This invention relates to an estimator of the throughput of a channel equalizer, a Minimum Mean Squared Error (MMSE) channel equalizer optimizer, method of optimizing the rank of a Minimum Mean Squared Error (MMSE) channel equalizer.
Referring to
A channel equalizer builds an adaptive model (R) of a communications channel (whose characteristics represent those of all the signal pathways between a base station and a receiver) and inverts the model to regenerate an originally transmitted signal (x) from a received signal (h). To calculate the coefficients of an MMSE equalizer, it is necessary to solve a linear system whose size is at least equal to the channel length. This can be done, for example, by inverting the received signal covariance matrix (whose size is equal to the channel delay spread). However, these channel inversion calculations may consume most of the resources of a digital signal processor (DSP) chip in a wireless receiver. A Minimum Mean Squared Error (MMSE) channel equalizer is an optimal linear equalizer in terms of mean squared error (MSE). To avoid the above problem, the coefficients of a reduced-rank MMSE equalizer can be calculated by inverting a matrix whose size is less than that of the covariance matrix. The size of the smaller matrix is known as the “rank”. With this approach, the length of the equalizer remains the same, but the number of degrees of freedom to be optimized is reduced. The performance of a channel equalizer is dependent on its rank (or number of optimized coefficients in its channel model R). Reduced-rank MMSE equalizers where studied by S. Chowdhury et al. (in Proc. 43rd IEEE Midwest Symp. on Circuits and Systems, 2000). In these receivers, the number of taps to be optimized is limited to D (D<N). This allows a reduction in complexity and in some cases accelerated convergence.
HSDPA (High-Speed Downlink Packet Access) is an evolution of the third generation mobile telecommunications protocol UMTS (Universal mobile telecommunication system) which can achieve data rates of up to 14 mega bits per second (Mbps). However, even with reduced-rank MMSE equalizers, the increased data rates of the HSDPA protocol are proving difficult to achieve. French Patent Application FR0105268 (and S. Burykh and K. Abed-Meraim, EURASIP Journal on Applied Signal Processing 12 (2002), pp. 1387-1400), describe a method of adapting the rank of a reduced-rank filter to attain a target Signal to Interference plus Noise Ratio (SINR) in “short” code CDMA. However, in data packet networks (like HSDPA) the measure of performance is throughput (not SINR) and the codes are not “short” because of the presence of a scrambling code.
In addition to the above problem, since throughput depends on the detection of many symbols of a same packet, the throughput will flatten after a certain rank (known as the limit rank). Beyond this point, further increases in rank produce no increases in throughput. Thus, even if SINR continues to increase, throughput does not. Referring to the example depicted in
According to the invention there is provided a an estimator of the throughput of a channel equalizer, a Minimum Mean Squared Error (MMSE) channel equalizer optimizer, method of optimizing the rank of a Minimum Mean Squared Error (MMSE) channel equalizer.
An embodiment of the invention is herein described by way of example only, with reference to the accompanying figures in which:
Referring to
More particularly, on receipt of a packet from the base station 38, the decoding component 36 (of the wireless receiver 32) attempts to decode the packet, and if successful, transmits a positive Acknowledge (ACK) message to the base station 38. Similarly, if the decoding component 36 is not successful, it transmits a Negative Acknowledge (NACK) message to the base station 38. Over a period of time and for a given data rate, it is clear that if no NACKs are received by the base station 38, then the throughput from the base station 38 to the wireless receiver 32, is at a maximum since all the packets transmitted by the base station 38 have been successfully decoded by a wireless receiver 32. Whereas, if the base station 38 receives only NACK messages, the throughput is zero since the wireless receiver 32 has not successfully decoded any packets. Thus, in between these two extremes, the throughput between a base station 38 and a wireless receiver 32 can be estimated from the number of NACKs (or the number of ACKs) received by the base station 38. Accordingly, the equalizer adaptor 30 is in communication with the decoding component 36 to receive the ACK/NACK messages transmitted to the base station 38. Depending on the statistics of the relative ratio of ACK to NACK messages, the equalizer adaptor 30 adapts the rank of the equalizer 34.
The equalizer adaptor 30 solves two problems, namely:
Problem 1: Determining the Minimum Rank to Attain a Target Throughput
Referring to
The pseudo-code for these operations is as follows:
This approach will allow a receiver to operate within the range 50%-60% of maximum throughput, while “minimizing” the equalizer rank (and thus the complexity)
It will also be recognised that the above optimisation procedure could also be implemented on the basis of the amount of time elapsed until a required number of ACK or NACK messages is received. In this case, the step of increasing or decreasing the equalizer rank is performed conditionally upon the elapsed time in question.
Problem 2: Determining the Limit Rank
Referring to
The rank of the equalizer is then increased 56 by a predefined amount and on further communication between the base station and wireless receiver, the equalizer adaptor receives further 58 ACK/NACK messages from the decoding component of the wireless receiver. The equalizer adaptor counts 60 the number of NACK and ACK messages received over a pre-defined number of CDMA slots and calculates 62 a second throughput of the equaliser therefrom.
The equalizer adaptor compares 64 the first and second throughputs. If a significant difference is found between the two throughputs, the rank of the equalizer is increased again 56 and the resulting throughput compared 64 against the previous throughput; and the rank of the equalizer incremented 56 again if substantial improvement in throughput is achieved. These steps of incrementing the rank of the equalizer and comparing the resulting throughputs of the equalizer based thereon are cyclically repeated until no further substantial increase in throughput is achieved 66 with increases in the rank of the equalizer.
The pseudo-code for this approach is as follows:
This approach will allow us to converge to the smallest rank giving the maximum throughput. More generally, the above approach enables the dynamic setting of the rank of the equalizer to avoid wasting computational resources of the wireless receiver, since the setting of this parameter is a key for balancing performance vs. consumption or vs. capabilities of the receiver. Further, it will be appreciated that the above operations of the equalizer adaptor are not incompatible with the prior art methods and could in fact be combined therewith.
It will be recognised that as in the previous optimisation procedure, the present procedure for determining the limit rank of an equaliser could also be implemented on the basis of the amount of time elapsed until a required number of ACK or NACK messages is received. In this case, the step of increasing or decreasing the equaliser rank is performed conditionally upon the elapsed time in question.
Modifications and alterations may be made to the above without departing from the scope of the invention.
Filing Document | Filing Date | Country | Kind | 371c Date |
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PCT/IB2007/051456 | 2/22/2007 | WO | 00 | 10/25/2010 |
Publishing Document | Publishing Date | Country | Kind |
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WO2008/102217 | 8/28/2008 | WO | A |
Number | Name | Date | Kind |
---|---|---|---|
7839940 | Borran et al. | Nov 2010 | B2 |
7944985 | ElGamal et al. | May 2011 | B2 |
7986680 | Kim et al. | Jul 2011 | B2 |
20030115331 | Xie et al. | Jun 2003 | A1 |
20050088959 | Kadous | Apr 2005 | A1 |
20060255989 | Kim et al. | Nov 2006 | A1 |
20070005749 | Sampath | Jan 2007 | A1 |
20070195738 | Kim | Aug 2007 | A1 |
20080037670 | Lee et al. | Feb 2008 | A1 |
Number | Date | Country |
---|---|---|
1542378 | Jun 2005 | EP |
2823922 | Oct 2002 | FR |
2006065181 | Dec 2004 | WO |
Number | Date | Country | |
---|---|---|---|
20110032919 A1 | Feb 2011 | US |