  We consider futuristic, intelligent reflecting surfaces (IRS)-aided
communication between a base station (BS) and a user equipment (UE) for two
distinct scenarios: a single-input, single-output (SISO) system whereby the BS
has a single antenna, and a multi-input, single-output (MISO) system whereby
the BS has multiple antennas. For the considered IRS-assisted downlink, we
compute the effective capacity (EC), which is a quantitative measure of the
statistical quality-of-service (QoS) offered by a communication system
experiencing random fading. For our analysis, we consider the two widely-known
assumptions on channel state information (CSI) -- i.e., perfect CSI and no CSI,
at the BS. Thereafter, we first derive the distribution of the signal-to-noise
ratio (SNR) for both SISO and MISO scenarios, and subsequently derive
closed-form expressions for the EC under perfect CSI and no CSI cases, for both
SISO and MISO scenarios. Furthermore, for the SISO and MISO systems with no
CSI, it turns out that the EC could be maximized further by searching for an
optimal transmission rate $r^*$, which is computed by exploiting the iterative
gradient-descent method. We provide extensive simulation results which
investigate the impact of the various system parameters, e.g., QoS exponent,
power budget, number of transmit antennas at the BS, number of reflective
elements at the IRS etc., on the EC of the system.
