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                        Vodafone Chair Mobile Communications Systems, Prof. Dr.-Ing. G. Fettweis chair
Digital Signal Transmission Lab
SS 08
Oliver Arnold
Steffen Kunze                                                                                                                                                                                                                                                                                                                                                                    
                    
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                                  Introduction chair Hardware Why to use digital signal processing? General introduction to DSPs The TMS320C6711 DSP Architecture Overview Peripherals DSK6711 evaluation board - Software Code Composer Studio DSP/BIOS Multi-channel Buffered Serial Port (McBSP) TU Dresden, 4/29/2008 Slide 2                                                                                                                                                                                                           
                    
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                        chair Hardware TU Dresden, 4/29/2008 Slide 3                                                                                                                                                                                                                                                                                                                                                                                                                                                                        
                    
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                                           Digital Signal Processing (DSP) chair Wireless / Cellular HDD Voice-band audio PRML read channel RF codecs MR pre-amp Voltage regulation Servo control SCSI tranceivers Consumer Audio DSP: Automotive Stereo A/D, D/A PLL Digital radio A/D/A Technology Mixers Active suspension Enabler Voltage regulation Multimedia Stereo audio DTAD Imaging Speech synthesizer Graphics palette Mixed-signal Voltage regulation processor TU Dresden, 4/29/2008 Slide 4                                   
                    
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                        System Considerations chair Performance Performance Interfacing Interfacing Power Power Size Size Ease-of Use Integration Ease-of Use Integration Cost Cost • Programming • Memory • Programming • Memory • Device cost • Device cost • • Interfacing Interfacing • • Peripherals Peripherals • System cost • System cost • Debugging  • Debugging  • Development cost • Development cost • Time to market  • Time to market  TU Dresden, 4/29/2008 Slide 5                                                         
                    
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                            Why Go Digital? chair Digital signal processing techniques are now  so powerful that sometimes it is extremely  difficult, if not impossible, for analogue signal  processing to achieve similar performance.  Examples:  FIR filter with linear phase Adaptive filters TU Dresden, 4/29/2008 Slide 6                                                                                                                                                                                                           
                    
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                             Why Go Digital? chair Analogue signal processing is achieved by  using analogue components such as:  Resistors Capacitors Inductors The inherent tolerances associated with  these components, temperature, voltage  changes and mechanical vibrations can  dramatically affect the effectiveness of the  analogue circuitry TU Dresden, 4/29/2008 Slide 7                                                                                                                                                     
                    
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                                  Why Go Digital? chair With DSP? - It is easy to: Change applications Correct applications Update applications Additionally DSPs reduce: Noise susceptibility Chip count Development time Cost Power consumption TU Dresden, 4/29/2008 Slide 8                                                                                                                                                                                                                                                             
                    
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                        chair General Introduction to DSPs TU Dresden, 4/29/2008 Slide 9                                                                                                                                                                                                                                                                                                                                                                                                                                                    
                    
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                        What Problem Are We Trying To Solve? chair xY ADC DAC DSP Digital sampling of  Most DSP algorithms can be  an analog signal: expressed as: count A Y  =  Σ a *  x i i i  =  1 for (i = 1; i < count; i++){ t sum += m[i] * n[i]; } TU Dresden, 4/29/2008 Slide 10                                                                                                                                                                                                                                                   
                    
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                         What are the typical DSP algorithms? chair The Sum of Products (SOP) is the key element in  most DSP algorithms: Algorithm Equation M yn () = a x(n −k) ∑ k Finite Impulse Response Filter k =0 M N y(n) = a x(n −k) + b y(n −k) k k ∑ ∑ Infinite Impulse Response Filter k =0 k =1 N y(n) = x(k)h(n −k) ∑ Convolution k =0 N −1 X (k) = x(n) exp[ −j(2 π / N)nk] ∑ Discrete Fourier Transform n =0 N −1 π ⎡ ⎤ F() u = c(u).f (x).cos u() 2x +1 ∑ ⎢ ⎥ Discrete Cosine Transform 2N ⎣ ⎦ x =0 TU Dresden, 4/29/2008 S
                    
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                                Why do we need DSP processors? chair Use a DSP processor when the following  are required: Cost saving Smaller size Low power consumption Processing of many “high” frequency signals in  real-time Use a GPP processor when the following  are required: Large memory Advanced operating systems TU Dresden, 4/29/2008 Slide 12                                                                                                                                                                            
                    
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                           Hardware vs. Microcode multiplication chair DSP processors are optimized to perform  multiplication and addition operations. Multiplication and addition are done in  hardware and in one cycle. Example: 4-bit multiply (unsigned). Hardware Microcode Hardware Microcode 1011 1011 1011 1011 x 1110 x 1110 x 1110 x 1110 10011010 10011010 0000 Cycle 1 0000 Cycle 1 1011. Cycle 2 1011. Cycle 2 1011.. Cycle 3 1011.. Cycle 3 1011... Cycle 4 1011... Cycle 4 10011010 Cycle 5 10011010 Cycle 5 TU Dresden, 4/
                    
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                          General Purpose DSP vs. DSP in ASIC chair Application Specific Integrated Circuits  (ASICs) are semiconductors designed for  dedicated functions. The advantages and disadvantages of using  ASICs are listed below: Advantages Disadvantages Advantages Disadvantages • High throughput • High investment cost • High throughput • High investment cost • Lower silicon area • Less flexibility • Lower silicon area • Less flexibility • Lower power consumption • Long time from design to  • Lower power consu
                    
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                                  Floating vs. Fixed point processors chair Applications which require: High precision Wide dynamic range High signal-to-noise ratio Ease of use Need a floating point processor Drawback of floating point processors: Higher power consumption Usually higher cost Usually slower than fixed-point counterparts and  larger in size TU Dresden, 4/29/2008 Slide 15                                                                                                                                        
                    
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                        chair TMS320C6711 Architectural Overview TU Dresden, 4/29/2008 Slide 16                                                                                                                                                                                                                                                                                                                                                                                                                                             
                    
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                        General DSP System Block Diagram chair Internal Memory Internal Buses P E External R I Memory P Central  H E Processing R A Unit L S TU Dresden, 4/29/2008 Slide 17                                                                                                                                                                                                                                                                                                                                                 
                    
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                                  ‘6711 CPU Overview  chair Specification Clock Rate: 100/150 MHz 600/900 MFLOPS 0.18- μm/5-Level Metal Process – CMOS Technology CPU has got two Datapaths, altogether: Four ALUs (Floating- and Fixed-Point) Two ALUs (Fixed-Point) Two Multipliers (Floating- and Fixed-Point) Load-Store Architecture  2*16 32-Bit General-Purpose Registers TU Dresden, 4/29/2008 Slide 18                                                                                                                             
                    
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                                     ‘6711 CPU Overview chair VelociTI advanced very-long instruction words (VLIW)  Program Memory Width is 256 Bit Up to 8 32-Bit instructions can be executed in parallel/Cycle 16, 32 and 40 bit fixed point operands 32 and 64 bit floating point operands Instruction parallelism is detected at compile-time no data dependency checking is done in Hardware. Instruction Packing Reduces Code Size All operations work on registers Memory Architecture 4K-Byte L1P Program Cache (Direct Mapped) 4K-
                    
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                        Functional Block and CPU Diagram chair TU Dresden, 4/29/2008 Slide 20