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75
Interference alignment and cancellation
 In Proceedings of ACM SIGCOMM
, 2009
"... The throughput of existing MIMO LANs is limited by the number of antennas on the AP. This paper shows how to overcome this limitation. It presents interference alignment and cancellation (IAC), a new approach for decoding concurrent senderreceiver pairs in MIMO networks. IAC synthesizes two signal ..."
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Cited by 101 (7 self)
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The throughput of existing MIMO LANs is limited by the number of antennas on the AP. This paper shows how to overcome this limitation. It presents interference alignment and cancellation (IAC), a new approach for decoding concurrent senderreceiver pairs in MIMO networks. IAC synthesizes two signal processing techniques, interference alignment and interference cancellation, showing that the combination applies to scenarios where neither interference alignment nor cancellation applies alone. We show analytically that IAC almost doubles the throughput of MIMO LANs. We also implement IAC in GNURadio, and experimentally demonstrate that for 2x2 MIMO LANs, IAC increases the average throughput by 1.5x on the downlink and 2x on the uplink.
Cooperative Algorithms for MIMO Interference Channels
, 2010
"... Interference alignment is a transmission technique for exploiting all available degrees of freedom in the frequencyor timeselective interference channel with an arbitrary number of users. Most prior work on interference alignment, however, neglects interference from other nodes in the network not ..."
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Cited by 65 (13 self)
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Interference alignment is a transmission technique for exploiting all available degrees of freedom in the frequencyor timeselective interference channel with an arbitrary number of users. Most prior work on interference alignment, however, neglects interference from other nodes in the network not participating in the alignment operation. This paper proposes three generalizations of interference alignment for the multipleantenna interference channel with multiple users that account for colored noise, which models uncoordinated interference. First, a minimum interferenceplusnoise leakage (INL) algorithm is presented, and shown to be equivalent to previous subspace methods when noise is spatially white or negligible. This algorithm results in orthonormal precoders that are desirable for practical implementation with limited feedback. A joint minimum mean squared error design is then proposed that jointly optimizes the transmit precoders and receive spatial filters, whereas previous designs neglect the receive spatial filter. Finally, a maximum signaltointerferenceplusnoise ratio (SINR) algorithm is developed that is proven to converge, unlike previous maximum SINR algorithms. The sum throughput of these algorithms is simulated in the context of a network with uncoordinated cochannel interferers not participating in the alignment protocol. It is found that a network with cochannel interference can benefit from employing precoders designed to consider that interference, but in extreme cases, such as when only one receiver has a large amount of interference, ignoring the cochannel interference is advantageous.
Interference alignment with asymmetric complex signaling  settling the HostMadsenNosratinia conjecture
 IEEE TRANSACTION ON INFORMATION THEORY
, 2009
"... It has been conjectured by HøstMadsen and Nosratinia that complex Gaussian interference channels with constant channel coefficients have only one degreeoffreedom regardless of the number of users. While several examples are known of constant channels that achieve more than 1 degree of freedom, th ..."
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Cited by 65 (17 self)
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It has been conjectured by HøstMadsen and Nosratinia that complex Gaussian interference channels with constant channel coefficients have only one degreeoffreedom regardless of the number of users. While several examples are known of constant channels that achieve more than 1 degree of freedom, these special cases only span a subset of measure zero. In other words, for almost all channel coefficient values, it is not known if more than 1 degreeoffreedom is achievable. In this paper, we settle the HøstMadsenNosratinia conjecture in the negative. We show that at least 1.2 degreesoffreedom are achievable for all values of complex channel coefficients except for a subset of measure zero. For the class of linear beamforming and interference alignment schemes considered in this paper, it is also shown that 1.2 is the maximum number of degrees of freedom achievable on the complex Gaussian 3 user interference channel with constant channel coefficients, for almost all values of channel coefficients. To establish the achievability of 1.2 degrees of freedom we introduce the novel idea of asymmetric complex signaling i.e., the inputs are chosen to be complex but not circularly symmetric. It is shown that unlike Gaussian pointtopoint, multipleaccess and broadcast channels where circularly
Exact regeneration codes for distributed storage repair using interference alignment
 in Proc. 2010 IEEE Int. Symp. on Inform. Theory (ISIT), Seoul, Korea
, 2010
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Interference Alignment for the K User MIMO Interference Channel
, 2009
"... The K user multiple input multiple output (MIMO) Gaussian interference channel with M antennas at each transmitter and N antennas at each receiver is considered. We assume that channel coefficients are fixed and are available at all transmitters and receivers. The main objective of this paper is to ..."
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Cited by 31 (0 self)
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The K user multiple input multiple output (MIMO) Gaussian interference channel with M antennas at each transmitter and N antennas at each receiver is considered. We assume that channel coefficients are fixed and are available at all transmitters and receivers. The main objective of this paper is to characterize the total number of degrees of freedom (DoF) for this channel. We show that for fixed channel coefficients MN M+N K degrees of freedom can be achieved. The achivability method is based on a new technique for interference alignment recently advised by Motahari et al. [17]. Also we provide a new upperbound on the total number of DoF for this channel. This upperbound coincide with our achievable DoF for K ≥ M+N gcd(M,N) where gcd(M, N) denotes the greatest common divisor of M and N. Because there is no cooperation among transmit and/or receive antennas of each user in our approach, our results are applicable to cellular systems in which a base station with multiple antennas communicates with several users each with single antenna. For this case, as the number of users in each cell increases, the total number of DoF also increases and approaches to the interference free DoF.
Interference alignment as a rank constrained rank minimization
 in Proc. of IEEE Global Telecommunications Conference (GLOBECOM
, 2010
"... Abstract—We show that the maximization of the sum degreesoffreedom for the static flatfading multipleinput multipleoutput (MIMO) interference channel is equivalent to a rank constrained rank minimization problem, when the signal spaces span all available dimensions. The rank minimization correspo ..."
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Cited by 29 (2 self)
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Abstract—We show that the maximization of the sum degreesoffreedom for the static flatfading multipleinput multipleoutput (MIMO) interference channel is equivalent to a rank constrained rank minimization problem, when the signal spaces span all available dimensions. The rank minimization corresponds to maximizing interference alignment (IA) such that interference spans the lowest dimensional subspace possible. The rank constraints account for the useful signal spaces spanning all available spatial dimensions. That way, we reformulate all IA requirements to requirements involving ranks. Then, we present a convex relaxation of the RCRM problem inspired by recent results in compressed sensing and lowrank matrix completion theory that rely on approximating rank with the nuclear norm. We show that the convex envelope of the sum of ranks of the interference matrices is the sum of their corresponding nuclear norms and introduce tractable constraints that are asymptotically equivalent to the rank constraints for the initial problem. We also show that our heuristic relaxation can be also tuned to the multicell interference channel. Furthermore, we experimentally show that the proposed algorithm outperforms previous approaches for finding precoding and zeroforcing matrices for interference alignment. I.
Network coding for three unicast sessions: Interference alignment approaches
 ALLERTON CONFERENCE ON COMMUNICATION, CONTROL, AND COMPUTING
, 2010
"... We propose interference alignment techniques, originally developed for wireless interference channels, for the problem of network coding across unicast sessions. We describe two general approaches (namely, coding at the edge or in the middle of the network) and one specific example of each approach ..."
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Cited by 24 (11 self)
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We propose interference alignment techniques, originally developed for wireless interference channels, for the problem of network coding across unicast sessions. We describe two general approaches (namely, coding at the edge or in the middle of the network) and one specific example of each approach (namely, symbol extension method and ergodic alignment, respectively). We discuss the conditions for feasibility of alignment and their relation to network structure. We also compare alignment to alternative approaches. For three unicast sessions with mincut one, we show that whenever alignment is possible, alternative approaches can also achieve half the mincut. However, for more than three sessions and/or for mincut per session greater than one, we show examples where alignment is necessary.
Exploiting channel correlations – simple interference alignment schemes with no CSIT
, 2009
"... We explore 5 network communication problems where the possibility of interference alignment, and consequently the total number of degrees of freedom (DoF) with channel uncertainty at the transmitters are unknown. These problems share the common property that in each case the best known outer bounds ..."
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Cited by 22 (6 self)
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We explore 5 network communication problems where the possibility of interference alignment, and consequently the total number of degrees of freedom (DoF) with channel uncertainty at the transmitters are unknown. These problems share the common property that in each case the best known outer bounds are essentially robust to channel uncertainty and represent the outcome with interference alignment, but the best inner bounds – in some cases conjectured to be optimal – predict a total collapse of DoF, thus indicating the infeasibility of interference alignment under channel uncertainty at transmitters. Our main contribution is to show that even with no knowledge of channel coefficient values at the transmitters, the knowledge of the channels ’ correlation structure can be exploited to achieve interference alignment. In each case, we show that under a staggered block fading model, the transmitters are able to align interference without the knowledge of channel coefficient values. The alignment schemes are based on linear beamforming – which can be seen as a repetition code over a small number of symbols – and involve delays of only a few coherence intervals.