  Current best limits on the 21-cm signal during reionization are provided at
large scales ($\gtrsim$100 Mpc). To model these scales, enormous simulation
volumes are required which are computationally expensive. We find that the
primary source of uncertainty at these large scales is sample variance, which
decides the minimum size of simulations required to analyse current and
upcoming observations. In large-scale structure simulations, the method of
`fixing' the initial conditions (ICs) to exactly follow the initial power
spectrum and `pairing' two simulations with exactly out-of-phase ICs has been
shown to significantly reduce sample variance. Here we apply this `fixing and
pairing' (F\&P) approach to reionization simulations whose clustering signal
originates from both density fluctuations and reionization bubbles. Using a
semi-numerical code, we show that with the traditional method, simulation boxes
of $L\simeq 500$ (300) Mpc are required to model the large-scale clustering
signal at $k$=0.1 Mpc$^{-1}$ with a precision of 5 (10) per cent. Using F\&P,
the simulation boxes can be reduced by a factor of 2 to obtain the same
precision level. We conclude that the computing costs can be reduced by at
least a factor of 4 when using the F\&P approach.
