Hi, I want to simulate an adaptive beamforming algorithm (using QR-RLS). From what I learned, I have the following thoughts and questions. Because I am not sure whether they are right or not (and the question is still unsolved), I want to get your answer to these. From �Adaptive Filter Theory� of Simon Haykin, 4th edition, Page 115, "The essence of a Wiener filter is that it minimizes the mean-square value of an estimation error, defined as the difference between a desired response and the actual filter out." The LS based algorithms are optimized in the least square sense (?). QR-RLS is one of LS algorithm, which has some adavantage in structure, accuracy, convergent speed, etc.. From some of the papers of QR-RLS I read, they are evaluated in a situation of known direction of the desired signal and the interferences. QR-RLS algorithm can adaptively suppress the interference signals at the same time enforce the desired signals from different antennas. The reference signal for the QR-RLS is the pilot PN binary sequences, i.e., in the time domain. I want to do a similar simulation with the desired and interference signals known their directions (There are 4 antennas to receive these signals). My question is: how can I design the signal source model with the intended directions? I have been thinking for quite a while. Could you help me? Any suggestion is highly appreciated.

# Questions about QR-RLS algorithm and antenna beamforming

Started by ●January 6, 2004

Reply by ●January 6, 20042004-01-06

"Jeff" <freelait2000@yahoo.com> wrote in message news:6cdef69d.0401060604.4e1f9c70@posting.google.com...> Hi, > I want to simulate an adaptive beamforming algorithm (using QR-RLS). > From what I learned, I have the following thoughts and questions. > Because I am not sure whether they are right or not (and the question > is still unsolved), I want to get your answer to these. > From �Adaptive Filter Theory� of Simon Haykin, 4th edition, Page 115, > "The essence of a Wiener filter is that it minimizes the mean-square > value of an estimation error, defined as the difference between a > desired response and the actual filter out." The LS based algorithms > are optimized in the least square sense (?). QR-RLS is one of LS > algorithm, which has some adavantage in structure, accuracy, > convergent speed, etc.. > From some of the papers of QR-RLS I read, they are evaluated in a > situation of known direction of the desired signal and the > interferences. QR-RLS algorithm can adaptively suppress the > interference signals at the same time enforce the desired signals from > different antennas. The reference signal for the QR-RLS is the pilot > PN binary sequences, i.e., in the time domain. I want to do a similar > simulation with the desired and interference signals known their > directions (There are 4 antennas to receive these signals). My > question is: how can I design the signal source model with the > intended directions? I have been thinking for quite a while. Could you > help me?If you already know the directions then the problem is deterministic and you can design an optimum array weighting to zero out the interfering sources - as long as there aren't too many of them. In this case, you appear to have amplitude and phase that can be adjusted for each antenna, is that right? I'd look for papers that adjust complex coefficients (i.e. amplitude and phase) to get optimum array patterns. The adaptive algorithms are good for situations where you don't know the direction of the interfering sources. Fred

Reply by ●January 6, 20042004-01-06

Fred Marshall wrote:> "Jeff" <freelait2000@yahoo.com> wrote in message > news:6cdef69d.0401060604.4e1f9c70@posting.google.com... > >>Hi, >>I want to simulate an adaptive beamforming algorithm (using QR-RLS). >>From what I learned, I have the following thoughts and questions. >>Because I am not sure whether they are right or not (and the question >>is still unsolved), I want to get your answer to these. >>From �Adaptive Filter Theory� of Simon Haykin, 4th edition, Page 115, >>"The essence of a Wiener filter is that it minimizes the mean-square >>value of an estimation error, defined as the difference between a >>desired response and the actual filter out." The LS based algorithms >>are optimized in the least square sense (?). QR-RLS is one of LS >>algorithm, which has some adavantage in structure, accuracy, >>convergent speed, etc.. >>From some of the papers of QR-RLS I read, they are evaluated in a >>situation of known direction of the desired signal and the >>interferences. QR-RLS algorithm can adaptively suppress the >>interference signals at the same time enforce the desired signals from >>different antennas. The reference signal for the QR-RLS is the pilot >>PN binary sequences, i.e., in the time domain. I want to do a similar >>simulation with the desired and interference signals known their >>directions (There are 4 antennas to receive these signals). My >>question is: how can I design the signal source model with the >>intended directions? I have been thinking for quite a while. Could you >>help me? > > > If you already know the directions then the problem is deterministic and you > can design an optimum array weighting to zero out the interfering sources - > as long as there aren't too many of them. In this case, you appear to have > amplitude and phase that can be adjusted for each antenna, is that right? > I'd look for papers that adjust complex coefficients (i.e. amplitude and > phase) to get optimum array patterns. > > The adaptive algorithms are good for situations where you don't know the > direction of the interfering sources.But they suck if you don't know the directions of the desired signals.> > Fred > >

Reply by ●January 6, 20042004-01-06

"Stan Pawlukiewicz" <stanp@nospam_mitre.org> wrote in message news:btet0l$eid$1@newslocal.mitre.org...> Fred Marshall wrote: > > "Jeff" <freelait2000@yahoo.com> wrote in message > > news:6cdef69d.0401060604.4e1f9c70@posting.google.com... > > > >>Hi, > >>I want to simulate an adaptive beamforming algorithm (using QR-RLS). > >>From what I learned, I have the following thoughts and questions. > >>Because I am not sure whether they are right or not (and the question > >>is still unsolved), I want to get your answer to these. > >>From �Adaptive Filter Theory� of Simon Haykin, 4th edition, Page 115, > >>"The essence of a Wiener filter is that it minimizes the mean-square > >>value of an estimation error, defined as the difference between a > >>desired response and the actual filter out." The LS based algorithms > >>are optimized in the least square sense (?). QR-RLS is one of LS > >>algorithm, which has some adavantage in structure, accuracy, > >>convergent speed, etc.. > >>From some of the papers of QR-RLS I read, they are evaluated in a > >>situation of known direction of the desired signal and the > >>interferences. QR-RLS algorithm can adaptively suppress the > >>interference signals at the same time enforce the desired signals from > >>different antennas. The reference signal for the QR-RLS is the pilot > >>PN binary sequences, i.e., in the time domain. I want to do a similar > >>simulation with the desired and interference signals known their > >>directions (There are 4 antennas to receive these signals). My > >>question is: how can I design the signal source model with the > >>intended directions? I have been thinking for quite a while. Could you > >>help me? > > > > > > If you already know the directions then the problem is deterministic andyou> > can design an optimum array weighting to zero out the interferingsources -> > as long as there aren't too many of them. In this case, you appear tohave> > amplitude and phase that can be adjusted for each antenna, is thatright?> > I'd look for papers that adjust complex coefficients (i.e. amplitude and > > phase) to get optimum array patterns. > > > > The adaptive algorithms are good for situations where you don't know the > > direction of the interfering sources. > > But they suck if you don't know the directions of the desired signals.Good point Stan. That was an unstated assumption. I guess if the antenna array is always physically aimed (rotated) at the desired source always then this is a contraint on the main lobe as is often the case. Fred