  Although interference alignment (IA) can theoretically achieve the optimal
degrees of freedom (DoFs) in the $K$-user Gaussian interference channel, its
direct application comes at the prohibitive cost of precoding over
exponentially-many signaling dimensions. On the other hand, it is known that
practical "one-shot" IA precoding (i.e., linear schemes without symbol
expansion) provides a vanishing DoFs gain in large fully-connected networks
with generic channel coefficients. In our previous work, we introduced the
concept of "Cellular IA" for a network topology induced by hexagonal cells with
sectors and nearest-neighbor interference. Assuming that neighboring sectors
can exchange decoded messages (and not received signal samples) in the uplink,
we showed that linear one-shot IA precoding over $M$ transmit/receive antennas
can achieve the optimal $M/2$ DoFs per user. In this paper we extend this
framework to networks with omni-directional (non-sectorized) cells and consider
the practical scenario where users have $2$ antennas, and base-stations have
$2$, $3$ or $4$ antennas. In particular, we provide linear one-shot IA schemes
for the $2\times 2$, $2\times3$ and $2\times 4$ cases, and show the
achievability of $3/4$, $1$ and $7/6$ DoFs per user, respectively. DoFs
converses for one-shot schemes require the solution of a discrete optimization
problem over a number of variables that grows with the network size. We develop
a new approach to transform such challenging optimization problem into a
tractable linear program (LP) with significantly fewer variables. This approach
is used to show that the achievable $3/4$ DoFs per user are indeed optimal for
a large (extended) cellular network with $2\times 2$ links.
