Patent Document

CROSS REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation-in-part of U.S. patent application Ser. No. 12/548,749 filed Aug. 27, 2009. 
    
    
     FIELD OF THE INVENTION 
     This invention relates to Wireless Mobile Communications system implementing Beam-Steering Phases Array Antenna. More particularly, the invention relates to a green-energy technology of wireless mobile system having a wireless mobile Terminal transmits unidirectional signals directly to the Base Station as opposed to transmitting multi-directional signals. 
     This invention also relates to MIMO system Wireless Baseband Processors and Forward Error-Correction (FEC) Codes (Turbo Codes Decoder) for 3 rd  Generation (3G) Wireless Mobile Communications. More particularly, the invention relates to a very high speed MIMO Baseband Processor sub-systems implementing diversity processing of multipath signals from multiple antenna and pipelined Max Log-MAP decoders for 3G Wideband Code Division Multiple Access (W-CDMA), 3G Code Division Multiple Access (CDMA2000) and Wireless LAN (WLAN). 
     BACKGROUND OF THE INVENTION 
     Beam Steering Phased Array Antenna implements an array of fixed radiation elements for transmitting signals, wherein phase shifters associates with various radiation element varies in small steps creating beam steering effect. 
     Diversity processing computes signals from two or more separate antennas using so-called “multipath” signals that arrive at the terminal via different routes after being reflected from buildings, trees or hills. Diversity processing can increase the signal to noise ratio (SNR) more than 6 dB, which enables 3G systems to deliver data rates up to 200 Mbit/s. A multiple-input multiple-output (MIMO) employed multiple antennas at both transmitter and the receiver for data transmission. The MIMO system can provide improved performance over fading channel and multi-path channel. 
     The Orthogonal Frequency Division Multiplexing is a technique used to divide the broadband channel into sub-channels where multiple adjacent channels transmit their carriers&#39; frequency, which are orthogonal to each other. The sum of all carriers can be transmitted over the air to the receiver where each channel&#39;s carrier can be separated without loss of information due to interferences. 
     Turbo Codes decoding is based upon the classic forward error correction concepts that include the use of concatenated Decoders and Interleavers to reduce E b /N 0  for power-limited wireless applications such as digital Wireless Mobile Communications. 
     A Turbo Codes Decoder is an important part of baseband processor of the digital wireless communication Receiver, which was used to reconstruct the corrupted and noisy received data and to improve BER (10 −9 ) throughput.  FIG. 1  shows an example of a diversity processing wireless systems with a M-Channels Baseband Processor sub-systems  12  which decodes signals RX( 0 ), RX( 1 ) to RX(M−1) from multiple Receivers  11  and multiple Antennas  13 , and sends decoded data to the Media Access Control (MAC) layer  14 . The signals received from two or more separate antennas  13  using so-called “multipath” signals that arrive at the terminal via different routes after being reflected from buildings, trees or hills pass through two or more Receivers  11  to produce multiple orthogonal signals RX( 0 ) to RX(M−1) for the M-Channels Baseband Processor sub-systems  12 . 
     DESCRIPTION OF PRIOR ART 
     As shown in  FIG. 27 , the wireless mobile terminal  271  transmits omni-directional signals where signal waves travel in all directions. However, only small portion of signal waves that travel directly to the base-station  272  are really used for transmitting information between the mobile terminal  271  and the base-station  272 .  FIG. 28  shows a signal wave lobe  281  in vertical pattern side view.  FIG. 29  shows signal wave lobe  291  in horizontal pattern top view where signal waves radiate in all directions in 360° circle. 
     A widely used Forward Error Correction (FEC) scheme is the Viterbi Algorithm Decoder in both wired and wireless applications. A drawback of the Viterbi Algorithm Decoder is that it requires a long wait for decisions until the whole sequence has been received. A delay of six times the memory processing speed of the received data is required for decoding. One of the more effective FEC schemes, with higher complexity, uses a maximum a posteriori (MAP) algorithm to decode received messages. The MAP algorithm is computationally complex, requiring many multiplications and additions per bit to compute the posteriori probability. A major difficulty with the use of the MAP algorithm has been the implementation in semiconductor ASIC devices. The complexity of the multiplications and additions slow down the decoding process and reduce the throughput data rates. Furthermore, even under the best conditions, multiplication operations in the MAP algorithm requires implementation using large circuits in the ASIC. The result is costly design and low performance in bit rates throughput. 
     Recently, the 3 rd  Generation Partnership Project (3GPP) organization introduced a new class of error correction codes using parallel concatenated codes (PCCC) that include the use of the classic recursive systematic constituent (RSC) Encoders and Interleavers as shown in  FIG. 3 . An example of the 3GPP Turbo Codes PCCC with 8-states and rate 1/3 is shown in  FIG. 3 . Data enters the two systematic encoders  31   33  separated by an interleaver  32 . An output codeword consists of the source data bit followed by the output bits of the two encoders. 
     Other prior work relating to error correction codes was performed by Berrou et al., describing parallel concatenated codes which are complex encoding structures that are not suitable for portable wireless device. Another U.S. Pat. No. 6,023,783 to Divsalar et al. describes an improved encoding method over Berrou et al., using mathematical concepts of parallel concatenated codes. However, patents by Berrou et al., Divsalar et al., and others only describe the concept of parallel concatenated codes using mathematical equations which are good for research in deep space communications and other government projects, but are not feasible, economical, and suitable for consumer portable wireless devices. In these prior systems, the encoding of data is simple and can be easily implemented with a few “xor” and flip-flop logic gates. But decoding the Turbo Codes is much more difficult to implement in ASIC or software. The prior art describes briefly the implementation of the Turbo Codes Decoder which are mostly for deep space communications and requires much more hardware, power consumption and costs. 
     All the prior art Turbo Codes fail to provide simple and suitable methods and architectures for a Turbo Codes Decoder as it is required and desired for 3G cellular phones and 3G personal communication devices, including the features of high speed data throughput, low power consumption, lower costs, limited bandwidth, and limited power transmitter in noisy environments. 
     SUMMARY OF INVENTION 
     The present invention is directed to a wireless mobile system implementing Beam Steering Phased Array Antenna  331  having an array of [N×N] antennas  332  mounting in the backside of the wireless mobile Terminal  361  transmits unidirectional signals  343  directly to the Base Station as opposed to transmitting multi-directional signals. The present invention wireless mobile system implementing beam-steering phased array antenna  331 , wherein the phases of the signals fed to the array antenna elements are varied by the phase shifters  342  in programmable values calculated by the Digital Signal Processing Phase Processor  341  for transmitting signal waves. Accordingly, several objects and advantages of the wireless mobile system implementing Beam Steering Phased Array Antenna are: 
     Unidirectional signal waves  343  are transmitted directly to the base-station  272 . 
     Only unidirectional signal waves lobe  321  radiate toward the base-station  272  would greatly reduce the total energy as supposed to radiate in all direction. 
     The present invention is directed to a MIMO Diversity M-channels Baseband Processor sub-system using diversity processing to improve error-rate of data transmission and to implement a more efficient, practical and suitable architecture and method to increase the signal to noise ratio (SNR), and to achieve the requirements for wireless systems, including the features of higher speed data throughput, lower power consumptions, lower costs, and suitable for implementation in ASIC or DSP codes. The diversity is achieved by paring two orthogonal channels for processing multipath data to improve receiver performance output. The present invention encompasses several improved and simplified Turbo Codes Decoder methods and devices to deliver higher speed and lower power consumption, especially for applications. Diversity processing can increase the signal to noise ratio (SNR) more than 6 dB, which enables wireless systems to deliver data rates up to 200 Mbit/s. As shown in  FIG. 2 , an exemplary embodiment of the Diversity M-channels Baseband Processor sub-system  12  utilizes a Diversity processor  22 , an N-point Complex FFT Processor  24 , and a Turbo Codes Decoder  23  for diversity processing. Each Turbo Codes Decoder  23  has two serially concatenated Soft-input Soft-output logarithm maximum a posteriori (SISO Log-MAP) Decoders  42 ,  44 . The two decoders function in a pipelined scheme with delay latency N. While the first decoder is decoding data stored in the second-decoder-Memory  45 , the second decoder performs decoding for data stored in the first-decoder-Memory  43 , which produces a decoded output every clock cycle. As shown in  FIG. 6 , the Turbo Codes Decoder  23  utilizes a Sliding Window of Block N  61  on the Memory  41  to decode data per block N, which improves processing efficiency. The invention presents a method to divide the wireless broadband into multiple sub-channels and uses an Orthogonal Frequency Division Multiplexing method implemented by N-point complex FFT processors to effectively divide the broadband high-speed channel into multiple slow-speed N sub-channels where multiple adjacent channels transmit their carriers&#39; frequency which are orthogonal to each other. The high-speed bit-stream is also sub-divided into multiple slow-speed sub bit-streams. For example, if the total broadband channel capacity is R-Mbps, then the slower sub-channel capacity S-Mbps is equal to (R-Mbps)/N. The slower sub-channel capacity benefits the Turbo Codes baseband processor since it performs much better at a slower bit rate with a greater number of iterations. Each bit-stream is encoded one bit per cycle with the Turbo Codes encoder and then mapped into an 8-PSK constellation point where its I and Q components are mapped into the real and imaginary part of the complex FFT point. Since M is less than or equal to N, channel hopping can be accomplished by assigning a bit-stream to a new channel once its current channel becomes noisy. Accordingly, several objects and advantages of the Diversity M-channels Baseband Processor sub-system  12  are: 
     To implement diversity processing to increase the signal to noise ratio (SNR). 
     To deliver higher speed throughput and be suitable for implementation in application specific integrated circuit (ASIC) designs or digital signal processor (DSP) codes. 
     To utilize SISO Log-MAP decoders for best result and faster decoding and simplified implementation in ASIC circuits and DSP codes with the use of binary adders for computation. 
     To perform re-iterative decoding of data back-and-forth between the two Log-MAP decoders in a pipelined scheme until a decision is made. In such pipelined scheme, decoded output data is produced each clock cycle. 
     To utilize a Sliding Window of Block N on the input buffer memory to decode data per block N for improved pipeline processing efficiency 
     To provide higher performance in term of symbol error probability and low BER (10 −9 ) for 3G applications such as 3G WCDMA, and 3G CDMA2000 operating at very high bit-rate up to 200 Mbps, in a low power, noisy environment. 
     To utilize a simplified and improved SISO Log-MAP decoder architecture, including a branch-metric (BM) calculations module, a recursive state-metric (SM) forward/backward calculations module, an Add-Compare-Select (ACS) circuit, a Log-MAP posteriori probability calculations module, and an output decision module. 
     To reduce complexity of multiplier circuits in MAP algorithm by performing the entire MAP algorithm in Log Max approximation using binary adder circuits, which are more suitable for ASIC and DSP codes implementation, while still maintaining a high level of performance output. 
     To design an improve Log-MAP Decoder using high level design language (HDL) such as Verilog, system-C and VHDL, which can be synthesized into custom ASIC and Field Programmable Gate Array (FPGA) devices. To implement an improve Log-MAP Decoder in DSP (digital signal processor) using optimized high level language C, C++, or assembly language. 
     To utilize an Orthogonal Frequency Division Multiplexing method implemented by N-point complex FFT processors to sub-divide the broadband high-speed channel into multiple slow-speed N sub-channels. 
     Still further objects and advantages will become apparent to one skill in the art from a consideration of the ensuing descriptions and accompanying drawings. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  illustrates a conventional MIMO Receiver Functional Block Diagram which uses Diversity M-channels Baseband Processor sub-system. 
         FIG. 2  illustrates a Diversity M-channels Baseband Processor sub-system. 
         FIG. 3  illustrates a block diagram of a prior-art 8-states 3GPP Parallel Concatenated Convolutional Codes. 
         FIG. 4  illustrates the Turbo Codes Decoder System Block Diagram showing Log-MAP Decoders, Interleavers, Memory Buffers, Hard-decoder, and control logics. 
         FIG. 5  illustrates a Turbo Codes Decoder State Diagram. 
         FIG. 6  illustrates the Block N Sliding Window Diagram. 
         FIG. 7  illustrates a block diagram of the SISO Log-MAP Decoder showing Branch Metric module, State Metric module, Log-MAP module, and State and Branch Memory modules. 
         FIG. 8  illustrates the 8-States Trellis Diagram of a SISO Log-MAP Decoder using the 3GPP 8-state PCCC Turbo codes. 
         FIG. 9  illustrates a block diagram of the BRANCH METRIC COMPUTING module. 
         FIG. 10   a  illustrates a block diagram of the Log-MAP computing for u=0. 
         FIG. 10   b  illustrates a block diagram of the Log-MAP computing for u=1. 
         FIG. 11  illustrates a block diagram of the Log-MAP Compare &amp; Select 1 maximum logic for each state. 
         FIG. 12  illustrates a block diagram of the Soft Decode module. 
         FIG. 13  illustrates a block diagram of the Computation of Forward Recursion of State Metric module (FACS). 
         FIG. 14  illustrates a block diagram of the Computation of Backward Recursion of State Metric module (BACS). 
         FIG. 15  illustrates State Metric Forward computing of Trellis state transitions. 
         FIG. 16  illustrates State Metric Backward computing of Trellis state transitions. 
         FIG. 17  illustrates a block diagram of the State Machine operations of Log-MAP Decoder. 
         FIG. 18  illustrates a block diagram of the BM dual-port Memory Module. 
         FIG. 19  illustrates a block diagram of the SM dual-port Memory Module. 
         FIG. 20  illustrates a block diagram of the Interleaver dual-port RAM Memory. 
         FIG. 21  illustrates a block diagram of the De-Interleaver dual-port RAM Memory. 
         FIG. 22  illustrates a flow chart of an exemplary Turbo Codes Decoder state machine operation. 
         FIG. 23  illustrates a block diagram of the Iterative decoding feedback control. 
         FIG. 24  illustrates a block diagram of the intrinsic feedback Adder of the Turbo Codes Decoder. 
         FIG. 25  illustrates a pre-processor for baseband processor sub-system. 
         FIG. 26  illustrates a Diversity Processor. 
         FIG. 27  illustrates a Handset Terminal transmits signals in multi-direction with omni-directional antenna. 
         FIG. 28  illustrates a Vertical Pattern Side View of radiating waves. 
         FIG. 29  illustrates a Horizontal Pattern Top View of radiating waves. 
         FIG. 30  illustrates a Handset Terminal transmits signals in uni-direction using array-antenna with beam-steering technology. 
         FIG. 31  illustrates a preferred embodiment Vertical Pattern Side View of radiating waves. 
         FIG. 32  illustrates a preferred embodiment Horizontal Pattern Top View of radiating waves. 
         FIG. 33  illustrates a preferred embodiment Array [4×4] Antenna. 
         FIG. 34  illustrates a preferred embodiment Beam Steering Array [N×N] Antenna system. 
         FIG. 35  illustrates a preferred embodiment Transmitter System with Beam Steering Array [N×N] Antenna. 
         FIG. 36  illustrates a preferred embodiment Backside of a Smart-Phone Terminal with Array [4×4] Antenna. 
         FIG. 37  illustrates a preferred embodiment Frontside of a Smart-Phone Terminal with 4 solar-cell panels. 
         FIG. 38  illustrates a preferred embodiment Power Management Logic. 
         FIG. 39  illustrates a preferred embodiment Clocks Management Logic. 
     
    
    
     DETAILED DESCRIPTION 
     Turbo Codes Decoder 
     An illustration of a 3GPP 8-state Parallel Concatenated Convolutional Code (PCCC), with coding rate 1/3, constraint length K=4 is illustrated in  FIG. 3 . An implementation using SISO Log-MAP Decoders is illustrated in  FIG. 4 . 
     In accordance with an exemplary embodiment, a Turbo Codes Decoder block  23  has concatenated max Log-MAP SISO Decoders A  42  and B  44  connected in a feedback loop with Interleaver Memory  43  and Interleaver Memory  45 . 
     Signals R 2 , R 1 , R 0  are received soft decision signals of data path from the system receiver. Signals XO 1  and XO 2  are output soft decision signals of the Log-MAP Decoders A  42  and B  44 , respectively, which are stored in the Interleaver Memory  43  and Memory  45  module. Signals Z 2  and Z 1  are the output of the Interleaver Memory  43  and Interleaver Memory  45 . Z 2  is fed into Log-MAP decoder B  44  and Z 1  is looped back into Log-MAP decoder A  42  through Adder  231 . 
     Each Interleaver Memory  43 ,  45 , shown in  FIG. 20 , includes one interleaver  201  and a dual-port RAM memory  202 . Input Memory block  41 , shown in  FIG. 21 , includes dual-port RAM memory  211 . Control logic module (CLSM)  47  consists of various state-machines, which control all the operations of the Turbo Codes Decoder. The hard-decoder module  46  outputs the final decoded data. 
     More particularly, as illustrated in  FIG. 3 , R 0 , is data bit corresponding to the transmit data bit u, R 1 , is the first parity bit corresponding to the output bit of the first RSC encoder, and R 2 , is interleaved second parity bit corresponding to the output bit of the second RSC encoder. 
     In accordance with the invention, corresponding ones of data bits R 0  is added to the feedback signals Z 1 , then fed into the decoder A. Corresponding ones of data bits R 1  is also fed into decoder A for decoding the first stage of decoding output XO 1 . Z 2  and corresponding ones of R 2  are fed into decoder B for decoding the second stage of decoding output XO 2 . 
     In accordance with the invention, as shown in  FIG. 6 , the Turbo Codes Decoder utilizes a Sliding Window of Block N  61  on the input buffers  62  to decode one block N data at a time, the next block N of data is decoded after the previous block N is done in a circular wrap-around scheme for pipeline operations. In another embodiment, the Sliding Window of Block N is used on the input buffer Memory so that each block N data is decoded at a time one block after another in a pipeline scheme. 
     In accordance with the invention, the Turbo Codes Decoder decodes an 8-state Parallel Concatenated Convolutional Code (PCCC). The Turbo Codes Decoder also decodes a higher n-state Parallel Concatenated Convolutional Code (PCCC) 
     As illustrated in  FIG. 4 , the Turbo Codes Decoder functions effectively as follows: 
     Received soft decision data (RXD[2:0]) is stored in three input buffers Memories  41  to produce data bits R 0 , R 1 , and R 2  that correspond to data words. Each output data word R 0 , R 1 , R 2  contains a number of binary bits. 
     A Sliding Window of Block N is imposed onto each interleaver memory blocks  43 ,  45  to produce corresponding ones output data words. 
     A Sliding Window of Block N is imposed onto each input memory to produce corresponding ones of R 0 , R 1 , and R 2 , output data words. 
     In accordance with the method of the invention, when an input data block of size N is ready, the Turbo Decoder starts the Log-MAP Decoder A, in block  23 , to decode the N input data based on the soft-values of R 0 , Z 1 , and R 1 , then stores the outputs in the Interleaver Memory A. 
     The Turbo Decoder also starts the Log-MAP Decoder B, in block  23 , to decode the N input data based on the soft-values of R 2  and Z 2 , in pipelined mode with a delay latency of N, then stores the output in the Interleaver Memory. 
     The Turbo Decoder performs iterative decoding for L number of times (L=1, 2, . . . , M). 
     When the iterative decoding sequence is complete, the Turbo Decoder starts the hard-decision operations to compute and produce soft-decision outputs. 
     SISO Log-MAP Decoder 
     As shown in  FIG. 7 , SISO Log-MAP Decoders  42 ,  44  include a Branch Metric (BM) computation module  71 , a State Metric (SM) computation module  72 , a Log-MAP computation module  73 , a BM Memory module  74 , a SM Memory module  75 , and a Control Logic State Machine module  76 . Soft-value inputs enter the Branch Metric (BM) computation module  71 , where Euclidean distance is calculated for each branch, the output branch metrics are stored in the BM Memory module  74 . The State Metric (SM) computation module  72  reads branch metrics from the BM Memory  74  and computes the state metric for each state; the output state-metrics are stored in the SM Memory module  75 . The Log-MAP computation module  73  reads both branch-metrics and state-metrics from BM memory  74  and SM memory  75  modules to compute the Log Maximum a Posteriori probability and produce soft-decision output. The Control Logic State-machine module  76  provides the overall operations of the decoding process. 
     As shown in  FIG. 7  which is one example of 3GPP Turbo Codes Decoder, the Log-MAP Decoder  42   44  functions effectively as follows: 
     The Log-MAP Decoder  42 ,  44  reads each soft-values (SD) data pair input, then computes branch-metric (BM) values for all paths in the Turbo Codes Trellis  80  as shown in  FIG. 8   a  (and Trellis  85  in  FIG. 8   b ). The computed BM data is stored into BM Memory  74 . The process of computing BM values is repeated for each input data until all N samples are calculated and stored in BM Memory  74 . 
     The Log-MAP Decoder  42   44  reads BM values from BM Memory  74  and SM values from SM Memory  75 , and computes the forward state-metric (SM) for all states in the Trellis  80  as shown in  FIG. 8   a  (and Trellis  85  in  FIG. 8   b ). The computed forward SM data is stored into SM Memory  75 . The process of computing forward SM values is repeated for each input data until all N samples are calculated and stored in SM Memory  75 . 
     The Log-MAP Decoder  42   44  reads BM values from BM Memory  74  and SM values from SM Memory  75 , and computes the backward state-metric (SM) for all states in the Trellis  80  as shown in  FIG. 8   a  (and Trellis  85  in  FIG. 8   b ). The computed backward SM data is stored into the SM Memory  75 . The process of computing backward SM values is repeated for each input data until all N samples are calculated and stored in SM Memory  75 . 
     The Log-MAP Decoder  42   44  then computes Log-MAP posteriori probability for u=0 and u=1 using the BM values and SM values from BM Memory  74  and SM Memory  75 . The process of computing Log-MAP posteriori probability is repeated for each input data until all N samples are calculated. The Log-MAP Decoder then decodes data by making soft decision based on the posteriori probability for each stage and produces soft-decision output, until all N inputs are decoded. 
     Branch Metric Computation Module 
     The Branch Metric (BM) computation module  71  computes the Euclidean distance for each branch in the 8-states Trellis  80  as shown in the  FIG. 8   a  based on the following equations:
 
Local Euclidean distances values= SD 0* G 0+ SD 1* G 1
 
     where SD 0  and SD 1  are soft-value input data and G 0  and G 1  are the expected input for each path in the Trellis  80 . G 0  and G 1  are coded as signed antipodal values, meaning that 0 corresponds to +1 and 1 corresponds to −1. Therefore, the local Euclidean distances for each path in the Trellis  80  are computed by the following equations:
 
 M 1= SD 0+ SD 1
 
 M 2=− M 1
 
M3=M2
 
M4=M1
 
 M 5=− SD 0+ SD 1
 
 M 6=− M 5
 
M7=M6
 
M8=M5
 
M9=M6
 
M10=M5
 
M11=M5
 
M12=M6
 
M13=M2
 
M14=M1
 
M15=M1
 
M16=M2
 
     As shown in the exemplary embodiment of  FIG. 9 , the Branch Metric Computing module includes one L-bit Adder  91 , one L-bit Subtracter  92 , and a 2′complemeter  93 . The Euclidean distances is computed for path M 1  and M 5 . Path M 2  is 2′complement of path M 1 . Path M 6  is 2′complement of M 5 . Path M 3  is the same path M 2 , path M 4  is the same as path M 1 , path M 7  is the same as path M 6 , path M 8  is the same as path M 5 , path M 9  is the same as path M 6 , path M 10  is the same as path M 5 , path M 11  is the same as path M 5 , path M 12  is the same as path M 6 , path M 13  is the same as path M 2 , path M 14  is the same as path M 1 , path M 15  is the same as path M 1 , and path M 16  is the same as path M 2 . 
     State Metric Computing Module 
     The State Metric Computing module  72  calculates the probability A(k) of each state transition in forward recursion and the probability B(k) in backward recursion.  FIG. 13  shows the implementation of state-metric in forward recursion with Add-Compare-Select (ACS) logic.  FIG. 14  shows the implementation of state-metric in backward recursion with Add-Compare-Select (ACS) logic. The calculations are performed at each node in the Turbo Codes Trellis  80  ( FIG. 8   a ) in both forward and backward recursion.  FIG. 15  shows the forward state transitions in the Turbo Codes Trellis  80  ( FIG. 8   a ).  FIG. 16  shows the backward state transitions in the Turbo Codes Trellis  80  ( FIG. 8   a ). Each node in the Trellis  80  as shown in  FIG. 8   a  has two entering paths: one-path  84  and zero-path  83 , from the two nodes in the previous stage. 
     In an exemplary embodiment, the ACS logic includes an Adder  132 , an Adder  134 , a Comparator  131 , and a Multiplexer  133 . In the forward recursion, the Adder  132  computes the sum of the branch metric and state metric in the one-path  84  from the state s(k−1) of previous stage (k−1). The Adder  134  computes the sum of the branch metric and state metric in the zero-path  83  from the state (k−1) of previous stage (k−1). The Comparator  131  compares the two sums and the Multiplexer  133  selects the larger sum for the state s(k) of current stage (k). In the backward recursion, the Adder  142  computes the sum of the branch metric and state metric in the one-path  84  from the state s(j+1) of previous stage (J+1). The Adder  144  computes the sum of the branch metric and state metric in the zero-path  83  from the state s(j+1) of previous stage (J+1). The Comparator  141  compares the two sums and the Multiplexer  143  selects the larger sum for the state s(j) of current stage (j). 
     The Equations for the ACS are shown below:
 
 A ( k )=MAX [( bm 0+ sm 0( k− 1)), ( bm 1+ sm 1( k− 1)]
 
 B ( j )=MAX [( bm 0+ sm 0( j+ 1)), ( bm 1+ sm 1( j+ 1)]
 
     Time (k−1) is the previous stage of (k) in forward recursion as shown in  FIG. 15 , and time (j+1) is the previous stage of (j) in backward recursion as shown in  FIG. 16 . 
     Log-MAP Computing Module 
     The Log-MAP computing module calculates the posteriori probability for u=0 and u=1, for each path entering each state in the Turbo Codes Trellis  80  corresponding to u=0 and u=1 or referred as zero-path  83  and one-path  84 . The accumulated probabilities are compared and the u with larger probability is selected. The soft-decisions are made based on the final probability selected for each bit.  FIG. 10   a  shows the implementation for calculating the posteriori probability for u=0.  FIG. 10   b  shows the implementation for calculating the posteriori probability for u=1.  FIG. 11  shows the implementation of compare-and-select for the u with larger probability.  FIG. 12  shows the implementation of the soft-decode compare logic to produce output bits based on the posteriori probability of u=0 and u=1. The equations for calculating the accumulated probabilities for each state and compare-and-select are shown below:
 
sum —   s 00= sm 0 i+bm 1+ sm 0 j  
 
sum —   s 01= sm 3 i+bm 7+ sm 1 j  
 
sum —   s 02 =sm 4 i+bm 9+ sm 2 j  
 
sum —   s 03= sm 7 i+bm 15+ sm 3 j  
 
sum —   s 04= sm 1 i+bm 4+ sm 4 j  
 
sum —   s 05= sm 2 i+bm 6+ sm 5 j  
 
sum —   s 06= sm 5 i+bm 12+ sm 6 j  
 
sum —   s 07= sm 6 i+bm 14+ sm 7 j  
 
sum —   s 10= sm 1 i+bm 3+ sm 0 j  
 
sum —   s 11= sm 2 i+bm 5+ sm 1 j  
 
sum —   s 12= sm 5 i+bm 11+ sm 2 j  
 
sum —   s 13= sm 6 i+bm 13+ sm 3 j  
 
sum —   s 14= sm 0 i+bm 2+ sm 4 j  
 
sum —   s 15= sm 3 i+bm 8+ sm 5 j  
 
sum —   s 16= sm 4 i+bm 10+ sm 6 j  
 
sum —   s 17= sm 7 i+bm 16+ sm 7 j  
 
 s 00sum=MAX[sum —   s 00, 0]
 
 s 01sum=MAX[sum —   s 01,  s 00sum]
 
 s 02sum=MAX[sum —   s 02,  s 01sum]
 
 s 03sum=MAX[sum —   s 03,  s 02sum]
 
 s 04sum=MAX[sum —   s 04,  s 03sum]
 
 s 05sum=MAX[sum —   s 05,  s 04sum]
 
 s 06sum=MAX[sum —   s 06,  s 05sum]
 
 s 07sum=MAX[sum —   s 07,  s 06sum]
 
 s 10sum=MAX[sum —   s 10, 0]
 
 s 11sum=MAX[sum —   s 11,  s 10sum]
 
 s 12sum=MAX[sum —   s 12,  s 11sum]
 
 s 13sum=MAX[sum —   s 13,  s 12sum]
 
 s 14sum=MAX[sum —   s 14,  s 13sum]
 
 s 15sum=MAX[sum —   s 15,  s 14sum]
 
 s 16sum=MAX[sum —   s 16,  s 15sum]
 
 s 17sum=MAX[sum —   s 17,  s 16sum]
 
Control Logics—State Machine (CLSM) Module
 
     As shown in  FIG. 7 , the Control Logic module controls the overall operations of the Log-MAP Decoder. The control logic state machine  171 , referred as CLSM, is shown in  FIG. 17 . The CLSM module  171  ( FIG. 17 ) operates effectively as follows. Initially, the CLSM module  171  operates in IDLE state  172 . When the decoder is enabled, the CLSM module  171  transitions to CALC-BM state  173 , where the Branch Metric (BM) module starts operations and monitors for completion. When Branch Metric calculations are completed, referred to as bm-done, the CLSM transitions to CALC-FWD-SM state  174 , where the State Metric module (SM) begins forward recursion operations. When the forward SM state metric calculations are completed, referred to as fwd-sm-done, the CLSM transitions to CALC-BWD-SM state  175 , where the State Metric module (SM) begins backward recursion operations. When backward SM state metric calculations are completed, referred to as bwd-sm-done, the CLSM transitions to CALC-Log-MAP state  176 , where the Log-MAP computation module begins calculating the maximum a posteriori (MAP) probability to produce soft decode output. When Log-MAP calculations are completed, referred to as log-map-done, the CLSM module  171  transitions back to IDLE state  172 . 
     BM Memory and SM Memory 
     The Branch-Metric Memory  74  and the State-Metric Memory  75  are shown in  FIG. 7  as the data storage components for BM module  71  and SM module  72 . The Branch Metric Memory module is a dual-port RAM that contains M− bits of N memory locations as shown in  FIG. 18 . The State Metric Memory module is a dual-port RAM that contains K− bits of N memory locations as shown in  FIG. 19 . Data can be written into one port while reading at the other port. 
     Interleaver Memory 
     As shown in  FIG. 4 , the Interleaver Memory A  43  stores data for the first decoder A  42  and Interleaver Memory B  45  stores data for the second decoder B  44 . In iterative pipelined decoding, the decoder A  42  reads data from Interleaver Memory B  45  and writes results data into Interleaver Memory B  43 , the decoder B  44  reads data from Interleaver Memory A  43  and write results into Interleaver Memory B  45 . 
     As shown in  FIG. 20 , the De-Interleaver memory  41  includes a De-Interleaver module  201  and a dual-port RAM  202 , which contains M− bits of N memory locations. The Interleaver is a Turbo code internal interleaver as defined by 3GPP standard ETSI TS 125 222 V3.2.1 (2000-05), or other source. The Interleaver permutes the address input port A for all write operations into dual-port RAM module. Reading data from output port B are done with normal address input. 
     The Interleaver Memory module uses an interleaver to generate the write-address sequences of the Memory core in write-mode. In read-mode, the memory core read-address is normal sequences. 
     As shown in  FIG. 21 , the Input Buffer Memory  43   45  comprises of a dual-port RAM  211 , which contains M− bits of N memory locations. 
     Turbo Codes Decoder Control Logics—State Machine (TDCLSM 
     As shown in  FIG. 4 , the Turbo Decoder Control Logics module  47 , referred to as TDCLSM, controls the overall operations of the Turbo Codes Decoder. Log-MAP A  42  starts the operations of data in Memory B  45 . At the same time, Log-MAP B starts the operations in Memory A  43 . When Log-MAP A  42  and Log-MAP B  44  finish with block N of data, the TDCLSM  47  starts the iterative decoding for L number of times. When the iterative decoding sequences are completed, the TDCLSM  47  transitions to HARD-DEC to generate the hard-decode outputs. Then the TDCLSM  47  transitions to start decoding another block of data. 
     Iterative Decoding 
     Turbo Codes decoder performs iterative decoding by feeding back the output Z 1 , Z 3  of the second Log-MAP decoder B into the corresponding first Log-MAP decoder A before making decision for hard-decoding output. As shown in  FIG. 23 , the Counter  233  counts the preset number L times. 
     Diversity M-Channels Baseband Processor Sub-System 
     An implementation of a Diversity M-channels Baseband Processor sub-system is illustrated in  FIG. 2  for processing multiple orthogonal received signals RX( 0 ) to RX(M−1) from multipath signals which arrive at the antennas after being reflected from buildings, trees or hills. 
     In accordance with an exemplary embodiment, a Diversity M-channels Baseband Processor sub-system  12  comprises a Turbo Codes Decoders  23 , an N-point Complex-FFT Processor  24  (Fast Fourier Transform) for demodulating orthogonal signals RX( 0 ) to RX(M−1), M-multiple of Pre-processors  21  for pre-processing of orthogonal signals RX( 0 ) to RX(M−1), and a Diversity Processor  22 . 
     In accordance with an exemplary embodiment, each identical Pre-processor  21  contains an I/Q Demodulator  251 , a Guard-interval Removal  252  for removing cyclic prefix, a clock recovery (AFC)  254  for reconstructing the clock, and the DLL digital phase-lock-loop  253  for re-sync and timing-correction. 
     In accordance with an exemplary embodiment, the Diversity Processor  22  contains a Combiner  261  for processing a pair of diversity channel RX(i) and RX(j), and a Matched Filter  262  for generate an output signal R(k). 
     In accordance with an exemplary embodiment, the N-point Complex FFT Processor  24  process orthogonal signals from diversity M-channels R(i). 
     In accordance with an exemplary embodiment, the Diversity M-channels Baseband Processor sub-system functions effectively as follows: 
     The received orthogonal signals RX( 0 ) to RX(M−1) were initially processed by the I/Q Demodulator  251  for demodulating the RX signal into baseband I/Q components. 
     The baseband I/Q components are then passed thru a Guard-interval Removal  252  for removing cyclic prefix to produce the clean I/Q baseband signals. 
     A clock recovery (AFC)  254  computes I/Q signals to calculate the phase-error during transmission due to noise and multipath fading effect. The phase-error output is used to drive the digital phase-lock-loop to correct sample timing for I/Q demodulator to produce better quality of signals. 
     The baseband I/Q components are then passed thru a Diversity Processor  22  for further processing of multipath signals. 
     The I and Q components are then passed to the N-point complex FFT Processor  24 . The FFT Processor  24  performs the complex Fast Fourier Transform (FFT) for the I and Q sequences of N samples to transform them into N points of complex-coefficient outputs. 
     In accordance with an exemplary embodiment, an N-point Complex-FFT Processor  24  processes each of the M-channels I/Q signals, where the I component is mapped into Real-coefficient input, and Q is mapped into the Imaginary-coefficient input of the FFT processor. The FFT processor processes I/Q signals and produce a set of complex-coefficient outputs that are fed into MUX  25  and then shifted into the Turbo Codes Decoder  23 . 
     Each set of (I,Q) is loaded into the MUX  25  then shifted into the Turbo Codes Decoder baseband processor  23 , where data is iteratively decoded until a final decision hard-decoded bit is produced for the output that correspond to each bit-stream. 
     In accordance with an exemplary embodiment, the Turbo Codes Decoder block  23  has concatenated max Log-MAP SISO Decoders A  42  and B  44  connected in a feedback loop with Interleaver Memory  43  and Interleaver Memory  45 . Signals R 2 , R 1 , R 0  are received soft decision signals from complex-coefficient output of the FFT processor. 
     N_Point Complex FFT Processor and the OFDM 
     The Orthogonal Frequency Division Multiplexing (OFDM) is a technique used to divide the broadband channel into sub-channels where multiple adjacent channels transmit their carriers&#39; frequency, which are orthogonal to each other. The sum of all carriers can be transmitted over the air to the receiver where each channel&#39;s carrier can be separated without loss of information due to interferences. In OFDM the subcarrier pulse used for transmission is chosen to be rectangular. This has the advantage that the task of pulse forming and modulation can be performed by a simple Inverse Discrete Fourier Transform (IDFT). Accordingly in the receiver we only need a Forward FFT to reverse this operation. The invention presents a method to divide the broadband into multiple sub-channels and uses an Orthogonal Frequency Division Multiplexing method implemented by N-point complex FFT processors to effectively divide the broadband high-speed channel into multiple slow-speed N sub-channels where multiple adjacent channels transmit their carriers&#39; frequency which are orthogonal to each other. 
     Forward Complex FFT takes sample data, multiplies it successively by complex exponentials over the range of frequencies, sums each product and produces the results as sequence of frequency coefficients. The results array of frequency coefficients is called a spectrum. The equation of a forward Complex FFT is shown below: 
     
       
         
           
             
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     where x(n) are inputs sampled data and X(k) is sequence of frequency coefficients. 
     As shown in  FIG. 2 , an N-point complex FFT Processor  24  takes sampled data (I,Q) from the Diversity Processor  22  output where the “I” component is mapped as Real part and the “Q” component is mapped Imaginary part into the input of an N-point complex FFT processor. After processing period, the complex FFT processor then produces an output sequence of frequency coefficients. The sequence of frequency coefficients are then fed into the MUX  25  and shifted into the Turbo Codes Decoder  23 . 
     Pre-Processor for Baseband Processing Sub-Systems 
     As shown in  FIG. 25 , an Pre-Processor  21  comprises an IQ demodulator  251  for demodulating the received signal into I and Q baseband signal components, a digital phase-lock-loop (DLL) and local carrier generator  253  produces phase-correct sample frequency, an a clock recovery (AFC Clock circuit)  254 , a guard interval (GI) remover  252  for deleting guard interval. 
     In accordance with an exemplary embodiment, the Pre-Processor functions effectively as follows: 
     Received signals entering the IQ Demodulator  251  are demodulated with a local carrier to produce the I and Q component signals. 
     The I and Q signals are shifted completely through the Guard Interval Remover  252  where the cyclic-prefix is removed from each I and Q signal. 
     The I and Q signals are inputted into the Clock-Recovery circuit  254  where the I and Q sample will be phase detected and the phase-error will be calculated. The phase-error output will be used to control the DLL local carrier generator circuit  253 . 
     Diversity Processing Sub-Systems 
     As shown in  FIG. 26 , the Diversity Processor  22  comprises a Combiner  261 , a Matched Filter  262 , and Antenna Selection Algorithm  263 . 
     In accordance with an exemplary embodiment, the Diversity Processor  22  functions effectively as follows: 
     The Antennas Selection Algorithm will select an optimum pair of diversity channels. For each channel RX(i), the Algorithm  263  will find an adjacent channel RX(j) to form an optimum pair of diversity channels. 
     The Combiner  261  will combiner signals of the two diversity channel. 
     The Matched Filter  261  will process the signal ad produce an result output R(i). 
     Beam Steering Phased Array Antenna 
       FIG. 30  shows a preferred embodiment of a mobile wireless system in which the mobile wireless terminal  301  transmits unidirectional signals to the base-station  272 .  FIG. 31  illustrates a unidirectional radiation wave lobe  311  in vertical pattern side view indicating only a single radiation lobe toward the base-station.  FIG. 32  illustrates a unidirectional radiation wave lobe  321  in horizontal pattern top view indicating only a single radiation lobe toward the base-station. 
       FIG. 33  shows a preferred embodiment of a Phased Array Antenna  331  comprising of an array [4×4] of radiating elements  332 . A different preferred embodiment of array [N×N] of radiating elements can be used for Phased Array Antenna. 
       FIG. 34  illustrates a preferred embodiment of a Beam Steering Phased Array Antenna system comprising a Signal Feed Processor  344  for feeding signals to the antennas, the Phase Shifters  342  associates with each radiation elements  332  for varying the phases of the signals before feeding to the radiating elements  332  for transmitting signal wave patterns  343  at the calculated angle θ, a Digital Signal Processing (DSP) Phase Processor  341  for calculating the phase shifting steps data for the phase shifters  342  based on the steering angle θ of radiating waves  343  using the following equation:
 
φ=[2π×( n×d )×sin(θ)]÷ c  
 
       FIG. 35  illustrates a preferred embodiment of a Transmitter system with Beam Steering Phased Array [N×N] Antenna comprising a TX Baseband Processor  352  wherein the Turbo Codes Encoder  354  encodes the transmitting data into coded words and then sending coded words to the inverse Fast Fourier Transform (iFFT) engine  353  for modulating into an OFDM signals, a Transmitter  351  further sends the OFDM signals to the Signal Feed Processor  344  for distributing signals to the phase shifter  342  for transmitting to the antennas  332 , the Phase Shifters  342  associates with each radiation elements  332  varies the phases of the signals before feeding to the radiating elements  332  for transmitting the signal wave patterns  343  at the calculated angle θ, a Digital Signal Processing (DSP) Phase Processor  341  calculates the phase shifting values for the phase shifters  342  based on the required steering angle θ of radiating waves  343 , and a Phased Array [N×N] Antenna  332  radiates wave lobe toward the base-station  272 , a Base Station Tracker  355  is used to track the current base station that the device is communicated. A Clock Management Logic  391  is used to control the clock distribution to target modules by turning off clock to the inactive modules. A Power Management Logic  381  is used to control the power distribution to target modules by turning off power to the inactive modules. 
     In accordance with a preferred embodiment, the Base Station Tracker  355  determines the current location of the base station relative to the mobile device and provides the information to the DSP Phase Processor  341 . The DSP Phase Processor  341  calculates the phase required, based on the current location of the base station, to control the Phase Shifter  342  angles. The Phase Shifter  342  varies the transmit signals received from the Signal Feed Processor  344  and controls the angles of the transmitting waves  343  for steering the transmitting waves toward the current base station. 
       FIG. 36  illustrates a preferred embodiment of a Smart Phone wireless Terminal indicating the arrangement of the phased array [N×N] antennas  361  in the backside of the device which radiates signal wave patterns  362  toward the base-station  272  at an angle θ. 
       FIG. 37  illustrates a preferred embodiment of a Smart Phone wireless Terminal frontside view indicating the arrangement of solar-cell panels for charging the battery. Because the reduced energy required for transmitting signals, the wireless mobile device power consumption is reduced significantly so that it employs solar-cell panels for charging its battery which achieves the green-energy goal. 
       FIG. 38  illustrates a preferred embodiment of a Smart Phone wireless Terminal Power Management Logic (PML) comprising a Power Management Logic (PML)  381  controls the distributing of power to the target modules only when need it. When a module needs to operate, the PML will turn-on the power to that module, otherwise the module power will be off. A sequence of monitoring and controlling power distributing on/off to the modules will greatly reduce the power consumption of the wireless terminal and achieves the green-energy goal. A Solar Power Charger Logic  382  for charging the battery  383 . 
       FIG. 39  illustrates a preferred embodiment of a Smart Phone wireless Terminal Clocks Management Logic (CML) comprising a Clocks Management Logic (CML)  391  controls the distributing of clock signal to the target modules only when need it. When a module needs to operate, the PML will turn-on the clock to that module, otherwise the module clock will be off. A sequence of monitoring and controlling clock distributing on/off to the modules will greatly reduce the power consumption of the wireless terminal and achieves the green-energy goal.

Technology Category: 4