Abstract:
A receiver that provides interference cancellation in conjunction with RAKE processing. Signal parameters corresponding to each of a plurality of fingers corresponding to RAKE processing are maintained. Synthesized pilot signals are estimated using the signal parameters by interpolating waveforms for respective ones of the plurality of synthesized pilot signals to a common sampling lattice of the received set of data, and are then cancelled out. According to another aspect, a receiver ensures completion of a time-critical process such as signal demodulation and adaptively applies a non-time-critical process such as interference cancellation to the extent that computational resources become available subject to ensuring the completion of the time-critical process.

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
   This application is a continuation in part of U.S. application Ser. No. 10/765,202, entitled “Sub-Symbol Parallel Interference Cancellation” and filed on Jan. 28, 2004 now U.S. Pat. No. 7,099,378, which claims the benefit under 35 U.S.C. 119(e) of provisional application 60/443,655, filed Jan. 30, 2003, entitled “Multi-User Detection Techniques for CDMA.” The entire contents of these applications are hereby incorporated by reference. 

   BACKGROUND OF THE INVENTION 
   1. Field of the Invention 
   This invention relates generally to wireless communications and more particularly to interference cancellation in a CDMA receiver. 
   2. Description of the Related Art 
   Code Division Multiple Access (“CDMA”) provides an effective communications technique for several users to share a communications channel. Unfortunately, when the channel becomes overcrowded, the conventional CDMA receiver performs poorly and multiple access interference (“MAI”) can severely degrade performance. Although the optimal maximum likelihood receiver in this case is easy to describe, it is nearly impossible to implement. 
   Various conventional techniques examine interference cancellation at the symbol level. Symbol-level matched filters can provide a sufficient statistic for multi-user detection (“MUD”) in an additive white Gaussian noise channel. This well known result concludes that the optimal user bit estimation procedure can be written at the symbol level. Accordingly, these various conventional MUD approaches use symbol-level estimation and cancellation approaches. However, these symbol-level techniques are only approximations to the optimal estimator, and there is no guarantee that these symbol level approximations fully exploit the signal structure. 
   Additionally, conventional procedures can involve the following computationally expensive process for canceling interference: (1) interpolating the data for each source (base station) to the sampling lattice of the signature waveform (chip center), (2) computing the bit estimates for each user, (3) synthesizing the entire symbol&#39;s binary waveform and (4) interpolating the waveform of the whole symbol back to the sampling grid of the data to perform the cancellation. 
   Some sample-level approaches have been proposed. One example uses a continuous time (i.e., analog) maximum likelihood estimator (“MLE”) approach, which can be used as continuous decision feedback. This MLE approach can be purposed as a single-stage analog process using filters controlled by relative user power levels. Although relatively easy to implement, these approaches are not a good theoretical match to the interference cancellation problem. To remedy such shortcomings, linear minimum mean squared error (MMSE) techniques, such as those based on standard applications of the Kalman filter and other least-squares generalizations, could be used to reduce un-cancelled interference. These techniques fully couple the users (resulting in large matrix computations) and perform interference cancellations in the innovation term in the filter. Accordingly, they remain quite computationally expensive. 
   Another issue with regard to interference cancellation is the implementation of RAKE receivers. The RAKE technique, which is used in many conventional CDMA handsets, uses multiple base band correlators to separately process several signal multi-path components. This processing is said to be performed by fingers. Each finger is basically an individual demodulator whose timing is adjusted for a particular multi-path component. During soft-handoff, one of these fingers is actually tuned to a neighboring base station. The output of each finger is typically soft information. The receiver typically combines the soft information from each of the fingers to produce a single log-likelihood ratio for each of the transmitted bits. Various interference cancellation problems remain with RAKE implementations, including interference that is introduced by pilot signals that may or may not correspond to processing that is being performed for a finger. 
   Still another problem with conventional interference cancellation is the inefficient use of computational resources, which are often limited in applications such as mobile handsets. Interference cancellation techniques and corresponding computational architectures have been found to be too inflexible to take full advantage of the computational capabilities of a system in which cancellation is being performed, at various stages of signal processing. 
   Thus, there remains a need for more efficient interference cancellation, particularly in receivers that implement RAKE processing, and for more efficient allocation of computational resources in typical applications. 
   SUMMARY OF THE INVENTION 
   According to one aspect, the present invention provides for the cancellation of interference in a receiver that implements RAKE processing. Data is received as a plurality of discrete values produced at a sub-symbol interval that is less than a full symbol period. A set of signal parameters such as the code delay and complex amplitude are maintained for each of a plurality of fingers corresponding to RAKE demodulation provided in the receiver. A plurality of synthesized pilot signals are estimated based upon the received data and the signal parameters, preferably by interpolating waveforms for respective ones of the plurality of synthesized pilot signals to a common sampling lattice of the received data. The estimated pilot signals are then canceled from the input signal. 
   According to another aspect, the present invention provides adaptive allocation of computational resources in real time processing of a communications signal. In this aspect, a stream of data corresponding to a communication signal is received. The stream of data is subject to a time-critical process that includes demodulation of the signal, as well as a non-time-critical process such as interference cancellation. Specifically, the completion of the time-critical process for the received stream of data is ensured, whereas the non-time-critical process is adaptively applied, subject to ensuring the completion of the time-critical process. 
   In one embodiment, ensuring completion of the time-critical process and adaptively applying the non-time-critical process is carried out by providing a series of buffers for blocks of data that are processed. This may comprise loading a first buffer with a first block from the stream of input data, a second buffer with a second block from the stream of input data, and ensuring the completion of the time-critical process for the block in the first buffer prior to receiving an indication that a third buffer has been filled with a third block of data from the stream of input data. 
   It may further comprise applying the non-time-critical process to the second block following completion of the time-critical process for the first block but prior to the indication that the third buffer has been filled with the third block of data. 
   The time-critical process may also include code tracking for RAKE fingers in addition to demodulation. There, the buffering may include loading a first buffer with a first block from the stream of input data, a second buffer with a second block from the stream of input data, and ensuring the completion of demodulation for the first block and code tracking for the second block prior to receiving an indication that a third buffer has been filled with a third block of data from the stream of input data. 
   The present invention can be embodied in various forms, including computer implemented methods, computer program products, communications systems and networks, receivers, transmitters and transceivers, and the like. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
     These and other more detailed and specific features of the present invention are more fully disclosed in the following specification, reference being had to the accompanying drawings, in which: 
       FIG. 1  is a schematic diagram illustrating an embodiment of multiple stage decoupled MUD processing. 
       FIG. 2  is a schematic diagram illustrating an embodiment of a stage of decoupled MUD processing. 
       FIG. 3  is a schematic diagram illustrating an embodiment of a decoupled MUD processing element. 
       FIG. 4  is a block diagram illustrating an embodiment of a receiver that includes pilot cancellation corresponding to inactive fingers in accordance with the present invention. 
       FIG. 5  is a block diagram illustrating an embodiment of a receiver that includes elements for adaptively allocating computational resources in interference cancellation processing in accordance with the present invention. 
       FIG. 6  is a flow diagram illustrating an embodiment of a process for adaptively allocating computational resources in accordance with the present invention. 
   

   DETAILED DESCRIPTION OF THE INVENTION 
   In the following description, for purposes of explanation, numerous details are set forth, such as flowcharts and system configurations, in order to provide an understanding of one or more embodiments of the present invention. However, it is and will be apparent to one skilled in the art that these specific details are not required in order to practice the present invention. 
   The previously mentioned application Ser. No. 10/765,202, entitled “Sub-Symbol Parallel Interference Cancellation” implements multi-user detection to cancel multi-access interference and thereby improve reception. According to one aspect of the present invention, the signal-to-interference ratio is improved by canceling only the pilot channels, thereby avoiding the need to estimate the transmitted bits. The pilot channels are observed as channels with known bits. Preferably, this performance improvement implements the interpolation technique described in application Ser. No. 10/765,202, which allows the cancellation to be effectively performed at the sampling lattice of the sampled data. 
     FIGS. 1-3  illustrate an example of the interpolation technique in multi-user detection (MUD) applications. Specifically,  FIGS. 1-3  are schematic diagrams that respectively illustrate multiple stage decoupled MUD processing  100 , a single stage of MUD processing  200  in more detail, and a MUD processing element  300  in still more detail. The schematic diagrams illustrate both the flow of such processing as well as an embodiment of modular architecture for the same. 
     FIG. 1  illustrates an embodiment of multiple stage decoupled MUD processing  100 , particularly showing how pilot interference is cancelled and then applied in a multistage setting (other implementations can use one stage). The multiple stages may apply the same decoupled MUD algorithm, or, in a hybrid setting, may use different MUD algorithms for the different stages. Initially, pilot, preamble, and mid-amble information is processed  102 , if present. Information such as timing and channel equalization is shared with other blocks as needed, since in many settings multiple users will share pilots. The pilot/preamble/mid-amble signals are also reconstructed and used to cancel  104  their contribution to multi-access interference, resulting in y cp (t), the base band signal after cancellation of pilots. This signal is provided to the first stage of decoupled MUD  106 , which estimates ĉ k (t) and other user state information as needed to provide transformation between stages. This process is described in more detail in  FIG. 2 . With a one symbol delay  112 , the 1 st  stage symbol estimates (and supporting data) are used to seed the 2 nd  stage MUD  108 , and so on. The final stage MUD  110  provides the soft decision outputs. 
   In the context of this example, the pilot information is estimated and the pilot signal is cancelled before user multi-access interference is estimated and removed. This is suggested when the pilots are strong enough to estimate the needed information. In some cases, the pilot information should be re-estimated and pilot signals re-cancelled after the intermediate stages of interference cancellation. This is advantageous, for example, when near-far problems cause weak pilots to be obscured by strong pilots and user signals. 
     FIG. 2  illustrates an embodiment of a stage of MUD processing  200 . Based on estimates ĉ k (t) of the constellation symbol, the interference cancellation is achieved by subtracting  202  the current interference estimate from the pilot-less base band signal to form i(t), the innovation signal. This innovation signal represents the original signal y(t) with all known multi-access interference removed. The separate MUD processing units are coupled only through this interference cancellation; inside of MUD processing units, the contribution of the un-cancelled interference from other users is viewed as additive noise. Scalar equations for each MUD processing unit then result, in contrast to standard approaches that result in large matrix equations. 
   The interference cancellation occurs on the discrete sub-symbol sampling lattice, instead of using interpolation to move these measurements to chip center for each user or using symbol-level sampling. The decoupled processing units  204   a - c  use i(t) and any pilot/preamble or mid-amble information to produce an estimate ĉ k (t+1)h k (t+1) for this user&#39;s contribution to MAI at the next sample time. 
     FIG. 3  illustrates an embodiment of a decoupled MUD processing element  300 . Again, the coupling of separate users&#39; processing units occurs through the innovation i(t), and the signal reconstruction ĉ k (t+1)h k (t+1) occurs at the discrete sub-symbol timescale which is common for each user&#39;s processing unit. The signature waveform synthesis module  302  uses equalization and timing information, if available, from embedded pilots, preambles, mid-ambles, and so on. Through application of a one time step delay  304 , the decoupled MUD processor  306  and signal reconstruction  310  share a single calculation of h k (t+1). The decoupled MUD Processor  306  uses its internal state information and the new measurement 
               y   k     ⁡     (   t   )       =       y   ⁡     (   t   )       -       ∑     p   =   1     p     ⁢           ⁢         y   ^     p     ⁡     (   t   )         -       ∑       l   =   1     ,     l   ≠   k       K     ⁢         h   k     ⁡     (   t   )       ⁢         c   ^     k     ⁡     (   t   )           +     v   ⁡     (   t   )               
to make an estimate of the constellation symbol ĉ k (t+1), where v(t) represents noise. The addition  308  of the estimated multi-access interference ĉ k (t)h k (t) restores the contribution of user k and simplifies the algorithm flow to produce y k (t) in the decoupled MUD processing. Although one embodiment is described, other functionally equivalent designs can be used for  FIGS. 2-3 .
 
   Another aspect of this technique is that the residual term 
               ∑     p   =   1     p     ⁢     (         y   p     ⁡     (   t   )       -         y   ^     p     ⁡     (   t   )         )       +       ∑       l   =   1     ,     l   ≠   k       K     ⁢         h   k     ⁡     (   t   )       ⁢     (         c   k     ⁡     (   t   )       -         c   ^     k     ⁡     (   t   )         )         +     v   ⁡     (   t   )             
is viewed as additive noise during signal processing, which leads to substantial savings in computational complexity when compared to fully coupled techniques. The internal states of the decoupled processor maintain the information needed to generate an estimate of the constellation point ĉ k (t) at each sub-symbol time step t. The decoupled MUD processor block produces an estimate at each t, instead of waiting until the end of a symbol period. This significantly improves cancellation at each pass and improves computational efficiency by allowing reuse of signature waveforms for both demodulation and reconstruction even when applying more traditional algorithms (such as classic parallel interference cancellation) in the decoupled MUD processor. In the signature waveform synthesis module  302 , the signature waveform is interpolated to the sub-symbol sampling lattice of the data, rather than interpolating the data y k (t) to a user k-based sampling grid, such as chip center. This produces a substantial reduction in complexity in many cases, since the h k (t+1) interpolation can often be implemented with binary lookup tables, in contrast to fixed point filters for interpolating y k (t) to a different chip center grid for each user.
 
   As indicated above, one aspect of the invention involves canceling pilots with code offsets that are not among the currently active fingers.  FIG. 4  is a schematic diagram illustrating an embodiment of a receiver  400  that includes pilot cancellation corresponding to inactive fingers in accordance with the present invention. Generally, the receiver  400  accommodates a determination of the pilots that are not being used by any currently active finger, and corresponding cancellation of those pilots (sometimes one, possibly more). In conjunction with the described interpolation technique that is also implemented by the receiver  400 , a useful interference cancellation is accommodated at a reasonable computational cost. 
   The illustrated receiver  400  includes a pilot acquisition module  402 , code tracking/channel estimation (CTCE) modules  404 , pilot synthesis modules  406 , a pilot cancellation module  408 , RAKE demodulators  410 , and a coherent combination module  412 , which is a conventional module that is used to coherently add the signals from the fingers. 
   The receiver  400  internals, including the described functionality, may be provided as software, hardware, firmware, or any possible combination of hardware, firmware and/or software. The receiver  400  may also be variously implemented using an Application-Specific Integrated Circuit (including System-on-a-Chip (SoC) embodiments), on a Digital Signal Processor, or on any system that includes elements for executing instructions stored in memory. Implementation may depend on ease of integration with the overall system design. The receiver  400  may also be provided in conjunction cellular phones that implement conventional housings and related equipment such as antennas, power supplies, and displays. 
   The pilot acquisition module  402  determines the code delay of each pilot. The CTCE modules  404  maintain the code delay, Doppler offset, and complex amplitude of each pilot. The pilot acquisition module  402  and CTCE modules  404  may respectively implement any conventional technology for code delay determination and maintenance of the code delay, Doppler offset and complex amplitude. The pilot synthesis modules  406  produce replicas of the transmitted waveforms at the estimated code delays, Doppler offsets and complex multiplied by the channel&#39;s estimated complex amplitude, and the pilot cancellation module  408  removes these pilots from the original signal. The RAKE demodulators  410  respectively perform the demodulation of the provided signals. 
   In CDMA Standards, such as IS-95 and CDMA2000, each base station transmits a pilot channel. In the case of those standards, the pilot channel transmits a known periodic pseudo-random sequence of 32,768 chips. The pilot acquisition module  402  correlates a portion of the received signal with a portion of the known pilot signal at each of the possible positions and if the amplitude of the correlation is strong enough, it determines that a base station exists at that offset. In this fashion, the receiver  400  attempts to communicate with the base station whose pilot has the strongest correlation. Nearby base stations are typically required to have a minimum offset because in the case of multi-path, the reception from a different path of base stations transmission would appear as another pilot several chips away from the strongest. The CTCE modules  404  are each equipped to perform code tracking on the strongest pilot and some of its multi-path components. 
   The pilot acquisition module  402  continuously scans for new pilots, and often scans those positions which were strong but not the strongest because these represent nearby base stations that could potentially become the strongest and used in soft handoff. There is a threshold called T_ADD when a pilot becomes strong enough to be involved in soft handoff. When this happens, the receiver  400  can go into soft handoff mode where it can simultaneously receive its transmission from two base stations. When the receiver  400  is not in soft handoff mode, it only receives its signal from one base station. 
   Many existing receivers maintain code tracking on the strongest pilot and two multi-path pilots, which have nearby offsets. The code tracking system for each of the three pilots combined with the demodulator for the information channel received on each of the three components are called fingers. In the case where the receiver tracks the pilot and demodulates an information channel from three different multi-path components, it is said that the RAKE receiver has three fingers. The demodulated soft information from each of the three fingers is coherently combined to improve the demodulated signal-to-interference ratio leading to a lower error rate. 
   In soft handoff mode, instead of tracking and demodulating the signal from one of the multi-path components, one of the fingers instead tracks and demodulates the signal from another base station. This allows the network to perform soft handoff between two base stations. 
   To accommodate this functionality, the code delay, amplitude, phase and Doppler offset of the corresponding multi-path component are typically maintained for each finger. The receiver  400 , particularly through the pilot synthesis modules  404  and pilot cancellation module  406  uses this information to cancel the interference from the pilot signals in the received signal, preferably using the above described interpolation technique. The allows the RAKE receiver  408  to see significant improvement in signal-to-interference ratio at its input. The pilot cancellation functionality may be undertaken to cancel as many pilots as can be afforded according to design constraints and the computational capabilities of the receiver  400 . 
   In parallel, the cancellation technique may also be implemented by additional fingers to track other pilots (or multi-paths), and to also cancel these pilots from the input signal, to provide further cancellation of unwanted pilots. 
   For ease of description, and in some embodiments, the fingers are separated into code tracking units and demodulators. Each of the code tracking modules  404  uses a delay-locked loop, also called an early-late gate, to maintain the code delay. Each unit also estimates the amplitude and phase (or real and imaginary) parts of the channel, and preferably the Doppler offset. Preferably, there is a code-tracking unit for each component (e.g., pilot) for which cancellation is to be performed. The RAKE demodulators  410  operate on the interference-cancelled signal and decode the information channel at one of several offsets. As indicated in the figure, in one embodiment there is one code-tracking unit per demodulator. Alternatively, there could be more code tracking units than there are demodulators, to track additional pilots for cancellation. It should be understood that multiple code tracking units and demodulators may be conceptual modules respectively found within single “code tracking” and “demodulation” modules that perform the described processes. 
   In order to cancel pilot signals, the code delay, amplitude, phase and Doppler Offset (if not available, assume 0) of each component are sent to a synthesis unit. The code delay may be to an accuracy, such as 1/16th of a chip. In order for the synthesis unit to synthesize the pilot waveforms at the sampling periods of the incoming waveform, a fractional interpolation unit is used. The details of this fractional interpolation approach are described in connection with  FIGS. 1-3  above. 
   Another aspect of this invention, which will be useful particularly where information bearing channels are cancelled, is the adaptive allocation of computational resources. Many receivers are implemented in software in a processor. In a typical system, the receiver processing must be real-time so the processing of a block of data is performed using a double buffer. In this case, one buffer is being filled with input data, while the receiver processes the other. The receiver must finish the processing before the input data buffer is filled, because it must release its data buffer for more input samples. When the input data buffer is filled, an interrupt is generated, and the receiver begins processing the new data buffer, and the previous data buffer is filled with input. When the receiver finishes processing a data buffer, it typically terminates its process and the real-time operating system or kernel can allow other functions to be performed. 
   In the present invention, the input blocks are triple buffered. The processing blocks may be referred to as “blocks”, “buffers” or the like.  FIG. 5  is a block diagram illustrating an embodiment of a receiver system  500  that includes elements for adaptively allocating computational resources in interference cancellation processing in accordance with the present invention. The receiver system  500  preferably implements software, but may also comprise hardware or firmware, or any combination of hardware, firmware and software elements. Although one modular breakdown is illustrated, it is noted that the same functionality may be provided by a system having greater, fewer, or differently named components. 
   The system is shown to include a processor  502  as well as a memory  504  configured to include a real time receiver module  506  that further includes a time-critical processing module  508  and a non-time-critical processing module  510 . The real time receiver module  506  may also include additional conventional components that are not necessary for an understanding of this aspect of the present invention. A buffer module  512  manages the loading of buffers that are processed, with Buffer 0, Buffer 1 and Buffer 2 conceptually indicated. 
   Consider that the blocks are indexed so Buffer N+2 follows Buffer N+1 which follows Buffer N. While Buffer N+2 is being loaded, the real-time receiver process runs the RAKE demodulator on Buffer N and performs the required Code Tracking for the RAKE fingers for Buffer N+1. When the real-time receiver process finishes, the processor can use the remaining cycles to process Buffer N+1 to cancel the pilots associated with the fingers, and perform additional code tracking and/or cancellation on other pilots. If there are enough excess cycles, the receiver also performs multi-user detection and interference cancellation of information bearing channels as previously described, and described further in application Ser. No. 10/765,202.This can be performed until an interrupt is generated by the completed Buffer N+2, in which case the extra cancellation is halted and the real-time receiver process begins running the RAKE demodulator on Buffer N+1 and the required Code Tracking on Buffer N+2, while Buffer N is loaded with the next block, which was the same size block conceptually occupying Buffer N+3. The net result is that depending upon the processor loading on other processes such as the display or other functions, the receiver can adapt the amount of interference cancellation to make optimal use of the computational resources. 
   Those processes that are needed to allow a device to provide viable communications functionality should be considered as time-critical processes. For example, a cellular phone provides voice communications. To accommodate this, demodulation is a time-critical process. CTCE for the pilots of the fingers is also a time-critical process. Interference cancellation (and, optionally, further code tracking for additional pilots) is a non-time-critical process. Time-critical and non-time-critical processes may be determined according to expected operation and design considerations. Other examples of time-critical processing for a cellular phone may be decoding of the voice signal, or anything that is needed to make the phone operate like a phone. Other examples of non-time critical processing may include processes like image processing and maintenance to install new software. 
   Conceptually this aspect of the present invention may be thought of as using three block sized buffers to accommodate three types of tasks, namely collecting a block of data, performing non-time-critical processing, and performing time-critical processing. The first task is collecting data that needs to be processed and may also be referred to as data acquisition. The third task is the processing that must be performed to provide viable functionality. 
   This aspect of the present invention provides a system that accommodates as much interference cancellation as can be accomplished during periods where time-critical processing is not necessary. Specifically, if the processor has completed the time-critical processing on block 3 before it is required to perform the time-critical processing on block 2, then additional non-critical time processing may be applied to block 2 before it must be passed along for time-critical processing. This allows the system  500  to improve the interference cancellation that is performed on a block of data, by applying more computational resources to such a task when they become available. 
     FIG. 6  is a flow diagram illustrating an embodiment of a process  600  for adaptively allocating computational resources in accordance with the present invention. A timeline indicates various junctures at “K” intervals, namely time 0, K, 2K, 3K, 4K, etc. K will typically be an integer number of symbols in units of chips. One example is 512 chips, which corresponds to 8 symbols according to the IS95 standard. 
   The buffer is loaded by an A/D converter. Various actions are illustrated along the time line, starting at time 0. the A/D converter is illustrated as loading Buffer 0 with data from time 0 through point K. When the buffer is loaded, the processor is interrupted to indicate that the data is ready for processing. 
   Note that the timeline of  FIG. 6  is somewhat simplified for ease of illustration. Accommodation for delays or clocking of results completed elsewhere. Thus, for example, the loading of Buffer 0 may actually be performed from 0 through K −  to leave one cycle for such an accommodation. Loading the Buffer 0 as described is the first “data acquisition” task as described above. Also, although discrete milestones and actions are illustrated, it should be understood that the sequence of loading and allowing access to the processor may be variously provided, such as by using a DMA coprocessor that begins moving buffer content into memory when a half full flag indicates that the buffer is half full. 
   In the first iteration of the process, the data must be loaded before the other tasks are undertaken. In subsequent iterations, the various tasks will be simultaneously undertaken, as described in connection with the “refilling” of Buffer 0 (step  618  ) below. 
   From time K through 2K, the non-time-critical interference cancellation is applied  604  to the data in Buffer 0, and Buffer 1 is loaded  606  with the next sequential set of data. Although any interference cancellation may be performed, in one embodiment the previously described sub-symbol parallel interference cancellation is performed on the data. Other examples of interference cancellation include but are not limited to pilot-only cancellation, serial interference cancellation, partial parallel interference cancellation, etc. 
   From time 2K through 3K, the A-D converter populates  610  Buffer 2, and time-critical demodulation is initiated and applied  608  to the data in Buffer 0. At the same time, any processing time prior to the interrupt at time 3K is used for the application  614  of non-critical interference calculation to the data in Buffer 1 as indicated. For ease of illustration, a discrete indication that time-critical demodulation has been completed  612  and a subsequent initiation of the application  614  of the non-critical interference calculation is provided. The illustration indicates how a chunk of time remains in period 2K-3K despite the allocation of computational resources to fully complete the time-critical component of processing. There may be instances where there is not a discrete, shared end-point for the critical processing, and starting-point for non-critical processing. 
   Moving along the timeline, from 3K to 4K, buffer 0 can again be loaded  618  since the time-critical demodulation of the data contained therein has been completed. Time-critical demodulation is applied  616  to the data in Buffer 1. Finally, as described regarding the previous buffers in connection with the preceding time period, remaining processing resources prior to time 4K are allocated to application  622  of non-critical interference cancellation to the data in Buffer 2. It is again shown following completion  620  of time-critical processing, but the guaranteed allocation of resources to time-critical processing, and corresponding allocation of remaining resources in the period to non-time-critical processing may be dispersed throughout the period if desired. For example, shared processing during a K length period that guarantees the completion of the time-critical processing and allows the non-time-critical processing during some remainder of the period is equally applicable in accordance with embodiments of the present invention. 
   Thus embodiments of the present invention produce and provide improved interference cancellation in a CDMA communications environment, particularly in the context of RAKE processing, and provide improved allocation of computational resources. Although the present invention has been described in considerable detail with reference to certain embodiments thereof, the invention may be variously embodied without departing from the spirit or scope of the invention. Therefore, the following claims should not be limited to the description of the embodiments contained herein in any way.