WO2015131314A1

WO2015131314A1 - Channel estimation in td-scdma

Info

Publication number: WO2015131314A1
Application number: PCT/CN2014/072804
Authority: WO
Inventors: Farrokh Abrishamkar; Jinghu Chen; Venkata Gautham CHAVALI; Mercader CABRERA; Hari Sankar; Insung Kang; Jilei Hou; Wanlun Zhao
Original assignee: Qualcomm Incorporated
Priority date: 2014-03-03
Filing date: 2014-03-03
Publication date: 2015-09-11

Abstract

Apparatus and methods for channel estimation in time division synchronous code division multiple access (TD-SCDMA), including determining least squares channel metric estimates based on a received signal that is received from one or more Node Bs, identifying signal taps and noise taps in a tapped delay line channel estimate based on at least one of temporal correlations and powers of the least squares channel metric estimates, and performing minimum mean square error scaling on the signal taps and the noise taps.

Description

CHANNEL ESTIMATION IN TD-SCDMA

BACKGROUND

[0001] Aspects of the present disclosure relate generally to wireless communication systems, and more particularly, to apparatus and methods for channel estimation in Time Division Synchronous Code Division Multiple Access (TD-SCDMA).

[0002] Wireless communication networks are widely deployed to provide various communication services such as telephony, video, data, messaging, broadcasts, and so on. Such networks, which are usually multiple access networks, support communications for multiple users by sharing the available network resources. One example of such a network is the UMTS Terrestrial Radio Access Network (UTRAN). The UTRAN is the radio access network (RAN) defined as a part of the Universal Mobile Telecommunications System (UMTS), a third generation (3G) mobile phone technology supported by the 3rd Generation Partnership Project (3GPP). The UMTS, which is the successor to Global System for Mobile Communications (GSM) technologies, currently supports various air interface standards, such as Wideband-Code Division Multiple Access (W-CDMA), Time Division-Code Division Multiple Access (TD-CDMA), and Time Division-Synchronous Code Division Multiple Access (TD- SCDMA). The UMTS also supports enhanced 3G data communications protocols, such as High Speed Packet Access (HSPA), which provides higher data transfer speeds and capacity to associated UMTS networks.

[0003] For mobile devices that receive signals according to TD-SCDMA, having accurate channel estimation ensures acceptable receiver performance, as channel estimation impacts, for example, demodulation, decode cell reselection, and TD- SCDMA protocol processing. Conventionally, channel estimation in TD-SCDMA includes linear least-squares followed by cleaning or tap identification.

[0004] As the demand for mobile broadband access continues to increase, research and development continue to advance the UMTS technologies not only to meet the growing demand for mobile broadband access, but to advance and enhance the user experience with mobile communications. Thus, in this case, improved channel estimation in TD- SCDMA is desired. SUMMARY

[0005] The following presents a simplified summary of one or more aspects in order to provide a basic understanding of such aspects. This summary is not an extensive overview of all contemplated aspects, and is intended to neither identify key or critical elements of all aspects nor delineate the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form as a prelude to the more detailed description that is presented later.

[0006] In one aspect, a method is provided for channel estimation in time division synchronous code division multiple access (TD-SCDMA), including determining least squares channel metric estimates based on a received signal that is received from one or more Node Bs, identifying signal taps and noise taps in a tapped delay line channel estimate based on at least one of temporal correlations and powers of the least squares channel metric estimates, and performing minimum mean square error scaling on the signal taps and the noise taps.

[0007] In another aspect, an apparatus for channel estimation in TD-SCDMA is provided that includes a processing system configured to determine least squares channel metric estimates based on a received signal that is received from one or more Node Bs, identify signal taps and noise taps in a tapped delay line channel estimate based on at least one of temporal correlations and powers of the least squares channel metric estimates, and perform minimum mean square error scaling on the signal taps and the noise taps.

[0008] In a further aspect, a computer program product for channel estimation in TD-

SCDMA is provided that includes a computer-readable medium including code for determining least squares channel metric estimates based on a received signal that is received from one or more Node Bs, code for identifying signal taps and noise taps in a tapped delay line channel estimate based on at least one of temporal correlations and powers of the least squares channel metric estimates, and code for performing minimum mean square error scaling on the signal taps and the noise taps.

[0009] In yet another aspect, an apparatus for channel estimation in TD-SCDMA is provided that includes means for determining least squares channel metric estimates based on a received signal that is received from one or more Node Bs; means for identifying signal taps and noise taps in a tapped delay line channel estimate based on at least one of temporal correlations and powers of the least squares channel metric estimates; and means for performing minimum mean square error scaling on the signal taps and the noise taps.

[0010] These and other aspects of the present disclosure will become more fully understood upon a review of the detailed description, which follows.

BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The disclosed aspects will hereinafter be described in conjunction with the appended drawings, provided to illustrate and not to limit the disclosed aspects, wherein like designations denote like elements, and in which:

[0012] FIG. 1 is a schematic block diagram of one aspect of a system for channel estimation in TD-SCDMA;

[0013] FIG. 2 is a block diagram illustrating a prior art example of channel estimation in aspects of the system of FIG. 1;

[0014] FIG. 3 is a block diagram illustrating an example channel estimation method in aspects of the system of FIG. 1;

[0015] FIG. 4 is a flowchart of an aspect of the methods of the system of FIG. 1;

[0016] FIG. 5 is a block diagram illustrating an example of a hardware implementation for an apparatus of FIG. 1 employing a processing system;

[0017] FIG. 6 is a block diagram conceptually illustrating an example of a telecommunications system including aspects of the system of FIG. 1;

[0018] FIG. 7 is a conceptual diagram illustrating an example of an access network including aspects of the system of FIG. 1; and

[0019] FIG. 8 is a block diagram conceptually illustrating an example of a Node B in communication with a UE in a telecommunications system, including aspects of the system of FIG. 1.

DETAILED DESCRIPTION

[0020] The detailed description set forth below in connection with the appended drawings is intended as a description of various configurations and is not intended to represent the only configurations in which the concepts described herein may be practiced. The detailed description includes specific details for the purpose of providing a thorough understanding of various concepts. However, it will be apparent to those skilled in the art that these concepts may be practiced without these specific details. In some instances, well known structures and components are shown in block diagram form in order to avoid obscuring such concepts.

[0021] Aspects of the present disclosure provide methods and apparatus for channel estimation in Time Division Synchronous Code Division Multiple Access (TD- SCDMA). In some aspects, channel estimation is enhanced at a user equipment (UE) operating in TD-SCDMA by using the temporal correlation and the power delay profile of the propagation channel to perform tap classification and estimate the delays and envelopes of the channel. In some aspects, based on the correlation and the power of the signal, tap classification is performed using power and/or temporal correlation filtering. In these aspects, the equivalent channel of a target Walsh code is estimated. In some further aspects, for example, for multiuser detection and/or interference cancellation, the equivalent channel of each active Walsh code is also estimated since, for example, the quality of the channel estimate of the target Walsh code depends on the quality of the channel estimation for other Walsh codes.

[0022] Referring to FIG. 1, in one aspect, system 1000 includes UE 1002 that is communicating signals 1001 with one or more Node Bs 1004 to estimate the downlink channel between Node Bs 1004 and UE 1002. UE 1002 includes channel estimation component 1006 that estimates the downlink TD-SCDMA channel from Node Bs 1004 by determining a channel estimate tapped delay line 1008 that includes signal taps 1010 and noise taps 1012, where signals taps 1010 correspond to the non-zero tap identifiers (IDs) within the channel estimate tapped delay line 1008.

[0023] Conventionally, in TD-SCDMA, the chip rate is 1.28 megachips per second

(Mcps) and the downlink time slot is 675 microseconds (μβ) or 874 chips. Table 1 shows an example configuration of chips in a TD-SCDMA downlink time slot.

Table 1

An example configuration of chips in a TD-SCDMA downlink time slot

As shown in Table 1, there are 144 chips in the midamble of a TD-SCDMA downlink time slot. The midambles are training sequences for channel estimation and power measurements at UE 1002. Each midamble can potentially have its own beamforming weights. Also, there is no offset between the power of the midamble and the total power of the associated channelization codes. The TD-SCDMA downlink time slot further includes 704 data chips and 16 guard period (GP) chips. The midambles (of length L_m = 144) used by different users in one cell in one time slot are cyclic shifted versions of one of the 128 basic midambles (of length P = 128). The number of cyclic shifts per cell may be J = 2, 4, 6, 8, 10, 12, 14, 16. In some aspects, in each sub-frame of 5 ms, there are 7 time slots, and the first time slot is denoted as TSO and uses J=8. The midambles are generated by rotating a basic midamble η¾> to obtain a complex midamble η¾>, cyclic extending η¾> to obtain K midambles of length L_m, and sampling to obtain J midambles per cell. For example, the midamble of the user (k = 1, K) may be obtained as:

where:

m(i) = m_p ( ), i = l, - - -, P

m(i) = m_p{i - P), i = P + \, · · ·, ί_ι max max L_m + (K-W

w P

K

The midamble allocation scheme for uplink and downlink may be, for example, a default scheme, a specific default scheme, a UE specific scheme, or a common scheme.

Conventionally, in TD-SCDMA, transmit data chips for user k in data state and with a spreading factor N=16 may be modeled as: u_k {n) = s(n mod N) w_k (n mod

n

p_k {n mod N)d_k

N where ¾ is the transmit chip for Walsh k (data chip or midamble, i.e., burst k), n is the chip index, s is the cell-specific scramble code, Wk Walsh code k, Pk is the channel code multiplier for Walsh k, d_k is the data symbol for Wash k, and p_k is the product of k-th Walsh multiplier, Walsh code, and scrambling code. Also, the transmitted data chips at the i-th transmit antenna t¹ are:

k=l i=l, ..., N_t

where N_t is the number of transmit antennas, K is the number of active Walsh codes, ο¾ is the beamforming weight of Walsh k at the i-th transmit antenna (||a_k|| = 1), and g_k is the gain of Walsh k. Assuming that there is only one receive antenna at UE 1002, the received signal r (n) at chip index n is:

where v is the channel memory, h¹ is the channel seen by the i-th antenna, and v(n) is additive white Gaussian noise (AWGN). The received signal may be re- written as:

N_t v K

r(n) =∑∑ ti (l)∑ a[g_ku_k (n - l) + v(n)

i=\ 1=0 k=l

K^v

=∑∑h_k (l)u_k (n - l) + v(n)

k=l 1=0

where the equivalent channel of the k-th user (after subsuming gain, beamforming, and propagation channel) is defined as: k (l) = g_k∑a[h l)

i=l

Assuming that the association between the Walsh codes and the midamble shifts is known, and the Walsh codes sharing the same midamble have the same beamforming and same gain, e.g., the Walsh codes using the same midamble have identical equivalent channels, the received signal model at midamble state is:

K v

r(n) =∑∑ K (l)u_k (« - /) + v(n)

k=l 1=0

=∑∑h~_j ^c (l)m_j (n - l) + v(n)

j=l 1=0 where m_j is the j-th midamble (e.g., shift) in the cell, J is the total of midamble shifts, S_j is the set of Walsh indices that map to midamble j, and the equivalent channel seen by j- th midamble is: ] (l) =∑h_k (l)

k≡S: In these aspects, a basic midamble of length 128 chips may be cyclically shifted to obtain a midamble shift, and the midamble signal may be one midamble or a sum of several midamble shifts from a basic midamble. As such, the equivalent channel seen by the k-th Walsh is:

where |S| is the cardinality of set S. Accordingly, the multi-cell signal model of the time domain received midamble sequence of M cells at UE 1002 is:

M

h_ = ILhL^c to ^T 5 l hi^c ii ^T ·> · · · 5 i hl^c iK-i ^TY J where y is the 128 x 1 vector of received midambles that is delayed such that the resulted channel impulse responses (CIRs) are double-sided and centered in the middle, M_j is the 128 x 128 circulant training matrix of the i-th cell, h _;h is the equivalent channel for the k^th shift and 1^th cell, and w is a 128 x 1 complex AWGN with zero mean and E (ww*) = No I.

Referring back to FIG. 1, some aspects of FIG. 1 are now described with reference to an example conventional channel estimation method 2000 that is illustrated in the block diagram of FIG. 2 and may be executed by channel estimation component 1006 of UE 1002 and/or respective components thereof. The conventional channel estimation method 2000 includes an inner loop 2010 over Node Bs 1004 and an outer loop 2012 to iterate the inner loop 2010, both executed by channel estimation component 1006. Within the inner loop 2010, least squares 2002 is performed on a received signal y to estimate the tap values in the channel estimate tapped delay line 1008. Least squares may be performed by the least squares component 1014 of channel estimation component 1006. Then, tap-wise MMSE 2004 (which may be performed by tap cleaning component 1026 of channel estimation component 1006) and minimum mean square error (MMSE) scaling 2006 (which may be performed by MMSE scaling component 1016 of channel estimation component 1006) are performed on the results of the least squares 2002. In some aspects, tap-wise MMSE 2004 may include the dismissal of a tap if its power is below a combining factor times the noise power:

Accordingly, the identified and scaled taps provide the channel estimate for a respective Node B. Then, also within the inner loop 2010 and at each inner loop iteration, channel estimation component 1006 updates the contents of an interference buffer 2008 (which holds the most recent estimates of the channels for the cells or Node Bs 1004) according to the identified and scaled taps of the respective Node B 1004 in that iteration of the inner loop 2010, and then the inner loop 2010 is repeated if there are more Node Bs 1004 left to be iterated over 2009. The set of inner loops 2010 (e.g., one inner loop 2010 per cell or Node B 1004) is then repeated in the outer loop 2012. The number of outer loop iterations may be, in one non-limiting example, five iterations. At each iteration of the outer loop 2012, channel estimation component 1006 may use the interference buffer 2008 from the previous execution of the inner loop 2010 to update input y by subtracting an estimated inter-cell interference from input y. Such updating of input y may be referred to as Successive Interference Cancellation (SIC). Accordingly, an improved input y (after performing SIC) is provided to the next iteration of the inner loop 2010.

In some present aspects, however, tap classification is performed using power and/or temporal correlation filtering. For example, in an aspect, channel estimation component 1006 may identify a number of non-zero tap positions based on the temporal correlation of the taps and/or the power of the taps. FIG. 3 is one example block diagram of a channel estimation method 3000 that is based on the power and/or temporal correlation of the taps and which may be executed by channel estimation component 1006 or respective components thereof. Channel estimation method 3000 includes an inner loop 3024 over Node Bs 1004 and an outer loop 3026 to iterate the inner loop 3024 (e.g., 5 iterations), both executed by channel estimation component 1006. Within the inner loop 3024, least squares 3002 with SIC is performed by the least squares component 1014 (FIG. 1) on a received signal y to estimate the tap values in the channel estimate tapped delay line 1008. Alternatively or additionally, a rake receiver with SIC may be used on input y to estimate the tap values. [0027] In some aspects, channel estimation component 1006 may include noise power determination component 1018 that estimates the noise power using edge taps. For example, noise power determination component 1018 may use a number of taps (e.g., 4 taps) at the beginning and/or at the end of a shift, and may estimate the noise power based on the average of the power of such edge taps.

[0028] In some aspects, channel estimation component 1006 may include shift combining component 1020 that performs shift combining 3006 by combining shifts of the same beam-forming pattern to obtain an improved CIR estimate. In some aspects, when it is known which shifts are of the same beam, shift combining component 1020 combines the channel estimate results of those shifts to reduce the noise and improve the channel estimation. Alternatively, when it is not known which shifts are of the same beam, shift combining component 1020 may further perform shift detection prior to shift combining. In one non- limiting example aspect, shift combining component 1020 may combine the shift CIRs that correspond to a same beam and a same power. In these aspects, shift combining component 1020 may then perform equal-gain combining, where the shift CIRs are summed up and their average is taken as the improved shift CIR.

[0029] In some aspects, in order to perform shift detection, shift combining component

1020 may determine shift CIRs of the same beam based on CIR correlation. For example, for each cell and at each iteration of inner loop 3024 (optionally only for the last iteration of inner loop 3024 to reduce complexity), within a set of CIR estimates {h;} that includes candidate shifts for shift combining, shift combining component 1020 determines the shift CIR with the largest power, denoted as ho. In some aspects, the set of candidate shifts is determined based on the number of cyclic shifts per cell which may be J = 2, 4, 6, 8, 10, 12, 14, 16. For example, if J=8, then there are J=8 candidate shifts, each with a length of 128/J = 16 chips. Then, for the i-th shift, shift combining component 1020 determines the correlation value:

Q = re (ho . hi^H)

If Ci > 0 and ||Ci|| > PiPo times a threshold, then shift combining component 1020 includes the i-th shift in a shift combining set. [0030] In some aspects, shift combining component 1020 may perform maximal ratio combining (MRC) shift combining based on the identified shift combining set. For example, shift combining component 1020 ma determine the weighted sum:

where {hi} and {Pi} are the CIR estimates and powers of shifts in the identified shift combining set, respectively. Then, shift combining component 1020 may determine the normalized weighted sum:

and finally determine the CIR estimate of the i-th shift after shift combining as:

[0031] In some aspects, tap cleaning component 1026 of channel estimation component

1006 may perform tap cleaning by using clean tap ID propagation, e.g., by using the information of previously identified clean taps. For example, tap cleaning component 1026 may perform tap cleaning using Tapldx 3012, where Tapldx is clean tap IDs obtained in a previous iteration of inner loop 3024. For example, in one aspect, tap cleaning component 1026 may perform cleaning by determining Tapldx at time t, propagating the TapldX to time t+1 , and performing tap cleaning at the location of Tapldx.

[0032] In some aspects, in order to provide Tapldx to tap cleaning component 1026, channel estimation component 1006 may include tap power/correlation filtering component 1024 that performs filtering of tap power and/or correlation 3010. For example, tap power/correlation filtering component 1024 may filter the power and/or correlation on each tap in the last iteration 3008 of inner loop 3024, and then based on the result of the filtering, determine which taps are noise taps and which are signal taps. In some aspects, the filter may be an infinite impulse response (IIR) filter. In some aspects, tap power/correlation filtering component 1024 may use a filter metric that is based on the filtered tap power and the absolute tap correlation. For example, tap power/correlation filtering component 1024 may determine:

R_h (z, n) = aR_h {/. « - !) + (! - a)(h(i, n)h^* (i, n) + ahs(h(i, n)h^* (i, n - 1))) where R_h{i,n) is the filter metric for the tap ID with tap index i at time index n, h(i,n) is the tap ID with tap index i at time index n, and a is a constant. Upon determining R_h(i,ri), tap power/correlation filtering component 1024 may declare a tap as a signal tap if R_h(i,ri) is greater than the noise power times Th that is a noise tap threshold value, and otherwise declare the tap as a noise tap. Upon determining the signal and noise taps, MMSE scaling component 1016 of channel estimation component 1006 performs MMSE scaling 3014 on the output of tap cleaning component 1026.

[0033] In some aspects, after MMSE scaling 3014, shift combining component 1020 of channel estimation component 1006 (FIG. 1) may perform enhanced shift combining 3016 by first performing shift detection to determine which shifts are of the same beam, and then combining those shifts that correspond the same beam-forming pattern. In some aspects, channel estimation component 1006 (FIG. 1) may include shift cleaning component 1022 that performs shift cleaning 3018 after MMSE scaling 3014 and enhanced shift combining 3016. For example, shift cleaning component 1022 may determine the power of each shift, and then zero out those shifts which have a power less than a maximum shift power multiplied by a threshold. In some aspects, in order to determine the power of each shift, shift cleaning component 1022 may add the powers of the taps in that shift. Upon determining shift powers, shift cleaning component 1022 may determine the strongest shift based on the shift powers, determine those shifts that are weak compared to the strongest shift (e.g., shifts with shift powers lower than the maximum shift power times a threshold), and then zero out the taps in the weak shifts.

[0034] Referring back to FIG. 3, upon performing shift cleaning 3018, channel estimation component 1006 updates the contents of an interference buffer 3020 according to the identified and scaled taps of the cell or Node B 1004 corresponding to a current iteration of inner loop 3024. Then, channel estimation component 1006 repeats the inner loop 3024 if there are more Node Bs 1004 left to be iterated over 3022. Once the inner loop 3024 has iterated over all Node Bs 1004, channel estimation component 1006 repeats the set of inner loops 3024 in the outer loop 3026 in a similar manner as described herein with reference to corresponding inner and outer loops in FIG. 2.

[0035] Accordingly, in the present aspects, channel estimation is enhanced at a UE operating in TD-SCDMA by one or more of performing noise power estimation based on edge taps in a shift, performing shift combining to enhance CIR estimates, using the temporal correlation and the power delay profile of the propagation channel to perform tap classification and estimate the delays and envelopes of the channel, and performing shift cleaning to clean the taps in the relatively weak shifts.

[0036] Referring again to FIG. 1, UE 1002 may include (or may be an example of) an apparatus for channel estimation in TD-SCDMA that includes one or more means for performing any functions described herein. For example, in an aspect, least squares component 1014 of UE 1002 may include a means for determining least squares channel metric estimates based on a received signal that is received from one or more Node Bs. For instance, least squares component 1014 of UE 1002 may include one or any combination of hardware, software, firmware, computer-executable code or instructions, and data for determining least squares channel metric estimates based on a received signal that is received from one or more Node Bs.

[0037] Further, in an aspect, channel estimation component 1006 of UE 1002 may include a means for identifying signal taps and noise taps in a tapped delay line channel estimate based on at least one of temporal correlations and powers of the least squares channel metric estimates. For instance, channel estimation component 1006 may include one or any combination of hardware, software, firmware, computer-executable code or instructions, and data for identifying signal taps and noise taps in a tapped delay line channel estimate based on at least one of temporal correlations and powers of the least squares channel metric estimates.

[0038] Also, in an aspect, MMSE scaling component 1016 of UE 1002 may include means for performing minimum mean square error scaling on the signal taps and the noise taps. For instance, MMSE scaling component 1016 may include one or any combination of hardware, software, firmware, computer-executable code or instructions, and data for performing minimum mean square error scaling on the signal taps and the noise taps.

[0039] Further, in an aspect, channel estimation component 1006 of UE 1002 may include means for iterating a first loop for a first number of iterations, each iteration corresponding to one of the one or more Node Bs and comprising the determining of the least squares channel metric estimates, the identifying of the signal taps and the noise taps, and the performing of the minimum mean square error scaling, and further including updating contents of an interference buffer based on the signal taps and the noise taps, and means for iterating a second loop for a second number of iterations, where the second loop includes the iterating of the first loop and further comprises updating the received signal based on the contents of the interference buffer after the iterating of the first loop. For instance, channel estimation component 1006 may include one or any combination of hardware, software, firmware, computer-executable code or instructions, and data for iterating a first loop for a first number of iterations, each iteration corresponding to one of the one or more Node Bs and including the determining of the least squares channel metric estimates, the identifying of the signal taps and the noise taps, and the performing of the minimum mean square error scaling, and further including updating contents of an interference buffer based on the signal taps and the noise taps, and for iterating a second loop for a second number of iterations, where the second loop includes the iterating of the first loop and further includes updating the received signal based on the contents of the interference buffer after the iterating of the first loop.

[0040] Optionally, in an aspect, noise power determination component 1018 of UE

1002 may include means for performing noise power estimation based on edge taps in a shift, where the shift includes a number of taps within the tapped delay line channel estimate and corresponding to a midamble shift. For instance, noise power determination component 1018 may include one or any combination of hardware, software, firmware, computer-executable code or instructions, and data for performing noise power estimation based on edge taps in a shift, where the shift includes a number of taps within the tapped delay line channel estimate and corresponding to a midamble shift.

[0041] Optionally, in an aspect, shift combining component 1020 of UE 1002 may include means for determining shifts that correspond to a same beam-forming pattern; and means for updating the least squares channel metric estimates by combining respective least squares channel metric estimates in the shifts that correspond to the same beam- forming pattern. For instance, shift combining component 1020 may include one or any combination of hardware, software, firmware, computer-executable code or instructions, and data for determining shifts that correspond to a same beam- forming pattern; and updating the least squares channel metric estimates by combining respective least squares channel metric estimates in the shifts that correspond to the same beam-forming pattern.

[0042] Optionally, in some further aspect, for example, shift combining component

1020 may include means for determining a strongest shift with a largest power in a set of candidate shifts, means for determining a correlation value between the strongest shift and a candidate shift from remaining shifts in the set of candidate shifts, and means for determining, based on the correlation value, whether the candidate shift corresponds to the same beam-forming pattern as the strongest shift. For instance, shift combining component 1020 may include one or any combination of hardware, software, firmware, computer-executable code or instructions, and data for determining a strongest shift with a largest power in a set of candidate shifts, determining a correlation value between the strongest shift and a candidate shift from remaining shifts in the set of candidate shifts, and determining, based on the correlation value, whether the candidate shift corresponds to the same beam-forming pattern as the strongest shift.

[0043] Also, optionally, in some aspects, shift combining component 1020 may include means for performing MRC to combine the respective least squares channel metric estimates in the shifts that correspond to the same beam-forming pattern. For instance, shift combining component 1020 may include one or any combination of hardware, software, firmware, computer-executable code or instructions, and data for performing MRC to combine the respective least squares channel metric estimates in the shifts that correspond to the same beam-forming pattern.

[0044] In some aspects, for example, tap cleaning component 1026 of UE 1002 may include means for determining a clean tap identifier within the tapped delay line channel estimate and obtained in a previous iteration of the first loop; and means for performing tap cleaning at a location of the clean tap identifier. For instance, channel tap cleaning component 1026 may include one or any combination of hardware, software, firmware, computer-executable code or instructions, and data for determining a clean tap identifier within the tapped delay line channel estimate and obtained in a previous iteration of the first loop; and performing tap cleaning at a location of the clean tap identifier.

[0045] Further, in some aspects, for example, tap power/correlation filtering component

1024 of UE 1002 may include means for performing filtering of tap power and temporal correlation for each tap within the tapped delay line channel estimate in a last iteration of the first loop. For instance, tap power/correlation filtering component 1024 may include one or any combination of hardware, software, firmware, computer-executable code or instructions, and data for performing filtering of tap power and temporal correlation for each tap within the tapped delay line channel estimate in a last iteration of the first loop. In some aspects, the filtering is performed according to a filter metric that is based on a sum of a filtered tap power and an absolute value of a tap temporal correlation for each tap within the tapped delay line channel estimate. [0046] In some further aspects, for example, shift cleaning component 1026 of UE 1002 may include means for determining a power for each of one or more shifts, where each of the one or more shifts includes a number of taps within the tapped delay line channel estimate and corresponding to a midamble shift; and means for cleaning a shift in the one or more shifts by setting tap values equal to zero for taps in the shift when the shift has a power less than a maximum shift power multiplied by a threshold. For instance, shift cleaning component 1026 may include one or any combination of hardware, software, firmware, computer-executable code or instructions, and data for determining a power for each of one or more shifts, where each of the one or more shifts includes a number of taps within the tapped delay line channel estimate and corresponding to a midamble shift; and cleaning a shift in the one or more shifts by setting tap values equal to zero for taps in the shift when the shift has a power less than a maximum shift power multiplied by a threshold.

[0047] Referring now to FIG. 4, in some aspects, method 4000 for channel estimation in

TD-SCDMA is illustrated. For explanatory purposes, method 4000 will be discussed with reference to the above described FIG. 1. It should be understood that in other implementations, other systems and/or UEs, Node Bs, or other apparatus comprising different components than those illustrated in FIG. 1 may be used when implementing method 4000 of FIG. 4.

[0048] At block 4002, method 4000 includes determining least squares channel metric estimates based on a received signal that is received from one or more Node Bs. For example, least squares component 1014 of channel estimation component 1006 of UE 1002 may determine least squares channel metric estimates based on a received signal that is received from Node Bs 1004.

[0049] Optionally, at block 4004, method 4000 includes performing noise power estimation based on edge taps in a shift, where the shift includes a number of taps within the tapped delay line channel estimate and corresponding to a midamble shift. For example, noise power determination component 1018 of channel estimation component 1006 may perform noise power estimation based on edge taps in a shift that includes a number of taps within channel estimate tapped delay line 1008, where the shift corresponds to a midamble shift.

[0050] Optionally, at block 4006, method 4000 includes determining shifts that correspond to a same beam-forming pattern and updating the least squares channel metric estimates by combining respective least squares channel metric estimates in the shifts that correspond to the same beam-forming pattern. For example, shift combining component 1020 of channel estimation component 1006 may determine shifts that correspond to a same beam-forming pattern and update the least squares channel metric estimates by combining respective least squares channel metric estimates in the shifts that correspond to the same beam-forming pattern. In some aspects, shift combining component 1020 may determine the shifts that correspond to the same beam- forming pattern by determining a strongest shift with a largest power in a set of candidate shifts, determining a correlation value between the strongest shift and a candidate shift from remaining shifts in the set of candidate shifts, and determining, based on the correlation value, whether the candidate shift corresponds to the same beam-forming pattern as the strongest shift. In some aspects, shift combining component 1020 may update the least squares channel metric estimates by performing MRC to combine the respective least squares channel metric estimates in the shifts that correspond to the same beam-forming pattern.

[0051] At block 4008, method 4000 includes identifying signal taps and noise taps in a tapped delay line channel estimate based on at least one of temporal correlations and powers of the least squares channel metric estimates. For example, channel estimation component 1006 may determine signal taps 1010 and noise taps 1012 in channel estimate tapped delay line 1008 based on at least one of temporal correlations and powers of the least squares channel metric estimates. In some aspects, channel estimation component 1006 includes tap cleaning component 1026 that identifies signal taps 1010 and noise taps 1012 by determining a clean tap identifier within channel estimate tapped delay line 1008 and obtained in a previous iteration of inner loop 3024 and performing tap cleaning at a location of the clean tap identifier. In some aspects, channel estimation component 1006 includes tap power/correlation filtering component 1024 that determines the clean tap identifier by performing filtering of tap power and temporal correlation for each tap within channel estimate tapped delay line 1008 in a last iteration of inner loop 3024. In some aspects, tap power/correlation filtering component 1024 performs the filtering according to a filter metric that is based on a sum of a filtered tap power and an absolute value of a tap temporal correlation for each tap within channel estimate tapped delay line 1008.

[0052] At block 4010, method 4000 includes performing minimum mean square error scaling on the signal taps and the noise taps. For example, MMSE scaling component 1016 may perform MMSE scaling on signal taps 1010 and noise taps 1012. [0053] At optional block 4012, method 4000 includes determining a power for each of one or more shifts, where each of the one or more shifts includes a number of taps within the tapped delay line channel estimate and corresponding to a midamble shift, and cleaning a shift in the one or more shifts by setting tap values equal to zero for taps in the shift when the shift has a power less than a maximum shift power multiplied by a threshold. For example, shift cleaning component 1022 of channel estimation component 1006 may determine a power for each of one or more shifts, where each of the one or more shifts includes a number of taps within channel estimate tapped delay line 1008 and corresponding to a midamble shift, and cleaning a shift in the one or more shifts by setting tap values equal to zero for taps in the shift when the shift has a power less than a maximum shift power multiplied by a threshold. In some aspects, shift cleaning component 1022 may determine the power for each of the one or more shifts by adding tap powers of taps in a shift.

[0054] At block 4014, method 4000 includes iterating a first loop for a first number of iterations, each iteration corresponding to one of the one or more Node Bs and including the determining of the least squares channel metric estimates, the identifying of the signal taps and the noise taps, and the performing of the minimum mean square error scaling, and further including updating contents of an interference buffer based on the signal taps and the noise taps. For example, channel estimation component 1006 may iterate inner loop 3024 for a first number of iterations, each iteration corresponding to one Node B 1004 and including the determining of the least squares channel metric estimates, the identifying of signal taps 1010 and noise taps 1012, and the performing of the minimum mean square error scaling, and further including updating contents of an interference buffer based on signal taps 1010 and noise taps 1012.

[0055] At block 4016, method 4000 includes iterating a second loop for a second number of iterations, where the second loop includes the iterating of the first loop and further includes updating the received signal based on the contents of the interference buffer after the iterating of the first loop. For example, channel estimation component 1006 may iterate outer loop 3026 for a second number of iterations, where outer loop 3026 includes the iterating of the inner loop 3024 and further includes updating the received signal based on the contents of the interference buffer after the iterating of inner loop 3024.

[0056] FIG. 5 is a block diagram illustrating an example of a hardware implementation for an apparatus 100 employing a processing system 114 to operate, for example, UE 1002, channel estimation component 1006, and/or respective components thereof (see FIG. 1) to perform any functions described herein with respect to UE 1002 or channel estimation component 1006, for example, method 3000 of FIG. 3 or method 4000 of FIG. 4. In this example, the processing system 114 may be implemented with a bus architecture, represented generally by the bus 102. The bus 102 may include any number of interconnecting buses and bridges depending on the specific application of the processing system 114 and the overall design constraints. The bus 102 links together various circuits including one or more processors, represented generally by the processor 104, and computer-readable media, represented generally by the computer- readable medium 106. The bus 102 may also link various other circuits such as timing sources, peripherals, voltage regulators, and power management circuits, which are well known in the art, and therefore, will not be described any further. A bus interface 108 provides an interface between the bus 102 and a transceiver 110. The transceiver 110 provides a means for communicating with various other apparatus over a transmission medium. Depending upon the nature of the apparatus, a user interface 112 (e.g., keypad, display, speaker, microphone, joystick) may also be provided. Apparatus 100 further includes channel estimation component 1006 (see FIG. 1) that is linked by bus 102 to other components of apparatus 100.

[0057] The processor 104 is responsible for managing the bus 102 and general processing, including the execution of software stored on the computer-readable medium 106. The software, when executed by the processor 104, causes the processing system 114 to perform the various functions described infra for any particular apparatus. The computer-readable medium 106 may also be used for storing data that is manipulated by the processor 104 when executing software.

[0058] The various concepts presented throughout this disclosure may be implemented across a broad variety of telecommunication systems, network architectures, and communication standards. By way of example and without limitation, the aspects of the present disclosure illustrated in FIG. 6 are presented with reference to a UMTS system 200 employing a W-CDMA air interface. A UMTS network includes three interacting domains: a Core Network (CN) 204, a UMTS Terrestrial Radio Access Network (UTRAN) 202, and User Equipment (UE) 210. UE 210 or UTRAN 202 may include UE 1002, channel estimation component 1006, or apparatus 100 (see FIGs. 1 and 5), and may be configured to perform any functions described herein with respect to UE 1002 or channel estimation component 1006, for example, method 3000 of FIG. 3 or method 4000 of FIG. 4. In this example, the UTRAN 202 provides various wireless services including telephony, video, data, messaging, broadcasts, and/or other services. The UTRAN 202 may include a plurality of Radio Network Subsystems (RNSs) such as an RNS 207, each controlled by a respective Radio Network Controller (RNC) such as an RNC 206. Here, the UTRAN 202 may include any number of RNCs 206 and RNSs 207 in addition to the RNCs 206 and RNSs 207 illustrated herein. The RNC 206 is an apparatus responsible for, among other things, assigning, reconfiguring and releasing radio resources within the RNS 207. The RNC 206 may be interconnected to other RNCs (not shown) in the UTRAN 202 through various types of interfaces such as a direct physical connection, a virtual network, or the like, using any suitable transport network.

[0059] Communication between a UE 210 and a Node B 208 may be considered as including a physical (PHY) layer and a medium access control (MAC) layer. Further, communication between a UE 210 and an RNC 206 by way of a respective Node B 208 may be considered as including a radio resource control (RRC) layer. In the instant specification, the PHY layer may be considered layer 1; the MAC layer may be considered layer 2; and the RRC layer may be considered layer 3. Information hereinbelow utilizes terminology introduced in the RRC Protocol Specification, 3 GPP TS 25.331 v9.1.0, incorporated herein by reference.

[0060] The geographic region covered by the RNS 207 may be divided into a number of cells, with a radio transceiver apparatus serving each cell. A radio transceiver apparatus is commonly referred to as a Node B in UMTS applications, but may also be referred to by those skilled in the art as a base station (BS), a base transceiver station (BTS), a radio base station, a radio transceiver, a transceiver function, a basic service set (BSS), an extended service set (ESS), an access point (AP), or some other suitable terminology. For clarity, three Node Bs 208 are shown in each RNS 207; however, the RNSs 207 may include any number of wireless Node Bs. The Node Bs 208 provide wireless access points to a CN 204 for any number of mobile apparatuses. Examples of a mobile apparatus include a cellular phone, a smart phone, a session initiation protocol (SIP) phone, a laptop, a notebook, a netbook, a smartbook, a personal digital assistant (PDA), a satellite radio, a global positioning system (GPS) device, a multimedia device, a video device, a digital audio player (e.g., MP3 player), a camera, a game console, or any other similar functioning device. The mobile apparatus is commonly referred to as a UE in UMTS applications, but may also be referred to by those skilled in the art as a mobile station, a subscriber station, a mobile unit, a subscriber unit, a wireless unit, a remote unit, a mobile device, a wireless device, a wireless communications device, a remote device, a mobile subscriber station, an access terminal, a mobile terminal, a wireless terminal, a remote terminal, a handset, a terminal, a user agent, a mobile client, a client, or some other suitable terminology. In a UMTS system, the UE 210 may further include a universal subscriber identity module (USIM) 211, which contains a user's subscription information to a network. For illustrative purposes, one UE 210 is shown in communication with a number of the Node Bs 208. The DL, also called the forward link, refers to the communication link from a Node B 208 to a UE 210, and the UL, also called the reverse link, refers to the communication link from a UE 210 to a Node B 208.

[0061] The CN 204 interfaces with one or more access networks, such as the UTRAN

202. As shown, the CN 204 is a GSM core network. However, as those skilled in the art will recognize, the various concepts presented throughout this disclosure may be implemented in a RAN, or other suitable access network, to provide UEs with access to types of CNs other than GSM networks.

[0062] The CN 204 includes a circuit-switched (CS) domain and a packet-switched (PS) domain. Some of the circuit-switched elements are a Mobile services Switching Centre (MSC), a Visitor location register (VLR) and a Gateway MSC. Packet-switched elements include a Serving GPRS Support Node (SGSN) and a Gateway GPRS Support Node (GGSN). Some network elements, like EIR, HLR, VLR and AuC may be shared by both of the circuit- switched and packet-switched domains. In the illustrated example, the CN 204 supports circuit-switched services with a MSC 212 and a GMSC 214. In some applications, the GMSC 214 may be referred to as a media gateway (MGW). One or more RNCs, such as the RNC 206, may be connected to the MSC 212. The MSC 212 is an apparatus that controls call setup, call routing, and UE mobility functions. The MSC 212 also includes a VLR that contains subscriber-related information for the duration that a UE is in the coverage area of the MSC 212. The GMSC 214 provides a gateway through the MSC 212 for the UE to access a circuit-switched network 216. The GMSC 214 includes a home location register (HLR) 215 containing subscriber data, such as the data reflecting the details of the services to which a particular user has subscribed. The HLR is also associated with an authentication center (AuC) that contains subscriber-specific authentication data. When a call is received for a particular UE, the GMSC 214 queries the HLR 215 to determine the UE's location and forwards the call to the particular MSC serving that location. [0063] The CN 204 also supports packet-data services with a serving GPRS support node (SGSN) 218 and a gateway GPRS support node (GGSN) 220. GPRS, which stands for General Packet Radio Service, is designed to provide packet-data services at speeds higher than those available with standard circuit-switched data services. The GGSN 220 provides a connection for the UTRAN 202 to a packet-based network 222. The packet-based network 222 may be the Internet, a private data network, or some other suitable packet-based network. The primary function of the GGSN 220 is to provide the UEs 210 with packet-based network connectivity. Data packets may be transferred between the GGSN 220 and the UEs 210 through the SGSN 218, which performs primarily the same functions in the packet-based domain as the MSC 212 performs in the circuit-switched domain.

[0064] An air interface for UMTS may utilize a spread spectrum Direct-Sequence Code

Division Multiple Access (DS-CDMA) system. The spread spectrum DS-CDMA spreads user data through multiplication by a sequence of pseudorandom bits called chips. The "wideband" W-CDMA air interface for UMTS is based on such direct sequence spread spectrum technology and additionally calls for a frequency division duplexing (FDD). FDD uses a different carrier frequency for the UL and DL between a Node B 208 and a UE 210. Another air interface for UMTS that utilizes DS-CDMA, and uses time division duplexing (TDD), is the TD-SCDMA air interface. Those skilled in the art will recognize that although various examples described herein may refer to a W-CDMA air interface, the underlying principles may be equally applicable to a TD- SCDMA air interface.

[0065] An HSPA air interface includes a series of enhancements to the 3G/W-CDMA air interface, facilitating greater throughput and reduced latency. Among other modifications over prior releases, HSPA utilizes hybrid automatic repeat request (HARQ), shared channel transmission, and adaptive modulation and coding. The standards that define HSPA include HSDPA (high speed downlink packet access) and HSUPA (high speed uplink packet access, also referred to as enhanced uplink, or EUL).

[0066] HSDPA utilizes as its transport channel the high-speed downlink shared channel

(HS-DSCH). The HS-DSCH is implemented by three physical channels: the high-speed physical downlink shared channel (HS-PDSCH), the high-speed shared control channel (HS-SCCH), and the high-speed dedicated physical control channel (HS-DPCCH).

[0067] Among these physical channels, the HS-DPCCH carries the HARQ

ACK/NACK signaling on the uplink to indicate whether a corresponding packet transmission was decoded successfully. That is, with respect to the downlink, the UE 210 provides feedback to the node B 208 over the HS-DPCCH to indicate whether it correctly decoded a packet on the downlink.

[0068] HS-DPCCH further includes feedback signaling from the UE 210 to assist the node B 208 in taking the right decision in terms of modulation and coding scheme and precoding weight selection, this feedback signaling including the CQI and PCI.

[0069] "HSPA Evolved" or HSPA+ is an evolution of the HSPA standard that includes

MIMO and 64-QAM, enabling increased throughput and higher performance. That is, in an aspect of the disclosure, the node B 208 and/or the UE 210 may have multiple antennas supporting MIMO technology. The use of MIMO technology enables the node B 208 to exploit the spatial domain to support spatial multiplexing, beamforming, and transmit diversity.

[0070] Multiple Input Multiple Output (MIMO) is a term generally used to refer to multi-antenna technology, that is, multiple transmit antennas (multiple inputs to the channel) and multiple receive antennas (multiple outputs from the channel). MIMO systems generally enhance data transmission performance, enabling diversity gains to reduce multipath fading and increase transmission quality, and spatial multiplexing gains to increase data throughput.

[0071] Spatial multiplexing may be used to transmit different streams of data simultaneously on the same frequency. The data steams may be transmitted to a single UE 210 to increase the data rate or to multiple UEs 210 to increase the overall system capacity. This is achieved by spatially precoding each data stream and then transmitting each spatially precoded stream through a different transmit antenna on the downlink. The spatially precoded data streams arrive at the UE(s) 210 with different spatial signatures, which enables each of the UE(s) 210 to recover the one or more the data streams destined for that UE 210. On the uplink, each UE 210 may transmit one or more spatially precoded data streams, which enables the node B 208 to identify the source of each spatially precoded data stream.

[0072] Spatial multiplexing may be used when channel conditions are good. When channel conditions are less favorable, beamforming may be used to focus the transmission energy in one or more directions, or to improve transmission based on characteristics of the channel. This may be achieved by spatially precoding a data stream for transmission through multiple antennas. To achieve good coverage at the edges of the cell, a single stream beamforming transmission may be used in combination with transmit diversity.

[0073] Generally, for MIMO systems utilizing n transmit antennas, n transport blocks may be transmitted simultaneously over the same carrier utilizing the same channelization code. Note that the different transport blocks sent over the n transmit antennas may have the same or different modulation and coding schemes from one another.

[0074] On the other hand, Single Input Multiple Output (SIMO) generally refers to a system utilizing a single transmit antenna (a single input to the channel) and multiple receive antennas (multiple outputs from the channel). Thus, in a SIMO system, a single transport block is sent over the respective carrier.

[0075] Referring to FIG. 7, an access network 300 in a UTRAN architecture is illustrated in which one or more of the wireless communication entities, e.g., UEs and/or base stations, may include UE 1002, 210, Node B 1004, 208, channel estimation component 1006, or apparatus 100 (see FIGs. 1, 5, and 6). For example, UEs 330, 332, 334, 336, 338, 340 may include UE 1002 or channel estimation component 1006 and may be configured to perform any functions described herein with respect to UE 1002 or channel estimation component 1006, for example, method 3000 of FIG. 3 or method 4000 of FIG. 4. The multiple access wireless communication system includes multiple cellular regions (cells), including cells 302, 304, and 306, each of which may include one or more sectors. The multiple sectors can be formed by groups of antennas with each antenna responsible for communication with UEs in a portion of the cell. For example, in cell 302, antenna groups 312, 314, and 316 may each correspond to a different sector. In cell 304, antenna groups 318, 320, and 322 each correspond to a different sector. In cell 306, antenna groups 324, 326, and 328 each correspond to a different sector. The cells 302, 304 and 306 may include several wireless communication devices, e.g., User Equipment or UEs, which may be in communication with one or more sectors of each cell 302, 304 or 306. For example, UEs 330 and 332 may be in communication with Node B 342, UEs 334 and 336 may be in communication with Node B 344, and UEs 338 and 340 can be in communication with Node B 346. Here, each Node B 342, 344, 346 is configured to provide an access point to a CN 204 (see FIG. 6) for all the UEs 330, 332, 334, 336, 338, 340 in the respective cells 302, 304, and 306. [0076] As the UE 334 moves from the illustrated location in cell 304 into cell 306, a serving cell change (SCC) or handover may occur in which communication with the UE 334 transitions from the cell 304, which may be referred to as the source cell, to cell 306, which may be referred to as the target cell. Management of the handover procedure may take place at the UE 334, at the Node Bs corresponding to the respective cells, at a radio network controller 206 (see FIG. 6), or at another suitable node in the wireless network. For example, during a call with the source cell 304, or at any other time, the UE 334 may monitor various parameters of the source cell 304 as well as various parameters of neighboring cells such as cells 306 and 302. Further, depending on the quality of these parameters, the UE 334 may maintain communication with one or more of the neighboring cells. During this time, the UE 334 may maintain an Active Set, that is, a list of cells that the UE 334 is simultaneously connected to (i.e., the UTRA cells that are currently assigning a downlink dedicated physical channel DPCH or fractional downlink dedicated physical channel F-DPCH to the UE 334 may constitute the Active Set).

[0077] The modulation and multiple access scheme employed by the access network

300 may vary depending on the particular telecommunications standard being deployed. By way of example, the standard may include Evolution-Data Optimized (EV-DO) or Ultra Mobile Broadband (UMB). EV-DO and UMB are air interface standards promulgated by the 3rd Generation Partnership Project 2 (3GPP2) as part of the CDMA2000 family of standards and employs CDMA to provide broadband Internet access to mobile stations. The standard may alternately be Universal Terrestrial Radio Access (UTRA) employing Wideband-CDMA (W-CDMA) and other variants of CDMA, such as TD-SCDMA; Global System for Mobile Communications (GSM) employing TDMA; and Evolved UTRA (E-UTRA), Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802.20, and Flash-OFDM employing OFDMA. UTRA, E-UTRA, UMTS, LTE, LTE Advanced, and GSM are described in documents from the 3GPP organization. CDMA2000 and UMB are described in documents from the 3GPP2 organization. The actual wireless communication standard and the multiple access technology employed will depend on the specific application and the overall design constraints imposed on the system.

[0078] FIG.8 is a block diagram of a Node B 810 in communication with a UE 850, where the Node B 810 may include Node Bs 1004, 208, and the UE 850 may include UEs 1002, 210, channel estimation component 1006, or apparatus 100 (see, e.g., FIGs. 1, 5, and 6), and where UE 850 may be configured to perform any functions described herein with respect to UE 1002 or channel estimation component 1006, for example, method 3000 of FIG. 3 or method 4000 of FIG. 4. In the downlink communication, a transmit processor 820 may receive data from a data source 812 and control signals from a controller/processor 840. The transmit processor 820 provides various signal processing functions for the data and control signals, as well as reference signals (e.g., pilot signals). For example, the transmit processor 820 may provide cyclic redundancy check (CRC) codes for error detection, coding and interleaving to facilitate forward error correction (FEC), mapping to signal constellations based on various modulation schemes (e.g., binary phase-shift keying (BPSK), quadrature phase-shift keying (QPSK), M-phase-shift keying (M-PSK), M-quadrature amplitude modulation (M-QAM), and the like), spreading with orthogonal variable spreading factors (OVSF), and multiplying with scrambling codes to produce a series of symbols. Channel estimates from a channel processor 844 may be used by a controller/processor 840 to determine the coding, modulation, spreading, and/or scrambling schemes for the transmit processor 820. These channel estimates may be derived from a reference signal transmitted by the UE 850 or from feedback from the UE 850. The symbols generated by the transmit processor 820 are provided to a transmit frame processor 830 to create a frame structure. The transmit frame processor 830 creates this frame structure by multiplexing the symbols with information from the controller/processor 840, resulting in a series of frames. The frames are then provided to a transmitter 832, which provides various signal conditioning functions including amplifying, filtering, and modulating the frames onto a carrier for downlink transmission over the wireless medium through antenna 834. The antenna 834 may include one or more antennas, for example, including beam steering bidirectional adaptive antenna arrays or other similar beam technologies.

At the UE 850, a receiver 854 receives the downlink transmission through an antenna 852 and processes the transmission to recover the information modulated onto the carrier. The information recovered by the receiver 854 is provided to a receive frame processor 860, which parses each frame, and provides information from the frames to a channel processor 894 and the data, control, and reference signals to a receive processor 870. The receive processor 870 then performs the inverse of the processing performed by the transmit processor 820 in the Node B 810. More specifically, the receive processor 870 descrambles and despreads the symbols, and then determines the most likely signal constellation points transmitted by the Node B 810 based on the modulation scheme. These soft decisions may be based on channel estimates computed by the channel processor 894. The soft decisions are then decoded and deinterleaved to recover the data, control, and reference signals. The CRC codes are then checked to determine whether the frames were successfully decoded. The data carried by the successfully decoded frames will then be provided to a data sink 872, which represents applications running in the UE 850 and/or various user interfaces (e.g., display). Control signals carried by successfully decoded frames will be provided to a controller/processor 890. When frames are unsuccessfully decoded by the receiver processor 870, the controller/processor 890 may also use an acknowledgement (ACK) and/or negative acknowledgement (NACK) protocol to support retransmission requests for those frames.

[0080] In the uplink, data from a data source 878 and control signals from the controller/processor 890 are provided to a transmit processor 880. The data source 878 may represent applications running in the UE 850 and various user interfaces (e.g., keyboard). Similar to the functionality described in connection with the downlink transmission by the Node B 810, the transmit processor 880 provides various signal processing functions including CRC codes, coding and interleaving to facilitate FEC, mapping to signal constellations, spreading with OVSFs, and scrambling to produce a series of symbols. Channel estimates, derived by the channel processor 894 from a reference signal transmitted by the Node B 810 or from feedback contained in the midamble transmitted by the Node B 810, may be used to select the appropriate coding, modulation, spreading, and/or scrambling schemes. The symbols produced by the transmit processor 880 will be provided to a transmit frame processor 882 to create a frame structure. The transmit frame processor 882 creates this frame structure by multiplexing the symbols with information from the controller/processor 890, resulting in a series of frames. The frames are then provided to a transmitter 856, which provides various signal conditioning functions including amplification, filtering, and modulating the frames onto a carrier for uplink transmission over the wireless medium through the antenna 852.

[0081] The uplink transmission is processed at the Node B 810 in a manner similar to that described in connection with the receiver function at the UE 850. A receiver 835 receives the uplink transmission through the antenna 834 and processes the transmission to recover the information modulated onto the carrier. The information recovered by the receiver 835 is provided to a receive frame processor 836, which parses each frame, and provides information from the frames to the channel processor 844 and the data, control, and reference signals to a receive processor 838. The receive processor 838 performs the inverse of the processing performed by the transmit processor 880 in the UE 850. The data and control signals carried by the successfully decoded frames may then be provided to a data sink 839 and the controller/processor, respectively. If some of the frames were unsuccessfully decoded by the receive processor, the controller/processor 840 may also use an acknowledgement (ACK) and/or negative acknowledgement (NACK) protocol to support retransmission requests for those frames.

[0082] The controllers/processors 840 and 890 may be used to direct the operation at the Node B 810 and the UE 850, respectively. For example, the controller/processors 840 and 890 may provide various functions including timing, peripheral interfaces, voltage regulation, power management, and other control functions. The computer readable media of memories 842 and 892 may store data and software for the Node B 810 and the UE 850, respectively. A scheduler/processor 846 at the Node B 810 may be used to allocate resources to the UEs and schedule downlink and/or uplink transmissions for the UEs.

[0083] Several aspects of a telecommunications system have been presented with reference to a W-CDMA system. As those skilled in the art will readily appreciate, various aspects described throughout this disclosure may be extended to other telecommunication systems, network architectures and communication standards.

[0084] By way of example, various aspects may be extended to other UMTS systems such as TD-SCDMA, High Speed Downlink Packet Access (HSDPA), High Speed Uplink Packet Access (HSUPA), High Speed Packet Access Plus (HSPA+) and TD- CDMA. Various aspects may also be extended to systems employing Long Term Evolution (LTE) (in FDD, TDD, or both modes), LTE-Advanced (LTE-A) (in FDD, TDD, or both modes), CDMA2000, Evolution-Data Optimized (EV-DO), Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802.20, Ultra- Wideband (UWB), Bluetooth, and/or other suitable systems. The actual telecommunication standard, network architecture, and/or communication standard employed will depend on the specific application and the overall design constraints imposed on the system.

[0085] In accordance with various aspects of the disclosure, an element, or any portion of an element, or any combination of elements may be implemented with a "processing system" that includes one or more processors. Examples of processors include microprocessors, microcontrollers, digital signal processors (DSPs), field programmable gate arrays (FPGAs), programmable logic devices (PLDs), state machines, gated logic, discrete hardware circuits, and other suitable hardware configured to perform the various functionality described throughout this disclosure. One or more processors in the processing system may execute software. Software shall be construed broadly to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executables, threads of execution, procedures, functions, etc., whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise. The software may reside on a computer-readable medium. The computer-readable medium may be a non-transitory computer-readable medium. A non-transitory computer-readable medium includes, by way of example, a magnetic storage device (e.g., hard disk, floppy disk, magnetic strip), an optical disk (e.g., compact disk (CD), digital versatile disk (DVD)), a smart card, a flash memory device (e.g., card, stick, key drive), random access memory (RAM), read only memory (ROM), programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), a register, a removable disk, and any other suitable medium for storing software and/or instructions that may be accessed and read by a computer. The computer-readable medium may also include, by way of example, a carrier wave, a transmission line, and any other suitable medium for transmitting software and/or instructions that may be accessed and read by a computer. The computer-readable medium may be resident in the processing system, external to the processing system, or distributed across multiple entities including the processing system. The computer- readable medium may be embodied in a computer-program product. By way of example, a computer-program product may include a computer-readable medium in packaging materials. Those skilled in the art will recognize how best to implement the described functionality presented throughout this disclosure depending on the particular application and the overall design constraints imposed on the overall system.

It is to be understood that the specific order or hierarchy of steps in the methods disclosed is an illustration of exemplary processes. Based upon design preferences, it is understood that the specific order or hierarchy of steps in the methods may be rearranged. The accompanying method claims present elements of the various steps in a sample order, and are not meant to be limited to the specific order or hierarchy presented unless specifically recited therein. The previous description is provided to enable any person skilled in the art to practice the various aspects described herein. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects. Thus, the claims are not intended to be limited to the aspects shown herein, but is to be accorded the full scope consistent with the language of the claims, wherein reference to an element in the singular is not intended to mean "one and only one" unless specifically so stated, but rather "one or more." Unless specifically stated otherwise, the term "some" refers to one or more. A phrase referring to "at least one of a list of items refers to any combination of those items, including single members. As an example, "at least one of: a, b, or c" is intended to cover: a; b; c; a and b; a and c; b and c; and a, b and c. All structural and functional equivalents to the elements of the various aspects described throughout this disclosure that are known or later come to be known to those of ordinary skill in the art are expressly incorporated herein by reference and are intended to be encompassed by the claims. Moreover, nothing disclosed herein is intended to be dedicated to the public regardless of whether such disclosure is explicitly recited in the claims. No claim element is to be construed under the provisions of 35 U.S.C. § 112, sixth paragraph, unless the element is expressly recited using the phrase "means for" or, in the case of a method claim, the element is recited using the phrase "step for."

Claims

CLAIMS What is claimed is:

1. A method for channel estimation in time division synchronous code division multiple access (TD-SCDMA), comprising:

determining least squares channel metric estimates based on a received signal that is received from one or more Node Bs;

identifying signal taps and noise taps in a tapped delay line channel estimate based on at least one of temporal correlations and powers of the least squares channel metric estimates; and

performing minimum mean square error scaling on the signal taps and the noise taps.

2. The method of claim 1, further comprising:

iterating a first loop for a first number of iterations, each iteration corresponding to one of the one or more Node Bs and comprising the determining of the least squares channel metric estimates, the identifying of the signal taps and the noise taps, and the performing of the minimum mean square error scaling, and further comprising updating contents of an interference buffer based on the signal taps and the noise taps; and

iterating a second loop for a second number of iterations, wherein the second loop comprises the iterating of the first loop and further comprises updating the received signal based on the contents of the interference buffer after the iterating of the first loop.

3. The method of claim 2, further comprising:

performing noise power estimation based on edge taps in a shift, wherein the shift includes a number of taps within the tapped delay line channel estimate and corresponding to a midamble shift.

4. The method of claim 2, further comprising:

determining shifts that correspond to a same beam- forming pattern; and updating the least squares channel metric estimates by combining respective least squares channel metric estimates in the shifts that correspond to the same beam- forming pattern.

5. The method of claim 4, wherein the determining of the shifts that correspond to the same beam- forming pattern comprises:

determining a strongest shift with a largest power in a set of candidate shifts; determining a correlation value between the strongest shift and a candidate shift from remaining shifts in the set of candidate shifts; and

determining, based on the correlation value, whether the candidate shift corresponds to the same beam-forming pattern as the strongest shift.

6. The method of claim 4, wherein the updating of the least squares channel metric estimates comprises:

performing maximal ratio combining (MRC) to combine the respective least squares channel metric estimates in the shifts that correspond to the same beam-forming pattern.

7. The method of claim 2, wherein the identifying of the signal taps and the noise taps comprises:

determining a clean tap identifier within the tapped delay line channel estimate and obtained in a previous iteration of the first loop; and

performing tap cleaning at a location of the clean tap identifier.

8. The method of claim 7, wherein the determining of the clean tap identifier comprises:

performing filtering of tap power and temporal correlation for each tap within the tapped delay line channel estimate in a last iteration of the first loop.

9. The method of claim 8, wherein the filtering is performed according to a filter metric that is based on a sum of a filtered tap power and an absolute value of a tap temporal correlation for each tap within the tapped delay line channel estimate.

10. The method of claim 2, further comprising:

determining a power for each of one or more shifts, wherein each of the one or more shifts includes a number of taps within the tapped delay line channel estimate and corresponding to a midamble shift; and

cleaning a shift in the one or more shifts by setting tap values equal to zero for taps in the shift when the shift has a power less than a maximum shift power multiplied by a threshold.

11. The method of claim 10, wherein the determining of the power for each of the one or more shifts comprises:

determining the power of the shift in the one or more shifts by adding tap powers of taps in the shift.

12. An apparatus for channel estimation in time division synchronous code division multiple access (TD-SCDMA) comprising a processing system configured to:

determine least squares channel metric estimates based on a received signal that is received from one or more Node Bs;

identify signal taps and noise taps in a tapped delay line channel estimate based on at least one of temporal correlations and powers of the least squares channel metric estimates; and

perform minimum mean square error scaling on the signal taps and the noise taps.

13. The apparatus of claim 12, wherein the processing system is further configured to:

iterate a first loop for a first number of iterations, each iteration corresponding to one of the one or more Node Bs and comprising the determining of the least squares channel metric estimates, the identifying of the signal taps and noise taps, and the performing of the minimum mean square error scaling, and further comprising updating contents of an interference buffer based on the signal taps and the noise taps; and

iterate a second loop for a second number of iterations, wherein the second loop comprises the iterating of the first loop and further comprises updating the received signal based on the contents of the interference buffer after the iterating of the first loop.

14. The apparatus of claim 13, wherein the processing system is further configured to:

perform noise power estimation based on edge taps in a shift, wherein the shift includes a number of taps within the tapped delay line channel estimate and corresponding to a midamble shift.

15. The apparatus of claim 13, wherein the processing system is further configured to:

determine shifts that correspond to a same beam- forming pattern; and

update the least squares channel metric estimates by combining respective least squares channel metric estimates in the shifts that correspond to the same beam-forming pattern.

16. The apparatus of claim 13, wherein the processing system is configured to determine the shifts that correspond to the same beam-forming pattern by:

17. The apparatus of claim 13, wherein the processing system is configured to update the least squares channel metric estimates by: performing maximal ratio combining (MRC) to combine the respective least squares channel metric estimates in the shifts that correspond to the same beam-forming pattern.

18. The apparatus of claim 13, wherein the processing system is configured to identify the signal taps and the noise taps by:

determining a clean tap identifier within the tapped delay line channel estimate and obtained in a previous iteration of the second loop; and

performing tap cleaning at a location of the clean tap identifier.

19. The apparatus of claim 18, wherein the processing system is configured to determine the clean tap identifier by:

20. A computer program product for channel estimation in time division

synchronous code division multiple access (TD-SCDMA) comprising a computer- readable medium comprising:

code for determining least squares channel metric estimates based on a received signal that is received from one or more Node Bs;

code for identifying signal taps and noise taps in a tapped delay line channel estimate based on at least one of temporal correlations and powers of the least squares channel metric estimates; and

code for performing minimum mean square error scaling on the signal taps and the noise taps.

21. An apparatus for channel estimation in time division synchronous code division multiple access (TD-SCDMA), comprising:

means for determining least squares channel metric estimates based on a received signal that is received from one or more Node Bs; means for identifying signal taps and noise taps in a tapped delay line channel estimate based on at least one of temporal correlations and powers of the least squares channel metric estimates; and

means for performing minimum mean square error scaling on the signal taps and the noise taps.

22. The apparatus of claim 21, further comprising:

means for iterating a first loop for a first number of iterations, each iteration corresponding to one of the one or more Node Bs and comprising the determining of the least squares channel metric estimates, the identifying of the signal taps and the noise taps, and the performing of the minimum mean square error scaling, and further comprising updating contents of an interference buffer based on the signal taps and the noise taps; and

means for iterating a second loop for a second number of iterations, wherein the second loop comprises the iterating of the first loop and further comprises updating the received signal based on the contents of the interference buffer after the iterating of the first loop.

23. The apparatus of claim 22, further comprising:

means for performing noise power estimation based on edge taps in a shift, wherein the shift includes a number of taps within the tapped delay line channel estimate and corresponding to a midamble shift.

24. The apparatus of claim 22, further comprising:

means for determining shifts that correspond to a same beam-forming pattern; and

means for updating the least squares channel metric estimates by combining respective least squares channel metric estimates in the shifts that correspond to the same beam-forming pattern.

25. The apparatus of claim 24, wherein the means for determining the shifts that correspond to the same beam-forming pattern comprises: means for determining a strongest shift with a largest power in a set of candidate shifts;

means for determining a correlation value between the strongest shift and a candidate shift from remaining shifts in the set of candidate shifts; and

means for determining, based on the correlation value, whether the candidate shift corresponds to the same beam-forming pattern as the strongest shift.

26. The apparatus of claim 24, wherein the means for updating the least squares channel metric estimates comprises:

means for performing maximal ratio combining (MRC) to combine the respective least squares channel metric estimates in the shifts that correspond to the same beam-forming pattern.

27. The apparatus of claim 22, wherein the means for identifying the signal taps and the noise taps comprises:

means for determining a clean tap identifier within the tapped delay line channel estimate and obtained in a previous iteration of the first loop; and

means for performing tap cleaning at a location of the clean tap identifier.

28. The apparatus of claim 27, wherein the means for determining the clean tap identifier comprises:

means for performing filtering of tap power and temporal correlation for each tap within the tapped delay line channel estimate in a last iteration of the first loop.

29. The apparatus of claim 28, wherein the filtering is performed according to a filter metric that is based on a sum of a filtered tap power and an absolute value of a tap temporal correlation for each tap within the tapped delay line channel estimate.

30. The apparatus of claim 22, further comprising: means for determining a power for each of one or more shifts, wherein each of the one or more shifts includes a number of taps within the tapped delay line channel estimate and corresponding to a midamble shift; and

means for cleaning a shift in the one or more shifts by setting tap values equal to zero for taps in the shift when the shift has a power less than a maximum shift power multiplied by a threshold.