  We propose a new complex block floating-point format to reduce implementation
complexity. The new format achieves wordlength reduction by sharing an exponent
across the block of samples, and uses box encoding for the shared exponent to
reduce quantization error. Arithmetic operations are performed on blocks of
samples at time, which can also reduce implementation complexity. For a case
study of a baseband quadrature amplitude modulation (QAM) transmitter and
receiver, we quantify the tradeoffs in signal quality vs. implementation
complexity using the new approach to represent IQ samples. Signal quality is
measured using error vector magnitude (EVM) in the receiver, and implementation
complexity is measured in terms of arithmetic complexity as well as memory
allocation and memory input/output rates. The primary contributions of this
paper are (1) a complex block floating-point format with box encoding of the
shared exponent to reduce quantization error, (2) arithmetic operations using
the new complex block floating-point format, and (3) a QAM transceiver case
study to quantify signal quality vs. implementation complexity tradeoffs using
the new format and arithmetic operations.
