraction then how does it help?
The basic model of retiming is that you have wavefronts of registers interconnected by a bunch of combinational logic, and you are improving the timing or area of the resulting circuit by repositioning the registers at different points in the circuit such that every path through the logic still goes through the same number of registers. For a simple example, lets say that you have an AND gate feeding a register, the longest path to the input of the register is 12ns, the longest path from the output of the register is 6ns, the delay of the AND gate is 3ns, and you need to get the clock cycle time down to 10ns. You could achieve this by deleting the register and replacing it with two registers, one at each input of the AND gate, clocked by the same clock as the original register. Now you have reduced the longest input path to 9ns, expanded the output path to 9ns, and met your clock cycle objective. In effect, you have added -3ns to the effective arrival time at the register (and added +3 ns to the effective output time).
A modified version of Leiserson and Saxe's original paper on retiming is available here. Wikipedia has a decent, though short, article on the subject with a few links. If you have access to IEEE Xplore or the ACM Digital Library, a search through the proceedings of the Design Automation Conference or the International Conference on Computer-Aided Design looking for retiming should yield lots of articles - this has been an active research area for years.