The interference alignment (IA) is a promising technique to efficiently mitigate interference and
to enhance capacity of a wireless network. This paper proposes an interference alignment scheme for
a cellular network with

Interference management is a key challenge in the design of the current and future cellular networks in order to satisfy the demand for higher data rates. To increase the system capacity in multicell and multiuser wireless network environments, various interference management techniques based on coordinated multipoint transmission and reception have been presented [

In the multi-cell MIMO Gaussian interfering broadcast channels (MIMO-IFBC), each base station (BS) supports multiple users within its cell and so there exist two kinds of interference, namely, interuser interference (IUI) and intercell interference (ICI). To mitigate both IUI and ICI simultaneously, a simple zero-forcing (ZF) scheme has been proposed for two-cell MIMO-IFBC [

The previous studies have mainly considered two- or three-cell case and there is still no closed-form solution for a general multi-cell case. In this paper, we propose a new IA scheme for a general

The rest of this paper is organized as follows. In Section

We describe a system model for the considered multi-cell MIMO-IFBC scenario. The system contains

MIMO-IFBC for the case of three cells and two users per cell (

We suppose that each BS tries to convey one data stream per MS. Therefore, the received signal

We define the DoF (a.k.a. multiplexing gain) for our multi-cell network as the prelog factor of the sum rate [

The proposed IA scheme operates with two steps. First, each MS cooperatively constructs the receive beamforming vectors to align the effective ICI channel within a small dimensional subspace. Through this ICI channel alignment, each BS can regard

Proposed IA scheme for

The receive beamforming vectors of MS

Since the effective ICI channels are aligned with each other, the BS

The received beamforming vector

In this section, we extend the proposed IA scheme to the general case for

For the

To align

The existence condition of the null space of

When the number of cells is two (i.e.,

From a practical point of view, the cellular system has a limited number of antennas due to the lack of physical space in equipments, but the number of cooperative cells or users is variable according to the geographical coverage and the scheduling method. In this context, we can verify the achievability of the proposed IA by maximizing the number of users per cell while each user has one DoF. Therefore, in this section, we aim to maximize the value of

Two conditions in (

Our objective is to maximize

Therefore, the achievability of the proposed IA scheme is summarized as follows.

For the

When the number of transmit antennas is less than the number of receive antennas (i.e.,

We compare the proposed IA scheme with the orthogonalization (i.e., resource partitioning among BSs), subspace IA [

Figure

Ergodic sum rate versus SNR for

Figure

Achievable DoF versus number of transmit antennas when

Figure

Achievable DoF versus number of receive antennas when

We proposed an IA scheme for the multi-cell MIMO-IFBC by jointly designing the transmit and receive beamforming vectors using a closed-form expression. The proposed IA scheme aligns multiple ICIs into a small dimensional subspace through the receive beamforming and removes both the ICI and IUI simultaneously through the transmit beamforming. As the feasibility condition of the proposed IA, we derived the minimum number of antennas required to achieve one DoF per user. For the achievability of the proposed IA, we derived the maximum number of supportable users for a given antenna configuration. The numerical results showed that the proposed IA scheme has a better DoF performance than the conventional schemes and informed how to determine the related parameters to achieve maximum DoF.

The author declares that there is no conflict of interests regarding the publication of this paper.

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2011-0025424).