VLSI Communication SystemsRecap VLSI Communication Systems RECAP

VLSI Communication SystemsRecap CMOS  Digital CMOS – MOS circuits: qualitative, quantitative – Gates, flops – Datapath – Memories – Scaling  Analog CMOS – Number of basic elements Diff amp, data converters, multipliers, LNA – Compensate for poor quality process

VLSI Communication SystemsRecap Comm Theory  Channel  Finite bandwidth  Multipath  Doppler  Attenuation  Sharing  Modulation  Multiply carrier(s)  BFSK, BPSK, QPSK, OFDM, Spread spectrum  Shaping, equalization\

VLSI Communication SystemsRecap Filtering  Spec: pass/stop band, ripple – Many benefits to digital filtering – Can be implemented in many ways  FFT – Replaces direct convolution – Various interpretations, best is PVR view – Not competitive for most wireless applications  Cordic – Compute sin/cos with very little hardware

VLSI Communication SystemsRecap DFGs  Data Flow Graph – Represents any “statically schedulable” computation – More than just multiply, add, delay elements LDPC, FFT, sorting arrays, dep checks, etc. Even some dynamic computations Iteration bound

VLSI Communication SystemsRecap Generic Optimizations  Pipelining – Tradeoff latency for clock speed  Retiming – Move flops to even out path delays  Unfolding – Parallize to meet IB  Folding – Map a DFG with 1000s of nodes to hardware with 10s of execution units

VLSI Communication SystemsRecap IIR filters  Allowing feedback can lead to huge reductions in hardware complexity – Poles can boost frequencies, zeroes can only attenuate them – Essential when doing adaptive filtering  Many problems – Pipelining is harder – Numerical issues: stability, limit cycles, etc.  Various optimizations – Some to meet IB, some to surpass it – Understanding z-domain critical

VLSI Communication SystemsRecap Numeric Strength Reduction  Share hardware across different computations – MCM – Ax – Exponentiation – MIMO  General algorithm for sub-expression sharing – Look for terms common to two separate computations

VLSI Communication SystemsRecap Numerical Issues  Coefficient quantization – Use 2 nd order stages  Compute the effects of over/underflow, truncation – Analytical approach: state space equations – Simulations  Use better architectures – Lattice filters

VLSI Communication SystemsRecap ECC  Core idea – Add redundancy to recover from errors – FEC vs ARQ  Various schemes – Two basic classes: block, convolutional – Differ in terms of number of errors they can recover from, implementation cost  Shannon limit  Linear Block Codes – G, H matrices – Simple decoding: bit flipping, works well when H is sparse

VLSI Communication SystemsRecap What we left out  Analog/RF, antenna issues – Better left to specialized classes  Comm theory: error probabilities, detailed channel models, timing recovery – Often simulation is more accurate  VLSI Signal Processing – Systolic arrays – Fast convolution, algorithmic strength reduction – Bit level arithmetic, redundant arithmetic – Wave pipelining – Low power design – DSPs