Proceedings Article10.1109/WCNC.2012.6214447
Interference alignment transceiver design for MIMO interference broadcast channels
Tingting Liu,Chenyang Yang +1 more
- 01 Apr 2012
- pp 641-646
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TL;DR: Simulation results validate the analysis and show that the proposed IA transceiver can achieve the maximal degrees of freedom of MIMO-IBC and attain a good trade-off between the maximal number of data streams and signal-to-noise ration gain.
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Abstract: In this paper, we develop linear interference alignment (IA) approach for multi-input-multi-output interference broadcast channel (MIMO-IBC). Since multiple data streams from each base station (BS) to multiple mobile stations (MSs) experience identical channel, it is hard to ensure the rank constraint to the intended MSs in the desired cell meanwhile ensure the interference aligned at the unintended MSs in other cells. Considering the difficulty in aligning interference at the receiver in MIMO-IBC, we design a transceiver to align and eliminate the interference at the transmitter. Specifically, we first design receive vectors of all MSs to align the inter-cell interference at the BS side, and then design the precoder of each BS to eliminate all the intra- and inter-cell interference. The proposed approach can be applied for general MIMO-IBC and has closed-from solutions for some antenna configurations. Simulation results validate our analysis and show that the proposed IA transceiver can achieve the maximal degrees of freedom of MIMO-IBC and attain a good trade-off between the maximal number of data streams and signal-to-noise ration gain.
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Citations
•Posted Content
Degrees of Freedom of MIMO Cellular Networks: Decomposition and Linear Beamforming Design
Sridharan Gokul,Wei Yu +1 more
TL;DR: An unstructured approach to linear interference alignment appears to be capable of achieving the optimal sDoF for MIMO cellular networks in regimes where linear beamforming dominates asymptotic decomposition, and a significant portion of s doF elsewhere.
51
Energy-Efficient Coordinated Beamforming Under Minimal Data Rate Constraint of Each User
Yang Li,Yafei Tian,Chenyang Yang +2 more
TL;DR: The results demonstrate that the proposed precoder performs closely to an upper bound derived from interference-free assumption, as well as a precoder, including an interference alignment (IA) beamformer and the optimized transmit power maximizing the EE.
45
Degrees of Freedom of MIMO Cellular Networks: Decomposition and Linear Beamforming Design
Sridharan Gokul,Wei Yu +1 more
TL;DR: In this paper, the authors investigated the symmetric degrees of freedom (DoF) of MIMO cellular networks with single-antenna users and showed that linear beamforming outperforms decomposition with asymptotic interference alignment.
41
Interference Alignment Transceiver Design by Minimizing the Maximum Mean Square Error for MIMO Interfering Broadcast Channel
TL;DR: Analysis indicates that the proposed Min-Max IA transceiver design scheme can significantly improve user fairness with a possible cost of sum-rate reduction and the proposed robust design algorithm provides better performance when lacking perfect channel state information (CSI).
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•Posted Content
Genie Chain and Degrees of Freedom of Symmetric MIMO Interference Broadcast Channels.
Tingting Liu,Chenyang Yang +1 more
TL;DR: The maximal DoF achieved by linear interference alignment (IA) is found, and it is found that the information theoretic DoF can be divided into two regions according to the ratio of the number of antennas at each base station (BS) to that at each user.
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References
•Book
Matrix Analysis and Applied Linear Algebra
Carl D. Meyer
- 24 May 2010
TL;DR: The author presents Perron-Frobenius theory of nonnegative matrices Index, a theory of matrices that combines linear equations, vector spaces, and matrix algebra with insights into eigenvalues and Eigenvectors.
5.3K
Interference Alignment and Degrees of Freedom of the $K$ -User Interference Channel
Viveck R. Cadambe,Syed A. Jafar +1 more
TL;DR: For the fully connected K user wireless interference channel where the channel coefficients are time-varying and are drawn from a continuous distribution, the sum capacity is characterized as C(SNR)=K/2log (SNR)+o(log( SNR), which almost surely has K/2 degrees of freedom.
Multi-Cell MIMO Cooperative Networks: A New Look at Interference
TL;DR: An overview of the theory and currently known techniques for multi-cell MIMO (multiple input multiple output) cooperation in wireless networks is presented and a few promising and quite fundamental research avenues are also suggested.
An iteratively weighted MMSE approach to distributed sum-utility maximization for a MIMO interfering broadcast channel
Qingjiang Shi,Meisam Razaviyayn,Zhi-Quan Luo,Chen He +3 more
- 22 May 2011
TL;DR: This paper proposes a linear transceiver design algorithm for weighted sum-rate maximization that is based on iterative minimization of weighted mean squared error (MSE) and extends the algorithm to a general class of utility functions and establishes its convergence.
1.7K