  Opportunistic interference alignment (OIA) asymptotically achieves the
optimal degrees-of-freedom (DoF) in interfering multiple-access channels
(IMACs) in a distributed fashion, as a certain user scaling condition is
satisfied. For the multiple-input multiple-output IMAC, it was shown that the
singular value decomposition (SVD)-based beamforming at the users fundamentally
reduces the user scaling condition required to achieve any target DoF compared
to that for the single-inputmultiple-output IMAC. In this paper, we tackle two
practical challenges of the existing SVD-based OIA: 1) the need of full
feedforward of the selected users' beamforming weight vectors and 2) a low rate
achieved based on the exiting zero-forcing (ZF) receiver. We first propose a
codebook-based OIA, in which the weight vectors are chosen from a pre-defined
codebook with a finite size so that information of the weight vectors can be
sent to the belonging BS with limited feedforward. We derive the codebook size
required to achieve the same user scaling condition as the SVD-based OIA case
for both Grassmannian and random codebooks. Surprisingly, it is shown that the
derived codebook size is the same for the two considered codebook approaches.
Second, we take into account an enhanced receiver at the base stations (BSs) in
pursuit of improving the achievable rate based on the ZF receiver. Assuming no
collaboration between the BSs, the interfering links between a BS and the
selected users in neighboring cells are difficult to be acquired at the
belonging BS. We propose the use of a simple minimum Euclidean distance
receiver operating with no information of the interfering links. With the help
of the OIA, we show that this new receiver asymptotically achieves the channel
capacity as the number of users increases.
