Advanced signal processors for interference cancellation in baseband receivers

Information

  • Patent Grant
  • 10050733
  • Patent Number
    10,050,733
  • Date Filed
    Tuesday, October 27, 2015
    9 years ago
  • Date Issued
    Tuesday, August 14, 2018
    6 years ago
Abstract
An interference canceller comprises a composite interference vector (CIV) generator configured to produce a CIV by combining soft and/or hard estimates of interference, an interference-cancelling operator configured for generating a soft projection operator, and a soft-projection canceller configured for performing a soft projection of the received baseband signal to output an interference-cancelled signal. Weights used in the soft-projection operator are selected to maximize a post-processing SINR.
Description
BACKGROUND

1. Field of the Invention


The present invention relates generally to interference cancellation in received wireless communication signals and, more particularly, to forming and using a composite interference signal for interference cancellation.


2. Discussion of the Related Art


In an exemplary wireless multiple-access system, a communication resource is divided into subchannels and allocated to different users. For example, subchannels may include time slots, frequency slots, multiple-access codes, spatio-temporal subchannels, or any combination thereof. A plurality of sub-channel signals received by a wireless terminal (e.g., a subscriber unit or a base station) may correspond to different users and/or different subchannels allocated to a particular user.


If a single transmitter broadcasts different messages to different receivers, such as a base station in a wireless communication system broadcasting to a plurality of mobile terminals, the channel resource is subdivided in order to distinguish between messages intended for each mobile. Thus, each mobile terminal, by knowing its allocated subchannel(s), may decode messages intended for it from the superposition of received signals. Similarly, a base station typically separates signals it receives into subchannels in order to differentiate between users.


In a multipath environment, received signals are superpositions of time delayed (and complex scaled) versions of the transmitted signals. Multipath can cause co-channel and cross-channel interference that correlates the allocated subchannels. For example, co-channel interference may occur when time-delayed reflections of transmitted signals from the same source interfere with each other. Cross-channel interference occurs when signals in a sub channel leak into and, thus, impair acquisition and tracking of other subchannels.


Co-channel and cross-channel interference can degrade communications by causing a receiver to incorrectly decode received transmissions, thus increasing a receiver's error floor. Interference may also have other degrading effects on communications. For example, uncancelled interference may diminish capacity of a communication system, decrease the region of coverage, and/or decrease maximum data rates. Previous interference-cancellation techniques include subtractive and projective interference cancellation, such as disclosed in U.S. Pat. Nos. 6,856,945 and 6,947,474, which are hereby incorporated by reference.


SUMMARY OF THE INVENTION

In view of the foregoing background, embodiments of the present invention may be employed in receivers configured to implement receive diversity and equalization. Embodiments may provide for optimally forming and using at least one composite interference vector (CIV) for use in any subtractive or projective interference canceller. Such embodiments may be employed in any receiver employing a Rake, such as (but not limited to) receivers configured to receive ultra-wideband (UWB), Code Division Multiple Access (CDMA), Multiple-Input/Multiple-Output (MIMO), and narrowband single-carrier signals. Embodiments of the invention may provide for analytically characterizing the signal-to-interference-and-noise ratio (SINR) in a composite signal or in a user subchannel, and choosing feedback terms (e.g., adaptive weights) to construct an interference-cancelled signal that maximizes this quantity.


Embodiments of the invention employ soft weighting of a projective operation to improve interference cancellation. For example, each finger of a Rake receiver is matched to a particular time delay and/or base station spreading code to combat the effects of frequency-selective fading and interference from multiple base stations, respectively. Inter-finger interference occurs due to loss of orthogonality in the user waveforms resulting from multi paths in the transmission channel. This interference may be mitigated by feeding soft estimates of active users' waveforms between the Rake fingers in order to improve the SINR at the output of each finger. The optimization is performed per Rake finger prior to combining. In a receiver employing receive diversity, fingers that are common to two or more receive paths may be combined using any of various well-known statistical signal-processing techniques.


In one embodiment of the invention, a means for generating one or more CIVs, a means for generating a soft-projection operator, and a means for performing a soft projection are configured to produce an interference-cancelled signal from a received baseband signal. The means for generating the one or more CIVs may include, by way of example, any means for deriving soft and/or hard estimates from a receiver and synthesizing the one or more CIVs therefrom. For example, the means for generating the one or more CIVs may include a symbol estimator (e.g., a symbol estimator in a receiver employing any combination of Rake processing, receive diversity, and equalization), a sub channel selector, a fast Walsh transform, and a PN coder. The means for generating the one or more CIVs may further include a channel emulator. The means for generating a soft-projection operator may include, by way of example, a soft-projection matrix generator or an interference-cancelling operator that includes a means for selecting a soft weight that maximizes a post-processing SINR. The means for performing a soft projection may include, by way of example, a signal processor configured to project a received baseband signal as specified by the soft-projection operator in order to produce an interference-cancelled signal.


Receivers and cancellation systems described herein may be employed in subscriber-side devices (e.g., cellular handsets, wireless modems, and consumer premises equipment) and/or server-side devices (e.g., cellular base stations, wireless access points, wireless routers, wireless relays, and repeaters). Chipsets for subscriber-side and/or server-side devices may be configured to perform at least some of the receiver and/or cancellation functionality of the embodiments described herein.


Various functional elements, separately or in combination, depicted in the figures may take the form of a microprocessor, digital signal processor, application specific integrated circuit, field programmable gate array, or other logic circuitry programmed or otherwise configured to operate as described herein. Accordingly, embodiments may take the form of programmable features executed by a common processor or discrete hardware unit.


These and other embodiments of the invention are described with respect to the figures and the following description of the preferred embodiments.





BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments according to the present invention are understood with reference to the flow diagram of FIG. 1 and the schematic block diagrams of FIGS. 2A and 2B.



FIG. 1 is a flow diagram of an interference-cancelling method for a particular multipath component.



FIG. 2A is a schematic block diagram of a circuit configured for cancelling interference and combining interference-cancelled multipath components.



FIG. 2B is a schematic block diagram of a circuit configured for cancelling interference from at least one finger of a Rake receiver that produces a CIV from signals received by all fingers of the Rake receiver.





DESCRIPTION OF THE PREFERRED EMBODIMENTS

The present invention will now be described more fully hereinafter with reference to the accompanying drawings, in which preferred embodiments of the invention are shown. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.


A received baseband signal at a user handset having K base stations (or subchannels)5 U users, L propagation paths, and a sequence of transmitted symbols {bk[m]} can be expressed by







y


[
n
]


=





k
=
1

K






m
=

-










l
=
1

L




c

k
,
l





s
k



[


n
-
Nm
-

d

k
,
l



,


b
k



[
m
]



]






+

v


[
n
]








where {sk[n, bk[m]]} is a discrete-time symbol-bearing waveform from base station k that has N samples per symbol period, the vector sequence {bk[m]} is a sequence of U user information symbols bk[m]=[bk,1[m], . . . , bk,U[m]] from base station k, the values Ck,1 and dk,l are the complex channel fading coefficients and the time delays characterizing the propagation channel linking the kth base station to the receiver, and v[n] is additive noise having power σ2. When a multi-code (e.g., CDMA, DSSS, WCDMA, DO) transmission is employed, a transmitted waveform can be represented as









s
k



[

n
,


b
k



[
m
]



]


=




u
=
1

u





b

k
,
u




[
m
]





w

k
,
u




[
n
]





,

mN

n
<


(

m
+
1

)


N







where U is the number of users, bk,u[m] is a user data symbol (which is drawn from a finite constellation and is constant over symbol intervals of sample length N), and wk,u[n] is a user spreading code (including PN, covering, and filtering), which is typically time varying at the sample rate. The sampling rate corresponding to n is taken to be the normalized rate 1 and assumed to be greater than the chip rate. The received signal y[n] may be organized into a sequence of vectors at rate 1/N










y


[
m
]


=




k
=
1

K






m







l
L




c

k
,
l





W

k
,
l




[

m
-

m



]





b
k



[

m


]







]

+

v


[
m
]



,





where bk contains symbols bk,u and the columns of the matrix Wk,l comprise vectors of the form

wk,l,u=[wk,l,u[mN−dl], . . . ,wk,l,u[(m+1)N−1−dl]]T

Thus, the sampling rate corresponding to m remains 1/N.


The optimal receiver for a given user information sequence depends on the cellular network's operating mode (e.g., soft handoff, blocking). For example, if a particular handset is not in handoff and there is no inter-base-station interference (i.e., K=1), the optimal detection strategy for a single symbol of interest corresponding to a designated user is








b
u



[
m
]


=

arg







max
b




max



{


b

u





[

m


]


}

:


b
u



[
m
]



=
b




Re




l





c
_

l




s
l
*



[

m
;

{

b


[

m


]


}


]




(


y


[
m
]


-


1
2



s


[


m
;

{

b


[

m


]


}


,
l

]




)












where overbar denotes a complex conjugate and superscript * denotes a Hermitian transpose. The term sl[m; {b[m′]}] is a received signal vector, delayed by dl corresponding to the vector-valued information sequence {b[m′]}, and the vector








s


[


m
;

{

b


[

m


]


}


,
l

]


=





l



l




c
l



,

s
l

,

[

m
;

{

b


[

m


]


}


]






represents an interference signal formed from all of the paths not equal to path l. This exemplary embodiment impels approximations that cancel interference terms sl[m; {b[m′]}] from received signals, in advance of Rake reception (i.e., the sum over l of clsl[m]. The vector sl[m; {b[m′]}] may be expressed as

sl[m;{b[m′]}]=[s[mN−dl,{b[m]}], . . . ,s[(m+1)N−1−dl,{b[m′]}]]


When the complex baseband signal y[m] is resolved at a particular (lth) finger in a handset's Rake receiver, it can be simplified to a vector representation

y=cxubu+xMAI+xINT+v

where y represents received data after it passes through a receiver pulse-shaping filter (e.g., a root raised-cosine pulse-shaping filter). The data y is time aligned to a particular path delay. The term c is a complex attenuation corresponding to the path.


When the modulation is linear, the term xu in path l, which represents a code waveform that typically includes an orthogonal basis code and an overlaid spreading sequence (e.g., a PN code) assigned to a user of interest, may be written as

x1,l,u[m]=c1,lw1,l,ub1,u[m]

The term W1,u is the spread and scrambled code for user u in cell k=1, and b1,u is an information symbol corresponding to the user of interest. The term xMAI is multiple access interference, and it may be expressed by








x

1
,
l
,
MAI




[
m
]


=


c
l







u



u





w

1
,
l
,
u






b

1
,
u




[
m
]


.









The term xINT may include inter-finger (and possibly inter-base-station) interference terms that are similar in form to xMAI. The term v is a vector of complex additive noise terms. Each of the vectors xu, xMAI, and xINT is a signal resolved onto a Rake finger matched to the lth multipath delay of base station k at symbol period m.


A conventional Rake receiver resolves the measurement xu onto a user's code vector to form the statistic xu*yl. Such statistics are typically derived from multiple Rake fingers and coherently combined across the paths via a maximum ratio combiner (i.e. they are weighted by the conjugate of the channel gains and summed). Alternatively, more general combining may be used.



FIG. 1 illustrates a signal processing method in accordance with an exemplary embodiment of the invention that is configured to reduce ISI in a received signal from a particular Rake finger. A CIV s is generated 101 by combining soft or hard estimates of interference corresponding to the other delays and/or base stations not tracked by the particular finger. For example, the soft estimates may correspond to interfering user subchannels from each base station tracked by a cellular handset. Soft or hard estimates may be derived from a conventional Rake receiver, an equalizer, or any detector matched to the communication protocol and channel conditions of a received signal. Embodiments of the invention may be configurable to operate within receivers employing receive diversity, equalization, transmit diversity combining, and/or space-time decoding.


Embodiments of the invention may include one or more CIVs. Therefore, in parts of the disclosure that describe a CIV, it is anticipated that a plurality of CIVs may be used. For example, specific embodiments may employ a matrix whose columns are CIVs. The CIV s is constructed from known and/or estimated active subchannels and then used to compute a soft projection matrix 102,

F(λ)=I−λss*.

The matrix F(λ) is configured to operate on a received data vector y 103 to produce an interference-cancelled signal ŷ=F(λ)y, which is coupled to a Rake processor or combiner (not shown). The term I is an identity matrix, and the weight λ may be determined symbol-by-symbol in order to maximize a post-processing SINR,







Γ


(
λ
)


=






x
u
*



F


(
λ
)




x
u




2



E






x
u
*



F


(
λ
)




x
MAI




2


+

E






x
u
*



F


(
λ
)




x
INT




2


+


σ
2



x
u
*



F


(
λ
)





F
*



(
λ
)




x
u









In this expression, each vector of the form xu is xu[m], corresponding to symbol period m. Therefore, the post-processing SINR Γ(λ) is measured symbol period-by-symbol period. The user powers are absorbed into the component vectors xu, xMAI, and xINT. These powers are known or estimated.


At each symbol period, the SINR at a given finger can be expressed as







Γ


(
λ
)


=


a
+

b





λ

+

c






λ
2




d
+

e





λ

+

f






λ
2









The coefficients are






a
=





x
u
*



x
u




2







b
=


-
2







x
u
*



x
u







x
u
*


s



2








c
=





x
u
*


s



4







d
=






u



u








x
u
*



x

u






2


+





x
u
*


s



2

+


σ
2



x
u
*



x
u









e
=


-
2







Re
(






u



u





(


x
u
*



x

u




)



(


x
u
*


s

)



(


s
*



x

u




)



+






x
u
*


s



2



s
*


s

+


σ
2







x
u
*


s



2



)








f
=






u



u









x
u
*


s



2







s
*



x

u






2



+






x
u
*


s



2







s
*


s



2


+


σ
2







x
u
*


s



2



(


s
*


s

)








wherein each of the inner products may be computed from the user codes wk[m] and complex amplitudes bl,u[m] identified for user u at baud interval m. If orthogonal spreading codes are used, the expression xu*xu with u′≠u is zero. Furthermore, the relevant inner product xu′*s can be efficiently obtained for a CDMA/WCDMA system by passing the synthesized CIV s for the finger of interest through a fast Walsh transform (FWT). Computing the soft projection matrix 102 may include a step of maximizing the SINR Γ(λ) by setting its derivative (with respect to λ) to zero (not shown), resulting in the following polynomial equation

(ce−bf2+2(cd−af)λ+(bd−ae)=0.

One of the roots of the polynomial equation corresponding to the maximum SINR is selected (not shown) and then used to scale ss* in the matrix F(λ). Once computed, F(λ)y may be scaled to conform to downstream processing in a baseband receiver.


It should be appreciated that variations to the previously described process for determining the weight λ may be made without departing from the spirit and scope of the claimed invention. For example, when a cellular handset is in a soft-handoff mode, there is an additional quadratic term in the numerator of Γ(λ) corresponding to the received signal power from the second base station, and there is one less term in the denominator. This changes the function Γ(λ), but it does not change the procedure for determining the value of Γ(λ) that maximizes Γ(λ). Furthermore, algorithms for maximizing Γ(λ) may be incorporated into other receiver processing techniques, such as (but not limited to) Rake path tracking, active user determination, amplitude estimation, receive diversity, and equalizing. Γ(λ) may be approximately maximized with variations or stochastic gradients.



FIG. 2A is a schematic block diagram of a circuit in accordance with an alternative embodiment of the invention that includes a CIV generator 201, an interference-cancelling operator 202, and a soft-projection canceller 203. Inputs to the CIV generator 201 and the soft-projection canceller 203 are coupled to outputs of a Rake receiver 200. An output of the soft-projection canceller 203 is coupled to the input of a combiner 210.


The soft-projection canceller 203 is configured to cancel interference from at least one path (or finger) of the Rake receiver 200. Soft and/or hard estimates from at least one other path or finger are processed by the CIV generator 201 to produce a CIVs. For example, FIG. 2B shows signals from rake fingers 210.1-210.N being used to construct a CIV in order to cancel interference from one of the rake fingers (e.g., 210.1). The interference-cancelling operator 202 uses the CIV s and user code xu to compute a soft-projection matrix. The soft-projection matrix computes the weight value λ that maximizes the SINR of the interference-cancelled signal ŷ=F(λ)y. The interference-cancelled signal 5 output from the soft-projection canceller 203 may be coupled into the combiner 210 and combined with interference-cancelled signals from other paths or Rake fingers.


The functions of the various elements shown in the drawings, including functional blocks, may be provided through the use of dedicated hardware, as well as hardware capable of executing software in association with appropriate software. When provided by a processor, the functions may be performed by a single dedicated processor, by a shared processor, or by a plurality of individual processors, some of which may be shared. Moreover, explicit use of the term “processor” should not be construed to refer exclusively to hardware capable of executing software, and may implicitly include, without limitation, digital signal processor DSP hardware, read-only memory (ROM) for storing software, random access memory (RAM), and non-volatile storage. Other hardware, conventional and/or custom, may also be included. Similarly, the function of any component or device described herein may be carried out through the operation of program logic, through dedicated logic, through the interaction of program control and dedicated logic, or even manually, the particular technique being selectable by the implementer as more specifically understood from the context.


The method and system embodiments described herein merely illustrate particular embodiments of the invention. It should be appreciated that those skilled in the art will be able to devise various arrangements, which, although not explicitly described or shown herein, embody the principles of the invention and are included within its spirit and scope. Furthermore, all examples and conditional language recited herein are intended to be only for pedagogical purposes to aid the reader in understanding the principles of the invention. This disclosure and its associated references are to be construed as applying without limitation to such specifically recited examples and conditions. Moreover, all statements herein reciting principles, aspects, and embodiments of the invention, as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Additionally, it is intended that such equivalents include currently known equivalents as well as equivalents developed in the future, i.e., any elements developed that perform the same function, regardless of structure.

Claims
  • 1. A method for cancelling interference from a received baseband signal, the method comprising: generating at least one composite interference vector (CIV) by combining estimates from interfering subchannels, wherein the estimates are derived from at least one of a Rake receiver, an equalizer, a receiver employing receive diversity, a receiver employing transmit diversity combining, or a receiver employing space-time decoding;generating a soft-projection matrix corresponding to the at least one CIV; andoperating on the received baseband signal using the soft-projection matrix to output an interference-cancelled signal.
  • 2. The method of claim 1, wherein: the generating at least one CIV comprises deriving the estimates from the Rake receiver; andeach finger of the Rake receiver is matched to at least one of a time delay or a base station spreading code.
  • 3. The method of claim 1, wherein the generating at least one CIV further comprises generating at least one or more soft estimates corresponding to interfering user subchannels from each base station tracked by a cellular handset.
  • 4. The method of claim 1, wherein the soft-projection matrix includes a weight that increases a post-processing signal-to-interference-plus-noise-ratio (SINR).
  • 5. The method of claim 1, wherein the operating on the received baseband signal further comprises coupling the interference-cancelled signal to at least one of a combiner or a Rake receiver.
  • 6. An apparatus for cancelling interference from a received baseband signal, comprising: at least one memory storing software; andat least one processor capable of executing the software to perform operations comprising: generating at least one composite interference vector (CIV) by combining estimates from interfering subchannels, wherein the estimates are derived from at least one of a Rake receiver, an equalizer, a receiver employing receive diversity, a receiver employing transmit diversity combining, or a receiver employing space-time decoding;generating a soft-projection matrix corresponding to the at least one CIV; andoperating on the received baseband signal using the soft-projection matrix to output an interference-cancelled signal.
  • 7. The apparatus of claim 6, wherein the at least one processor is capable of executing the software to perform operations comprising: the generating at least one CIV comprises deriving the estimates from the Rake receiver.
  • 8. The apparatus of claim 7, wherein each finger of the Rake receiver is matched to at least one of a time delay or a base station spreading code.
  • 9. The apparatus of claim 6, wherein the at least one processor is capable of executing the software to perform operations comprising: the generating at least one CIV further comprises generating at least one or more soft estimates corresponding to interfering user subchannels from each base station tracked by a cellular handset.
  • 10. The apparatus of claim 6, wherein the soft-projection matrix includes a weight that increases a post-processing signal-to-interference-plus-noise-ratio (SINR).
  • 11. The apparatus of claim 6, wherein the at least one processor is capable of executing the software to perform operations comprising: wherein the operating on the received baseband signal further comprises coupling the interference-cancelled signal to at least one of a combiner or a Rake receiver.
  • 12. At least one non-transitory computer-readable medium including software that, when executed by at least one processor, causes operations comprising: generating at least one composite interference vector (CIV) by combining estimates from interfering subchannels, wherein the estimates are derived from at least one of a Rake receiver, an equalizer, a receiver employing receive diversity, a receiver employing transmit diversity combining, or a receiver employing space-time decoding;generating a soft-projection matrix corresponding to the at least one CIV; andoperating on a received baseband signal using the soft-projection matrix to output an interference-cancelled signal.
  • 13. The at least one non-transitory computer-readable medium of claim 12 that includes software that, when executed by the at least one processor, causes further operations comprising: the generating at least one CIV comprises deriving the estimates from the Rake receiver.
  • 14. The at least one non-transitory computer-readable medium of claim 13, wherein each finger of the Rake receiver is matched to at least one of a time delay or a base station spreading code.
  • 15. The at least one non-transitory computer-readable medium of claim 12 that includes software that, when executed by the at least one processor, causes further operations comprising: the generating at least one CIV further comprises generating at least one or more soft estimates corresponding to interfering user subchannels from each base station tracked by a cellular handset.
  • 16. The at least one non-transitory computer-readable medium of claim 12, wherein the soft-projection matrix includes a weight that increases a post-processing signal-to-interference-plus-noise-ratio (SINR).
  • 17. The at least one non-transitory computer-readable medium of claim 12 that includes software that, when executed by the at least one processor, causes further operations comprising: wherein the operating on the received baseband signal further comprises coupling the interference-cancelled signal to at least one of a combiner or a Rake receiver.
CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No. 14/108,333, entitled “Advanced signal processors for Interference Cancellation in baseband receivers,” filed Dec. 16, 2013, which is a continuation of U.S. patent application Ser. No. 12/892,874, entitled “Advanced signal processors for Interference Cancellation in baseband receivers,” filed Sep. 28, 2010 and published as U.S. Patent Application Publication Number 2011-0019656 A1, which is a continuation of U.S. patent application Ser. No. 11/272,411, entitled “Variable interference cancellation technology for CDMA systems,” filed Nov. 10, 2005, now U.S. Pat. No. 7,808,937, which (1) is a continuation-in-part of U.S. patent application Ser. No. 11/233,636, entitled “Optimal feedback weighting for soft-decision cancellers,” filed Sep. 23, 2005 and published as U.S. Patent Application Publication Number 2006-0227909 A1. The entirety of each of the foregoing patents, patent applications, and patent application publications is incorporated by reference herein.

US Referenced Citations (251)
Number Name Date Kind
3742201 Groginsky Jun 1973 A
4088955 Baghdady May 1978 A
4309769 Taylor, Jr. Jan 1982 A
4359738 Lewis Nov 1982 A
4601046 Halpern et al. Jul 1986 A
4665401 Garrard et al. May 1987 A
4670885 Parl et al. Jun 1987 A
4713794 Byington et al. Dec 1987 A
4780885 Paul et al. Oct 1988 A
4856025 Takai Aug 1989 A
4893316 Janc et al. Jan 1990 A
4922506 McCallister et al. May 1990 A
4933639 Barker Jun 1990 A
4965732 Roy, III et al. Oct 1990 A
5017929 Tsuda May 1991 A
5099493 Zeger et al. Mar 1992 A
5105435 Stilwell Apr 1992 A
5109390 Gilhousen et al. Apr 1992 A
5119401 Tsujimoto Jun 1992 A
5136296 Roettger et al. Aug 1992 A
5151919 Dent Sep 1992 A
5218359 Minamisono Jun 1993 A
5218619 Dent Jun 1993 A
5220687 Ichikawa et al. Jun 1993 A
5224122 Bruckert Jun 1993 A
5237586 Bottomley Aug 1993 A
5263191 Kickerson Nov 1993 A
5280472 Gilhousen et al. Jan 1994 A
5305349 Dent Apr 1994 A
5325394 Bruckert Jun 1994 A
5343493 Karimullah Aug 1994 A
5343496 Honig et al. Aug 1994 A
5347535 Karasawa et al. Sep 1994 A
5353302 Bi Oct 1994 A
5377183 Dent Dec 1994 A
5386202 Cochran et al. Jan 1995 A
5390207 Fenton et al. Feb 1995 A
5394110 Mizoguchi Feb 1995 A
5396256 Chiba et al. Mar 1995 A
5423045 Kannan et al. Jun 1995 A
5437055 Wheatley, III Jul 1995 A
5440265 Cochran et al. Aug 1995 A
5448600 Lucas Sep 1995 A
5481570 Winters Jan 1996 A
5506865 Weaver, Jr. Apr 1996 A
5513176 Dean et al. Apr 1996 A
5533011 Dean et al. Jul 1996 A
5553098 Cochran et al. Sep 1996 A
5602833 Zehavi Feb 1997 A
5606560 Malek et al. Feb 1997 A
5621768 Lechleider Apr 1997 A
5644592 Divsalar et al. Jul 1997 A
5736964 Ghosh et al. Apr 1998 A
5761237 Petersen Jun 1998 A
5787130 Kotzin et al. Jul 1998 A
5812086 Bertiger et al. Sep 1998 A
5844521 Stephens et al. Dec 1998 A
5859613 Otto Jan 1999 A
5872540 Casabona et al. Feb 1999 A
5872776 Yang Feb 1999 A
5894500 Bruckert et al. Apr 1999 A
5926761 Reed et al. Jul 1999 A
5930229 Yoshida et al. Jul 1999 A
5953369 Suzuki Sep 1999 A
5978413 Bender Nov 1999 A
5995499 Hottinen et al. Nov 1999 A
6002727 Uesugi Dec 1999 A
6014373 Schilling et al. Jan 2000 A
6018317 Dogan et al. Jan 2000 A
6032056 Reudink Feb 2000 A
6067333 Kim et al. May 2000 A
6078611 La Rosa et al. Jun 2000 A
6088383 Suzuki et al. Jul 2000 A
6101385 Monte et al. Aug 2000 A
6104712 Robert et al. Aug 2000 A
6115409 Upadhyay et al. Sep 2000 A
6127973 Choi et al. Oct 2000 A
6131013 Bergstrom et al. Oct 2000 A
6137788 Sawahashi et al. Oct 2000 A
6141332 Lavean Oct 2000 A
6154443 Huang et al. Nov 2000 A
6157685 Tanaka et al. Dec 2000 A
6157842 Karlsson et al. Dec 2000 A
6157847 Buehrer et al. Dec 2000 A
6163696 Bi et al. Dec 2000 A
6166690 Lin et al. Dec 2000 A
6172969 Kawakami et al. Jan 2001 B1
6173008 Lee Jan 2001 B1
6175587 Madhow et al. Jan 2001 B1
6175588 Visotsky Jan 2001 B1
6177906 Petrus Jan 2001 B1
6185716 Riggle Feb 2001 B1
6192067 Toda et al. Feb 2001 B1
6201799 Huang et al. Mar 2001 B1
6215812 Young et al. Apr 2001 B1
6219376 Zhodzishsky et al. Apr 2001 B1
6222828 Ohlson et al. Apr 2001 B1
6230180 Mohamed May 2001 B1
6233229 Ranta et al. May 2001 B1
6233459 Sullivan et al. May 2001 B1
6240124 Wiedeman et al. May 2001 B1
6252535 Kober et al. Jun 2001 B1
6256336 Rademacher et al. Jul 2001 B1
6259688 Schilling et al. Jul 2001 B1
6263208 Chang et al. Jul 2001 B1
6266529 Chheda Jul 2001 B1
6269075 Tran Jul 2001 B1
6275186 Kong Aug 2001 B1
6278726 Mesecher et al. Aug 2001 B1
6282231 Norman et al. Aug 2001 B1
6282233 Yoshida Aug 2001 B1
6285316 Nir et al. Sep 2001 B1
6285319 Rose Sep 2001 B1
6285861 Bonaccorso et al. Sep 2001 B1
6295311 Sun Sep 2001 B1
6301289 Bejjani et al. Oct 2001 B1
6304618 Hafeez et al. Oct 2001 B1
6308072 Labedz et al. Oct 2001 B1
6310704 Dogan et al. Oct 2001 B1
6317453 Chang Nov 2001 B1
6321090 Soliman Nov 2001 B1
6324159 Mennekens et al. Nov 2001 B1
6327471 Song Dec 2001 B1
6330460 Wong et al. Dec 2001 B1
6333947 van Heeswyk et al. Dec 2001 B1
6351235 Stilp Feb 2002 B1
6351642 Corbett et al. Feb 2002 B1
6359874 Dent Mar 2002 B1
6362760 Kober et al. Mar 2002 B2
6363104 Bottomley Mar 2002 B1
6377607 Ling et al. Apr 2002 B1
6377636 Paulraj et al. Apr 2002 B1
6380879 Kober et al. Apr 2002 B2
6385264 Terasawa et al. May 2002 B1
6396804 Odenwalder May 2002 B2
6404760 Holtzman et al. Jun 2002 B1
6414949 Boulanger Jul 2002 B1
6430216 Kober Aug 2002 B1
6449246 Barton et al. Sep 2002 B1
6459693 Park et al. Oct 2002 B1
6466611 Bachu Oct 2002 B1
6501788 Wang et al. Dec 2002 B1
6515980 Bottomley Feb 2003 B1
6522683 Smee Feb 2003 B1
6570909 Kansakoski et al. May 2003 B1
6570919 Lee May 2003 B1
6574270 Madkour et al. Jun 2003 B1
6580771 Kenney Jun 2003 B2
6584115 Suzuki Jun 2003 B1
6590888 Ohshima Jul 2003 B1
6665349 Cherubini Dec 2003 B1
6668011 Li et al. Dec 2003 B1
6680727 Butler et al. Jan 2004 B2
6687723 Ding Feb 2004 B1
6690723 Gosse Feb 2004 B1
6711219 Thomas et al. Mar 2004 B2
6714585 Wang et al. Mar 2004 B1
6724809 Reznik Apr 2004 B2
6741634 Kim et al. May 2004 B1
6754340 Ding Jun 2004 B1
6798737 Dabak et al. Sep 2004 B1
6798850 Wedin et al. Sep 2004 B1
6801565 Bottomley et al. Oct 2004 B1
6829313 Xu Dec 2004 B1
6839390 Mills Jan 2005 B2
6882678 Kong et al. Apr 2005 B2
6912250 Adireddy Jun 2005 B1
6931052 Fuller Aug 2005 B2
6956893 Frank Oct 2005 B2
6963546 Misra Nov 2005 B2
6975666 Affes et al. Dec 2005 B2
6975669 Ling Dec 2005 B2
6975671 Sindhushayana Dec 2005 B2
7010073 Black et al. Mar 2006 B2
7027533 Abe et al. Apr 2006 B2
7200183 Olson et al. Apr 2007 B2
7245679 Aoki et al. Jul 2007 B2
7292623 Reznik Nov 2007 B2
7373128 Dowling May 2008 B2
7394879 Narayan et al. Jul 2008 B2
7397842 Bottomley et al. Jul 2008 B2
7430253 Olson et al. Sep 2008 B2
7440490 Kidiyarova-Shevchenko et al. Oct 2008 B2
7440492 Maruyama Oct 2008 B2
7463609 Scharf et al. Dec 2008 B2
7477710 Narayan Jan 2009 B2
7577186 Thomas et al. Aug 2009 B2
7733941 McCloud Jun 2010 B2
7808937 McCloud Oct 2010 B2
7876810 McCloud Jan 2011 B2
8005128 Lamba Aug 2011 B1
8090006 Narayan Jan 2012 B2
8121177 Narayan Feb 2012 B2
8654689 McCloud Feb 2014 B2
9172411 McCloud Oct 2015 B2
20010003443 Velazquez et al. Jun 2001 A1
20010020912 Naruse et al. Sep 2001 A1
20010021646 Antonucci et al. Sep 2001 A1
20010028677 Wang et al. Oct 2001 A1
20010046266 Rakib et al. Nov 2001 A1
20020001299 Petch et al. Jan 2002 A1
20020021747 Sequeira Feb 2002 A1
20020051433 Affes et al. May 2002 A1
20020060999 Ma May 2002 A1
20020131534 Ariyoshi Sep 2002 A1
20020154717 Shima Oct 2002 A1
20020172173 Schilling et al. Nov 2002 A1
20020176488 Kober Nov 2002 A1
20020186761 Corbaton et al. Dec 2002 A1
20020191676 O'Hagan Dec 2002 A1
20030035468 Corbaton et al. Feb 2003 A1
20030050020 Erceg et al. Mar 2003 A1
20030053524 Dent Mar 2003 A1
20030053526 Reznik Mar 2003 A1
20030092456 Dent May 2003 A1
20030095590 Fuller May 2003 A1
20030156630 Sriram Aug 2003 A1
20030198201 Ylitalo et al. Oct 2003 A1
20030202568 Choi et al. Oct 2003 A1
20030210667 Zhengdi Nov 2003 A1
20030219085 Endres Nov 2003 A1
20040008765 Chung Jan 2004 A1
20040013190 Jayaraman Jan 2004 A1
20040017867 Thomas et al. Jan 2004 A1
20040022302 Olson Feb 2004 A1
20040030534 Thomas Feb 2004 A1
20040136445 Olson et al. Jul 2004 A1
20040146093 Olson Jul 2004 A1
20040161065 Buckley Aug 2004 A1
20040190601 Papadimitriou Sep 2004 A1
20040196892 Reznik Oct 2004 A1
20040264552 Smee Dec 2004 A1
20050031060 Thomas Feb 2005 A1
20050084045 Stewart Apr 2005 A1
20050111566 Park et al. May 2005 A1
20050129107 Park Jun 2005 A1
20050163196 Currivan et al. Jul 2005 A1
20050180364 Nagarajan Aug 2005 A1
20050195889 Grant et al. Sep 2005 A1
20050201499 Jonsson Sep 2005 A1
20050223049 Regis Oct 2005 A1
20050243908 Heo Nov 2005 A1
20050259770 Chen Nov 2005 A1
20060013289 Hwang Jan 2006 A1
20060072654 Nielsen Apr 2006 A1
20060153283 Scharf Jul 2006 A1
20060227730 McCloud et al. Oct 2006 A1
20060227854 McCloud et al. Oct 2006 A1
20070041310 Tulino Feb 2007 A1
20110064172 Olson Mar 2011 A1
20110080923 McCloud Apr 2011 A1
Foreign Referenced Citations (11)
Number Date Country
4201439 Jul 1993 DE
4326843 Feb 1995 DE
4343959 Jun 1995 DE
0558910 Jan 1993 EP
0610989 Jan 1994 EP
1179891 Feb 2002 EP
2280575 Feb 1995 GB
2000-13360 Jan 2000 JP
WO 9312590 Jun 1995 WO
WO 2001089107 Nov 2001 WO
WO 02080432 Oct 2002 WO
Non-Patent Literature Citations (75)
Entry
G.M.A. Sessler, “Low Complexity Polynomial Expansion Multiuser Detector for CDMA Systems”, IEEE Trans. on Veh. Tech. 54(4), 1379-1391.
Preliminary Amendment submitted on Sep. 13, 2010, re U.S. Appl. No. 12/274,551. 7 pages.
Notice of Allowance and Fee(s) Due, dated Sep. 3, 2010, in re U.S. Appl. No. 12/426,083, includes Supplemental NOA and Information Disclosure Citation. 5 pages.
Information Disclosure Statement submitted May 1, 2011 re U.S. Appl. No. 11/233,636. 9 Pages.
Non-Final Office Action dated Jul. 31, 2008 for U.S. Appl. No. 11/100,935 for response dated Apr. 7, 2005, includes Notice of References Cited and Information Disclosure Statements. 56 pages.
Non-Final Office Action dated Jul. 31, 2008 for U.S. Appl. No. 11/100,935 dated Apr. 7, 2005, 42 pages.
B. Widrow, S. Stearns, “Adaptive Signal Processing”, Prentice Hall, Signal Processing Series, ISBN 0-13-004029-01, 1985.
G.M.A. Sessler, “Low Complexity Polynomial Expansion Multiuser Detector for CDMA Systems”, IEEE Trans. On Veh. Tech., vol. 54, No. 4, pp. 1379-1391, Jul. 2005.
Advisory Action Before the Filing of an Appeal Brief Office Action for reply filed Aug. 17, 2010, dated Sep. 1, 2010, in U.S. Appl. No. 11/266,928. 2 pages.
AFFES, Sofiene; Hansen, Henrik; and Mermelstein, Paul, “Interference Subspace Rejection: A Framework for Multiuser Detection in Wideband CDMA,” IEEE Journal on Selected Areas in Communications, vol. 20, No. 2, Feb. 2002. 16 pages.
Alexander, Paul D., Rasmussen, Lars K., and Schlegel, Christian B., “A Linear Receiver for Coded Multiuser CDMA,” IEEE transactions on Communications, vol. 45, No. 5, May 1997. 6 pages.
Behrens, Richard T. and Scharf, Louis I., “Signal Processing Applications of Oblique Projection Operators,” IEEE Transactions on Signal Processing, vol. 42, No. 6, Jun. 1994, pp. 1413-1424. 12 pages.
Behrens, Richard T. and Scharf, Louis L., “Parameter Estimation in the Presence of Low Rank Noise,” Proceedings of the Twenty-second Asilomar Conference on signals,systems and Computers, Pacific Grove, C.A,22ACSSC-12/88/0341, pp. 341-344, Maple Press, Nov. 1988. 4 pages.
Behrens, Richard T., “Subspace Signal Processing in Structured Noise,” UMI Dissertation Services, Ann Arbor, MI, US, Nov. 30, 1990. 117 pages.
Best, Roland E., “Phase-Locked Loops—Design, Simulation, and Applications,” 4th edition, McGraw-Hill, 1999. 23 pages.
Cheng, Unjeng, Hurd, William J., and Statman, Joseph I., “Spread-Spectrum Code Acquisition in the Presence of Doppler Shift and Data Modulation,” IEEE Transactions on Communications, vol. 38, No. 2, Feb. 1990. 10 pages.
Duel-Hallen, Alexandra, “Decorrelating Decision-Feedback Multiuser Detector for Synchronous Code-Division Multiple-Access Channel,” IEEE Transactions on Communications, vol. 41, No. 2, Feb. 1993. pp. 285-290. 6 pages.
Frankel et al., “High-performance photonic analogue-digital converter,” Electronic Letters, Dec. 4, 1997, vol. 33, No. 25, pp. 2096-2097. 2 pages.
Garg, Vijay K. and Wilkes, Joseph E., “Wireless and Personal Communications Systems,” Prentice Hall PTR, Upper Saddle River, NJ, US. 1996. 45 pages.
Halper, Christian; Heiss, Michael; and Brasseur, Georg, “Digital-to-Analog Conversion by Pulse-Count Modulation Methods,” IEEE Transactions on Instrumentation and Measurement, vol. 45, No. 4, Aug. 1996. 10 pages.
Iltis, Ronald A. and Mailaender, Laurence, “Multiuser Detection of Quasisynchronous CDMA Signals Using Linear Decorrelators,” IEEE Transactions on Communications, vol. 44, No. 11, Nov. 1996. 11 pages.
Jayaweera, Sudharman K. et al., “A RAKE-Based Iterative Receiver for Space-Time Block-Coded Multipath CDMA”, IEEE Transactions on Signal Processing, vol. 52, No. 3, Mar. 2004. 11 Pages.
Kaplan, Elliott D., Editor, “Understanding GPS—Principles and Applications,” Artech House, Norwood MA, US, 1996, pp. 152-236. (Provided publication missing pp. 83-151 of cited reference.) 46 pages.
Kohno, Ryuji, Imaj, Hideki, and Hatori, Mitsutoshi, “Cancellation techniques of Co-Channel Interference in Asynchronous Spread Spectrum Multiple Access Systems,” May 1983, vol. J 56-A, No. 5. 8 pages.
Lin, Kun; Zhao, Kan; Chui, Edmund; Krone, Andrew; and Nohrden, Jim; “Digital Filters for High Performance Audio Delta-sigma Analog-to-Digital and Digital-to-Analog Conversions,” Proceedings of ICSP 1996, Crystal Semiconductor Corporation, Austin, TX, US, pp. 59-63. 5 pages.
Lupas, Ruxandra and Verdu, Sergio, “Linear Multiuser Detectors for Synchronous Code-Division Multiple-Access Channels,” IEEE Transactions on Information Theory, vol. 35, No. 1, Jan. 1989. 14 pages.
Lupas, Ruxandra and Verdu, Sergio, “Near-Far Resistance of Multiuser Detectors in Asynchronous Channels,” IEEE transactions on Communications, vol. 38, No. 4, Apr. 1990. 13 pages.
Marinkovic, Slavica et al., “Space-Time Iterative and Multistage Receiver Structures for CDMA Mobile Communications Systems”, IEEE Journal on Selected Areas in Communications, vol. 19, No. 8, Aug. 2001. 11 Pages.
Mitra, Urbashi and Poor, H. Vincent, “Adaptive Decorrelating Detectors for CDMA Systems,” accepted for publication in the Wireless Communications Journal, accepted May 1995. 25 pages.
Mitra, Urbashi, and Poor, H. Vincent, “Adaptive Receiver Algorithms for Near-Far Resistant CDMA,” IEEE Transactions of Communications, vol. 43, No. 2/3/4, Feb./Mar./Apr. 1995. 12 pages.
Mohamed, Nermin A. et al., “A Low-Complexity Combined Antenna Array and Interference Cancellation DS-CDMA Receiver in Multipath Fading Channels”, IEEE Journal on Selected Areas in Communications, vol. 20, No. 2, Feb. 2002. 9 Pages.
Notice of Allowance and Fee(s) Due dated May 28, 2010 for U.S. Appl. No. 11/272,411. 7 pages.
Notice of Allowance and Fees Due dated Nov. 30, 2010 for U.S. Appl. No. 11/266,928 includes excerpt from Response to Final Office Action and Examiner's comments. 21 Pages.
Office Action dated May 6, 2007, dated Jun. 28, 2010, U.S. Appl. No. 11/266,928. 17 pages.
Ortega, J.G.; Janer, C.L.; Quero, J.M.; Franquelo, L.G.; Pinilla, J.; and Serrano, J., “Analog to Digital and Digital to Analog Conversion Based on Stochastic Logic,” IEEE 0-7803-3026-9/95, 1995. 5 pages.
PCT Notification of Transmittal of International Search Report and Written Opinion of International Searching Authority dated Sep. 21, 2007, re Int'l Application No. PCT/US 06/36018. 10 pages.
Price, et al., “A Communication Technique for Multipath Channels,” Proceedings to the IRE, vol. 46, The Institute of Radio Engineers, New York, NY, US, 1958. 16 pages.
Rappaport, Theodore S., Editor, “Wireless Communications—Principles & Practice,” Prentice Hall, Upper Saddle River, NJ, US, 1996, pp. 518-533. 14 pages.
Reply Brief dated Jul. 30, 2010 in U.S. Appl. No. 11/233,636. 22 pages.
Response dated Aug. 17, 2010 to the Final Office Action of Jun. 28, 2010, U.S. Appl. No. 11/266,928. 47 pages.
Response dated May 13, 2010 to final Office Action dated Apr. 19, 2010 U.S. Appl. No. 11/272,411 includes Terminal Disclaimer. 6 Pages.
Response dated May 6, 2010 to Non-Final Office Action dated Dec. 14, 2009 U.S. Appl. No. 11/266,928. 43 Pages.
Scharf, et al., “Matched Subspace Detectors,” IEEE Transactions on Signal Processing, vol. 42, No. 8, Aug. 1994. 12 pages.
Scharf, Louis L., “Statistical Signal Processing—Detection, Estimation, and Time Series Analysis,” Addison-Wesley Publishing Company, 1991, pp. 23-75 and 103-178. 74 pages.
Schlegel, C.B.; Xiang, Z-J.; and Roy, S., “Projection Receiver: A New Efficient Multi-User Detector,” IEEE 0-7803-2509-5/95, 1995. 5 pages.
Schlegel, Christian and Xiang, Zengjun, “A New Projection Receiver for Coded Synchronous Multi-User CDMA Systems,” Proceedings, 1995, IEEE International Symposium on Information Theory, p. 318, Sep. 17, 1995. 1 page.
Schlegel, Christian, Alexander, Paul and Roy, Sumit, “Coded Asynchronous CDMA and Its Efficient Detection,” IEEE Transactions on Information Theory, vol. 44, No. 7, Nov. 1998. 11 pages.
Schlegel, Christian; Roy, Sumit; Alexander, Paul D.; and Xiang, Zeng-Jun, “Multiuser Projection Receivers,” IEEE Journal on Selected Areas in Communications, vol. 14, No. 8, Oct. 1996. 9 pages.
Schneider, Kenneth S., “Optimum Detection of Code Division Multiplexed Signals,” IEEE Transactions on Aerospace and Electronic Systems, vol. AES-15, No. 1, Jan. 1979. 5 pages.
Stimson, George W., “An Introduction to Airborne Radar,” 2nd Edition, SciTech Publishing Inc., Mendham, NJ, US, 1998, pp. 163-176 and 473-491. 40 pages.
Thomas, John K., “Thesis for the Doctor of Philosophy Degree,” UMI Dissertation Services, Jun. 28, 1996. Ann Arbor, MI, US, 117 pages.
Verdu, Sergio, “Minimum Probability of Error for Asynchronous Gaussian Multiple-Access Channels,” IEEE Transactions on Information Theory, vol. IT-32, No. 1, Jan. 1986. 12 pages.
Viterbi, Andrew J., “CDMA—Principles of Spread Spectrum Communication,” Addison-Wesley Publishing Company, Reading, MA,US. 1995, pp. 11-75 and 179-233. 66 pages.
Viterbi, Andrew J., “Very Low Rate Convolutional Codes for Maximum Theoretical Performance of Spread-Spectrum Multiple-Access Channels,” IEEE Journal on Selected Areas in Communications, vol. 8, No. 4, May 1990. pp. 641-649, 9 pages.
Wang, Xiaodong et al., “Space-Time Multiuser Detection in Multipath CDMA Channels”, IEEE Transactions on Signal Processing, vol. 47, No. 9, Sep. 1999. 19 Pages.
Xie, Zhenhua; Short, Robert T. and Rushforth, Craig K., “A Family of Suboptimum Detectors for Coherent Multiuser Communications,” IEEE Journal on Selected Areas in Communications, vol. 8, No. 4, pp. 683-690, May 1990. 8 pages.
Zheng, Fu-Chun and Barton, Stephen K., “On the Performance of Near-Far Resistant CDMA Detectors in the Presence of Synchronization Errors,” IEEE Transactions on Communications, vol. 43, No. 12 (pp. 3037-3045), Dec. 1995. 9 pages.
B. Widrow, S. ‘Stearns Adaptive Signal Processing’, Prentice Hall, Signal Processing Series, 1985.
H. Yan et al, “ Parallel Interference Cancellation for Uplink Multirate Overlay CDMA channels”, IEEE Trans. Comm. V53,No. 1, Jan. 2005, pp. 152-161.
K. Hooli, et al, “Chip Level Channel Equalization in WCDMA Downlink”, EURASIP Journal on Applied Signal Processing 2002:8, pp. 757-770.
J. Winters, “Optimal Combining in Digital Mobile Radio with Co channel Interference”, IEEEE J. Selected Areas in Comm., V. SAC-2, No. 4, Jul. 1984, pp. 528-539.
M. Ali-Hackl, et. al, “Error Vector Magnitude as a Figure of Merit for CDMA Receiver Design”, The Fifth European Wireless Conference Feb. 24-27, 2004.
D. Athanasios et. al, “SNR Estimation Algorithms in AWGN for Hiper LAN/2 Transceiver”, MWCN 2005 Morocco, Sep. 19-21, 2005.
D. Divsalar, “Improved Parallel Interference Cancellation for CDMA”, IEEE Trans. Comm., V46, No. 2, Feb. 1998, pp. 258-268.
T.Lim, S.Roy, “Adaptive Filters in Multiuser (MU) CDMA detection,” Wireless Networks 4 (1998) pp. 307-318.
D.Guo,et. al, “A Matrix-Algebraic Approach to Linear Parallel Interference Cancellation in CDMA” IEEE Trans. Comm., V. 48, No. 1, Jan. 2000, pp. 152-161.
L. Rasmussen, et. al, “A Matrix-Algebraic Approach to Successive Interference Cancellation in CDMA” IEEE J. Selected Areas Comm. V. 48, No. 1, Jan. 2000, pp. 145-151.
D.Guo, et. al, “Linear Parallel Interference Cancellation in Long Code CDMA-Multiuser Detection” IEEE J. Selected Areas Comm. V.17, No. 12, Dec. 1999, pp. 2074-2081.
G. Xue, et. al, “Adaptive Multistage Parallel Interference Cancellation for CDMA” IEEE J. Selected Areas Comm. V.17, No. 10, Oct. 1999, pp. 1815-1827.
Y. Guo ,“Advance MIMO —CDMA receiver for Interference Suppression: Algorithms, Systems-on-Chips Architectures and Design Methodology,” Doctoral Thesis, Rice University, May 2005, pp. 165-180.
J. Robler, et. al, “Matched—Filter and MMSE Based Iterative Equalization with Soft Feedback, for QPSK Transmission”, International Zurich Seminar on Broadband Communication (IZS 2002) pp. 19-1-19-6, Feb. 2002.
H. Dai, et al, “Iterative Space—Time Processing for Multiuser Detection in Multipath CDMA Channels”, IEEE Trans. Signal Proc., V.50, No. 9, Sep. 2002, pp. 2116-2127.
A. Yener, et. al, “CDMA Multiuser Detection : A Non-Linear Programming Approach”, IEEE Trans. Comm., V. 50, No. 6, Jun. 2002, pp. 1016-1024.
A .Persson, et. al, “Time Frequency Localized CDMA for Downlink Multicarrier Systems”, 2002 7th Int. Symp. Spread Spectrum, V. 1, 2002, pp. 118-122.
G.M.A. Sessler, “Low Complexity Polynomial Expansion Multiuser Detector for CDMA Systems”, IEEE Trans. on Veh. Tech., 54(4), 1379-1391.
Related Publications (1)
Number Date Country
20160050041 A1 Feb 2016 US
Continuations (3)
Number Date Country
Parent 14108333 Dec 2013 US
Child 14924196 US
Parent 12892874 Sep 2010 US
Child 14108333 US
Parent 11272411 Nov 2005 US
Child 12892874 US
Continuation in Parts (1)
Number Date Country
Parent 11233636 Sep 2005 US
Child 11272411 US