More Simultaneous Dynamic Range with Fixed Point or Floating Point?
For the same total bit width, a fixed-point representation has a higher instantaneous dynamic range than a floating-point representation.
 For a value to be simultaneously including information about a strong and a weak signal (where the information is being carried by the sum of the strong and weak signal components), the weak signal has to have a value at least as large as the stronger signal's numerical error floor, given by the format's epsilon. In a floating-point representation, every bit allocated to the exponent similarly reduces the number of bits allocated to the significand, and thus increases the format's epsilon. This correspondingly decreases the ratio between the strong and weak signal components that can be included in a single value.
 For example in a standard 32-bit IEEE-754 single-precision floating point representation, 23 bits are allocated to the significand. As a result the smallest number that can be added to a given number $x$ is of the order of $x/2^{23}$ or approximately $8.6\times 10^6$ times smaller. Note that this is consistent with the C programming language's FLT_EPSILON which is approximately $1.19\times 10^{-7}$. In comparison, using a 32-bit fixed-point representation the smallest number that can be added to a large number using near full scale (e.g. 0xffffff00) is of the order of a single unit (e.g. 0x00000001) which is approximately $2^{32} \approx 4.3\times10^9$ times smaller.