Conference Paper

On the degrees-of-freedom of the MIMO interference channel

Lincoln Lab., MIT, Lexington, MA
DOI: 10.1109/CISS.2008.4558496 Conference: Information Sciences and Systems, 2008. CISS 2008. 42nd Annual Conference on
Source: IEEE Xplore

ABSTRACT The high signal-to-noise ratio capacity of the symmetric MIMO interference channel is characterized as a function of the interference-to-noise ratio. This work is a multiple antenna extension of the degrees of freedom expressions derived by Etkin et al. for the single antenna case. This characterization considers the case where the number of receive antennas is greater than or equal to the number of transmit antennas and shows the number of degrees of freedom available for communication as a function of log(INR)/log(SNR).

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: It has been shown recently by Geng et al. that in a $K$ user Gaussian interference network, if for each user the desired signal strength is no less than the sum of the strengths of the strongest interference from this user and the strongest interference to this user (all signal strengths measured in dB scale), then power control and treating interference as noise (TIN) is sufficient to achieve the entire generalized degrees of freedom (GDoF) region. Motivated by the intuition that the deterministic model of Avestimehr et al. (ADT deterministic model) is particularly suited for exploring the optimality of TIN, the results of Geng et al. are first re-visited under the ADT deterministic model, and are shown to directly translate between the Gaussian and deterministic settings. Next, we focus on the extension of these results to parallel interference networks, from a sum-capacity/sum-GDoF perspective. To this end, we interpret the explicit characterization of the sum-capacity/sum-GDoF of a TIN optimal network (without parallel channels) as a minimum weighted matching problem in combinatorial optimization, and obtain a simple characterization in terms of a partition of the interference network into vertex-disjoint cycles. Aided by insights from the cyclic partition, the sum-capacity optimality of TIN for $K$ user parallel interference networks is characterized for the ADT deterministic model, leading ultimately to corresponding GDoF results for the Gaussian setting. In both cases, subject to a mild invertibility condition the optimality of TIN is shown to extend to parallel networks in a separable fashion.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, we study the effect of feedback on two-user MIMO interference channels. The capacity region of MIMO interference channels with feedback is characterized within a constant number of bits, where this constant is independent of the channel matrices. Further, it is shown that the capacity region of a MIMO interference channel with feedback and its reciprocal interference channel are within a constant number of bits. Finally, the generalized degrees of freedom region for the MIMO interference channel with feedback is characterized.
    IEEE Transactions on Information Theory 12/2012; · 2.62 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper gives the approximate capacity region of a two-user MIMO interference channel with limited receiver cooperation, where the gap between the inner and outer bounds is in terms of the total number of receive antennas at the two receivers and is independent of the actual channel values. The approximate capacity region is then used to find the degrees of freedom region. For the special case of symmetric interference channels, we also find the amount of receiver cooperation in terms of the backhaul capacity beyond which the degrees of freedom do not improve. Further, the generalized degrees of freedom are found for MIMO interference channels with equal number of antennas at all nodes. It is shown that the generalized degrees of freedom improve gradually from a "W" curve to a "V" curve with increase in cooperation in terms of the backhaul capacity.
    IEEE Transactions on Information Theory 08/2013; 60(7). · 2.62 Impact Factor