domain, for different UTs are usually different.[^5] For APSPs, when the phase shifts for pilots employed by different UTs are properly scheduled according to the above channel properties, channel acquisition can be achieved simultaneously in an almost interference-free manner as with conventional PSOPs. There has recently been increased research interest on utilizing channel sparsity for channel acquisition in massive MIMO. For instance, a time-frequency training scheme [@Dai13Spectrally] and a distributed Bayesian channel estimation scheme [@Masood15Efficient] were proposed for massive MIMO-OFDM by exploiting the channel sparsity. As the approaches in [@Masood15Efficient] and [@Dai13Spectrally] focus on channel acquisition for a single UT, the corresponding pilot overhead would still grow linearly with the number of UTs. Channel sparsity has also been exploited to mitigate pilot contamination in multi-cell massive MIMO [@Chen14Pilot; @Wen15Channel]. Note that compressive sensing has been applied to sparse channel acquisition in some recent works (see, e.g., [@Bajwa10Compressed; @Barbotin12Estimation; @Berger10Application; @Rao14Distributed] and references therein), in which the corresponding pilot signals are usually assumed to be randomly generated. However, it is usually quite difficult to implement random pilot signals in practical systems [@Candes07Sparsity]. For example, adopting large dimensional random pilot signals in the massive MIMO-OFDM systems considered here requires huge storage space 