Patent Application
20080032628
The drawing includes the following Figures, which are not necessarily drawn to scale:
a and 11b show exemplary diagrams of the Universal Mobile Telecommunications System (UMTS) packet network architecture.
In
The present invention provides a new and unique technique for detecting in a wireless short-range communication device, such as, for example a WLAN STA the trend in received signal strength based on one or more characteristics, e.g. received signal strength values and current time of their observation, by fitting a generalized linear model to the values. Based on the detected trend, three things can be inferred by the WLAN STA:
1) WLAN radio coverage available for the STA is strengthening,
2) WLAN radio coverage available for the STA is stationary, or
3) WLAN radio coverage available for the STA is weakening
In operation, the technique includes receiving signals from a node, point or terminal (such as an access point (AP)) in the wireless local area network (WLAN); and estimating in the WLAN station (STA) the trend in the received signal strength values and the current time of their observation related to the received signals that can be utilized to predict the reliable threshold for performing a handover. In effect, given current time and signal strength, the technique can be utilized to predict the threshold for the handover (HO). It should be noted, however, that the same principles are applicable also to other suitable wireless short-range communication systems.
The techniques provided by the various embodiments of the present invention may also be used in relation to the extended service set (ESS) shown in
For the purpose of understanding the present invention, a basic description of the terms “roaming” and “handover” as they are understood in the art are set forth below:
In telecommunications, roaming may have at least three different meanings, depending on the context:
1. A general term in wireless telecommunications that refers to the extension of connectivity service in a network that is different than the network with which a station is currently registered.
2. The ability of a WLAN STA user to travel from one BSS to another, with complete communications continuity.
3. A term given for inter-network operability, that is, moving from one network provider to another (internationally).
In comparison, a handover (HO) is understood to be a basic mobile network capability for support of terminal migration. HO management is the process of initiating and ensuring a seamless and lossless transfer of a data link connection of a STA, from one AP (or, more commonly, base station) to another. Furthermore, HOs can be divided to:
For a WLAN HO, three separate scenarios are defined:
1. No-transition (STA is either static or mobile within a BSS),
2. an AP transition (handover from an AP to another (from BSS to another) within the same ESS), or
3. an ESS transition (STA HO from BSS to another where the BSSs belong to different ESSs).
By way of example,
1. WLAN radio coverage available for the STA is strengthening
2. WLAN radio coverage available for the STA is stationary
3. WLAN radio coverage available for the STA is weakening.
For example, the signal strength trend can be detected with an STA software (SW) implementation as follows:
1. From received MAC data frames, the received signal strength indication value (denoted here by yi) can be read (either the Received Signal Strength Indicator (RSSI) or the Received Channel Power Indicator (RCPI), both discussed below).
2. A time stamp (denoted here by xi) is attached for each received signal strength value;
3. A number (denoted here by M) of signal strength values are First In First Out (FIFO) buffered. This buffer is called herein the Median Buffer or M-Buffer;
4. The buffered data is median filtered, i.e. the M-Buffer is sorted and the median value is the filter output.
5. A number (denoted here by N) of median filtered data is FIFO buffered. This buffer is called the Estimator Buffer or E-Buffer herein.
6. For the data in the E-Buffer, the linear regression least square estimation fit is made and the linear fit parameters a0 and a1 are solved from a=(FTF)−1FTy.
7. The condition (the absolute value and sign) of the fitted line slope a1 is checked.
8. Based on the slope, three things can inferred:
Consistent with that described above, it is noted that the IEEE 802.11 standard defines a mechanism by which RF energy is to be measured by the circuitry on a wireless STA. This numeric value is an integer with an allowable range of 0-255 (a 1-byte value) called the Receive Signal Strength Indicator (RSSI). Presently, 256 actual measurements of different signal levels are not taken, but known 802.11 implementation to have a specific maximum RSSI value (“RSSI Max”).
Consistent with that described above, it is also noted that the RCPI indicator is a measure of the received RF power in the selected channel. This parameter shall be a measure by the PHY sublayer of the received RF power in the channel measured over the entire received frame. RCPI shall be a monotonically increasing, logarithmic function of the received power level defined in dBm. The allowed values for the Received Channel Power Indicator (RCPI) parameter may be an 8 bit value in the range from 0 through 220, with indicated values rounded to the nearest 0.5 dB, for example, as follows:
0: Power<−110 dBm
1: Power=−109.5 dBm
2: Power=−109.0 dBm
and so on where
RCPI=int{(Power in dBm+110)*2} for Odbm>Power>−110 dBm
220: Power>−0 dBm
221-254: Reserved
255: Measurement not available
Accuracy for each measurement shall be ±5 dB (95% confidence interval) within the specified dynamic range of the receiver. The measurement may assume a receiver noise equivalent bandwidth equal to the channel bandwidth multiplied by 1.1.
For the method according to the present invention, and consistent with that described above, one or more of the following parameters may be used:
a) Signal strength measurement interval,
b) The length of the median filtering buffer,
c) The length of the estimator buffer,
d) The type of linear regression model and the number of its parameters, the estimation is valid for general linear function f(x,a)=a1f1(x)+ . . . +anfn(x). in the examples of this IPR first order polynomial f(x)=a0+a1x is used but some other model type, e.g. higher order polynomial f(x)=a0+a1x + . . . +anxn could be considered as well,
e) The negative Slope (NS),
f) The positive Slope (PS),
g) The Link Loss Threshold,
h) Time needed for HO,
i) some combination thereof.
Let one denote a general linear function as f(x,a)=a1f1(x)+ . . . +anfn(x), where a is a function parameter and n is the degree of the function, and denote a set of given data points as (x1, y1), (x2, y2), . . . , (xN, yN) where y is the output and N is the number of data points. Now, minimizing the linear squares estimation function S(a)=Σi=1 . . . N(f(x1,a)−y1)2 yields to a normal equation which we mark as FTFa=FTy where i=1, . . . , N, and j=1, . . . , n. From the normal equation the function parameters a can be solved.
For the purpose of understanding the present invention, it is understood that a linear equation involves only the sum of constants or products of constants and the first power of a variable. Such an equation is equivalent to equating a first-degree polynomial to zero. A common form of a linear equation in two variables is f(x)=a0+a1x. In this form, the value a, will determine the slope or gradient of the line; and the value a0 will determine the point at which the line crosses the y-axis. For any two data points (x1, y1), (x2, y2) slope of the line can be calculated: a1=(y2−y1)/(x2−x1)=□y/□x.
Let one take an example for line fitting by least squares estimation, for data set of, as follows:
The minimization of the estimation function S(a) for the data set above yields to the following normal equation:
Solving the normal equation (a=(FTF)−1FTy) in terms of a gives us a linear estimate f(x)=2.445+0.3321x for the exemplary data set.
For the purposes of understanding various embodiments of the present invention, it is understood that median filtering is a simple, non-linear operation, where the value of the signal x(k), k=1, 2, . . . , N is replaced with the median of the values within a window of fixed length M=2m+1. The window length defines how many samples will be used at a time for determining the median. M and m are positive integers and M is always odd. The median is both the (m+1)th largest and (m+1)th smallest element of a sorted set. All the samples of the signal are filtered by sliding a filter of the length Mthrough the original set.
In equation form, median filtering can be presented as follows:
x
med(k)=MED[x(i)|x(i)∈{x(k−m), x(k−m+1), . . . , x(k), . . . , x(k+m)}]
In order to filter the ends of the set in an appropriate way we must add m values to both the beginning and the end of the original set. The values to be added may be either zeros or similar to the first and last value of the set (fixed end values). Using the mirror images of the beginning and end of the signal is also possible.
Median filtering will remove the short (less than m+1 of length) outliers (impulses) from the signal preserving the longer lasting step-like changes.
Experiments have produced an exemplary estimation curve with a handover estimation compared to received signal strength data that indicate that a really good estimation for the trend of the received signal strength can be created to avoid unnecessary reactions to signal level differences of particular packets while providing necessary information for predicting becoming handover and an estimation of time when the becoming handover will be imminent.
The various embodiments of the present invention provides at least following advantages to a wireless short-range communication capable terminal, such as, for example a WLAN STA:
1) The STA power consumption is reduced and latencies in data transfer are smaller when, based on trend detection information, unnecessary scanning required for HO can be avoided.
2) There is an increased possibility to successfully roam the data link either to another system (vertical HO) or to another WLAN BSS (horizontal HO). The detection of weakening radio coverage gives an STA more time to search for new candidate networks and have an estimation when the link for existing network is lost.
3) The radio coverage of a WLAN AP is better utilized because there is no need to set the threshold of roaming unnecessarily high to give time for HO. An STA can stay longer in one BSS (i.e. stationary in weak radio coverage) because, based on the trend (i.e. user movement), HO can be predicted faster and more accurately than before.
4) The WLAN signal quality is improved when trend detection information is utilized for the adaptation of data transfer bit rate. When WLAN coverage is strengthening the data transfer bit rate can be increased and vice versa.
If one assumes that the STA user is static within a BSA, and the measured signal strength varies between, say, −75 dBm and −85 dBm. However, the BER is still acceptable in these conditions, say, less than 10−5. Now, because the measurements are median filtered indicates less variation, say between −79 dBm and −81 dBm, and if the known link loss threshold is −90 dBm, the predicted link loss time is never less that the time needed for HO (say, 2 seconds) and the user can enjoy WLAN coverage further away from the AP that has been previously possible.
The STA user walks away from the AP she is currently connected to and the signal starts to degrade gradually. When the predicted link loss time is small enough ‘Link loss imminent’ indication is given and the HO is initiated in time to perform either horizontal or vertical HO. See, for example, that shown in
The functionality of the STA 30 described above may be implemented in the modules 32 and 34 shown in
The other module 36 and the functionality thereof are known in the art, do not form part of the underlying invention per se, and are not described in detail herein. For example, the other modules 36 may include other modules that formal part of a typical mobile telephone or terminal, such as a UMTS subscriber identity module (USIM) and mobile equipment (ME) module, which are known in the art and not described herein.
The interworking of the WLAN (IEEE 802.11) shown in
By way of example,
Accordingly, the invention comprises the features of construction, combination of elements, and arrangement of parts which will be exemplified in the construction hereinafter set forth.
It will thus be seen that the objects set forth above, and those made apparent from the preceding description, are efficiently attained and, since certain changes may be made in the above construction without departing from the scope of the invention, it is intended that all matter contained in the above description or shown in the accompanying drawing shall be interpreted as illustrative and not in a limiting sense.
