Journal Article10.1109/TVT.2015.2472463
Interference Alignment Transceiver Design by Minimizing the Maximum Mean Square Error for MIMO Interfering Broadcast Channel
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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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Abstract: An interference alignment (IA) transceiver design scheme for multiple-input–multiple-output (MIMO) multicell multiuser wireless communication systems is proposed by minimizing the maximum mean square error (MSE) of the received symbols to improve fairness among users. The formulated Min-Max MSE optimization problem is not jointly convex on the transmit precoders and receive filters and, thus, is very difficult to solve directly. An iterative method is proposed to solve the optimization problem to get a suboptimal solution instead. Considering that if the receive filters are fixed, the Min-Max MSE problem can be reformulated as a second-order cone programming problem, and if the transmit precoders are fixed, the closed-form receive filters minimizing the receive MSE can be easily obtained, and the formulated Min-Max MSE problem is solved by alternatively optimizing the transmit precoders and the receive filters. The convergence of the proposed algorithm is proved, which shows its feasibility. Furthermore, a robust Min-Max MSE algorithm is proposed to counter the channel uncertainty. Simulation results show that the proposed Min-Max MSE algorithm can achieve IA when the antennas are configured to be strong IA proper and when the users in the network are of the same signal-to-noise ratio (SNR). Analysis indicates that the proposed Min-Max IA transceiver design scheme can significantly improve user fairness with a possible cost of sum-rate reduction. Results also show that the proposed robust design algorithm provides better performance when lacking perfect channel state information (CSI).
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Citations
Caching UAV Assisted Secure Transmission in Hyper-Dense Networks Based on Interference Alignment
TL;DR: In this paper, UAV assisted secure transmission for scalable videos in hyper-dense networks via caching is studied and the feasibility conditions of the proposed scheme are derived, and the secrecy performance is analyzed.
Optimization or Alignment: Secure Primary Transmission Assisted by Secondary Networks
TL;DR: Two schemes to improve the sum rate of SUs while guaranteeing the secrecy rate of PU and the principle of interference alignment is employed to eliminate interference from PU and other SUs at each secondary receiver and the interference from SUs is zero-forced at the primary receiver.
Joint Transceiver and Power Splitting Optimization for Multiuser MIMO SWIPT Under MSE QoS Constraints
TL;DR: An iterative optimization framework composed of joint transmitter and PS factor optimization (JTxPS) subproblem and a receiver side minimum mean-square error (MMSE) minimization subproblem is proposed, and by iteratively solve the two subproblems, the original optimization problem is solved.
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Proactive Jamming Toward Interference Alignment Networks: Beneficial and Adversarial Aspects
TL;DR: This paper considers two opposite scenarios, beneficial and adversarial jamming, toward IA networks, and based on which two proactive jamming schemes are proposed, which will disrupt the potential eavesdropping significantly without affecting the transmission of IA users.
Feasibility Analysis and Clustering for Interference Alignment in Full-Duplex-Based Small Cell Networks
TL;DR: This paper exploits interference alignment (IA) to address the interference in small cell networks, where some of the base stations simultaneously serve both uplink and downlink users on the same frequency via FD, and proposes two clustering methods, minimized spectrum consumption clustering and minimized interference leakage clustering, both of which can perfectly eliminate the intra-cluster interference with IA.
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