  This two-part paper aims to quantify the cost of device activity detection in
an uplink massive connectivity scenario with a large number of devices but
device activities are sporadic. Part I of this paper shows that in an
asymptotic massive multiple-input multiple-output (MIMO) regime, device
activity detection can always be made perfect. Part II of this paper
subsequently shows that despite the perfect device activity detection, there is
nevertheless significant cost due to device detection in terms of overall
achievable rate, because of the fact that non-orthogonal pilot sequences have
to be used in order to accommodate the large number of potential devices,
resulting in significantly larger channel estimation error as compared to
conventional massive MIMO systems with orthogonal pilots. Specifically, this
paper characterizes each active user's achievable rate using random matrix
theory under either maximal-ratio combining (MRC) or minimum mean-squared error
(MMSE) receive beamforming at the base-station (BS), assuming the statistics of
their estimated channels as derived in Part I. The characterization of user
rate also allows the optimization of pilot sequences length. Moreover, in
contrast to the conventional massive MIMO system, the MMSE beamforming is shown
to achieve much higher rate than the MRC beamforming for the massive
connectivity scenario under consideration. Finally, this paper illustrates the
necessity of user scheduling for rate maximization when the number of active
users is larger than the number of antennas at the BS.
