What is the simplest way to estimate interference?

In the considered network, if (d1, ..., dK), are carefully chosen such that interference alignment is feasible, then there exist transmitter beamforming and receiver filtering matrices that satisfy the following conditions:

What is the simplest way to calculate the transmission power of a data stream?

The simulations confirm that if the parameters of the algorithm are properly designed, then the iterative stochastic power control and transceiver design converges.

What is the way to estimate the interference?

An iterative optimization of the transmitter beamforming and the receiver filtering matrices is proposed in [3] which demands only local CSI at each terminal.

What is the way to estimate interference signals?

The beamforming mentioned in Section II can be performed such that, at each destination, interference signals are aligned in the same subspace which is distinct from the desired signal subspace.

what is the exact value of Qk(n 1)?

Since the exact value of Qk(n − 1) is unknown at Dk, it chooses the receiver filters as followsudk = ν d [ Q̂k(n− 1) ] , d = 1, ..., dk.

What is the mean condition of the stochastic power control algorithm?

In the following the authors prove that the estimated interference function in (24) satisfies the mean condition, the Lipschitz condition, and the growing condition.

Open AccessProceedings Article10.1109/BLACKSEACOM.2013.6623375

Distributed interference alignment and power control for wireless MIMO interference networks with noisy channel state information

Hamed Farhadi, +4 more

- 03 Jul 2013

- pp 23-27

TL;DR: An iterative algorithm is proposed to perform stochastic power control and transceiver design based on only noisy local CSI in a multi-input multi-output (MIMO) interference network.

Abstract: This paper considers a multi-input multi-output (MIMO) interference network in which each transmitter intends to communicate with its dedicated receiver at a certain fixed rate. It is known that when perfect CSI is available at each terminal, the interference alignment technique can be applied, to align the interference signals at each receivers in a subspace independent of the desired signal subspace. The impact of interference can hence be eliminated. In practice, however, terminals in general can acquire only noisy CSI. Interference alignment cannot be perfectly performed to avoid interference leakage in the signal subspace. Thus, the quality of each communication link depends on the transmission power of the unintended transmitters. To solve this problem, we propose an iterative algorithm to perform stochastic power control and transceiver design based on only noisy local CSI. The transceiver design is conducted based on the interference alignment concept, and the power control seeks solutions of efficiently assigning transmit powers to provide successful communications for all transmitter-receiver pairs.

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Most frequently asked questions

1. What are the contributions in "Distributed interference alignment and power control for wireless mimo interference networks with noisy channel state information" ?

This paper considers a multi-input multi-output ( MIMO ) interference network in which each transmitter intends to communicate with its dedicated receiver at a certain fixed rate.. To solve this problem, the authors propose an iterative algorithm to perform stochastic power control and transceiver design based on only noisy local CSI.. The transceiver design is conducted based on the interference alignment concept, and the power control seeks solutions of efficiently assigning transmit powers to provide successful communications for all transmitter-receiver pairs.

2. What is the filter output of Dk isyk?

The filter output of Dk isyk = U ∗ kHkkVkxk +K∑l=1,l 6=kU∗kHklVlxl +U ∗ kzk, (2)where U∗k denotes the conjugate transpose of matrix Uk; Hkl is the channel matrix from Sl to Dk; zk is zero mean complex Gaussian noise, i.e. zk ∼ CN (0, N0InDk ) in whichN0 is the noise power and InD k is the nDk ×n D k identity matrix.

3. what is the standard stochastic power control algorithm?

The stochastic power control algorithm initializes power vector and iteratively updates the power vector as followsp(i+ 1) = (1− α(i))p(i) + α(i)̂I (p(i), θ) , (20)where α(i) is the step size at the ith iteration and Î(p(i), θ) is an estimation of the interference function for a given p(i) in which θ is a random variable.

4. What is the interference covariance matrix for the receiver filter?

Dk beamforms its training sequences with a fixed power pF uniformly allocated to different sequences, using an nDk × dk matrix V r k.

Citations

•Proceedings Article•10.1109/WCNC.2013.6555053

Distributed interference alignment and power control for wireless MIMO interference networks

Hamed Farhadi, +2 more

- 07 Apr 2013

TL;DR: This paper considers joint transceiver design and power control for K-user multiple-input multiple-output (MIMO) interference networks and proposes iterative algorithms to perform power control to guarantee successful communication while designing transmitter beamforming matrices and receiver filtering matrices according to the interference alignment concept.

...read moreread less

Journal Article•10.1109/TWC.2020.2974465

Reciprocity Calibration of TDD MIMO Channel for Interference Alignment

Heng Zhao, +2 more

- 25 Feb 2020

- IEEE Transactions on Wireless Communicat...

TL;DR: The modeling of the non-reciprocity for the TDD MIMO channels and a corresponding calibration method to minimize the mismatch are provided and highlight the indispensability of the reciprocity calibration for approaching the network capacity gain promised by IA.

...read moreread less

•Book Chapter•10.5772/59200

Interference Alignment — Practical Challenges and Test-bed Implementation

Nima N. Moghadam, +4 more

- 26 Nov 2014

- arXiv: Information Theory

TL;DR: Data traffic over wireless communication networks has experienced a tremendous growth in the last decade, and it is predicted to exponentially increase in the next decades.

...read moreread less

Coordinated Transmission for Wireless Interference Networks

Hamed Farhadi

- 01 Jan 2014

TL;DR: Wireless interference networks refer to communication systems in which multiple source–destination pairs share the same transmission medium, and each source’s transmission interferes with the other sources’ transmission.

...read moreread less

On Multiantenna Cellular Communications: From Theory to Practice

Nima N. Moghadam

- 01 Jan 2017

TL;DR: Today, wireless communications are an essential part of the authors' everyday life and both the number of users and their demands for wireless data have increasedtremendously during the last decade.

...read moreread less

References

Monograph•10.1017/CBO9780511810817

Matrix analysis: Frontmatter

Roger A. Horn, +1 more

- 01 Jan 1985

TL;DR: This book presents results of both classic and recent matrix analyses using canonical forms as a unifying theme, and demonstrates their importance in a variety of applications.

...read moreread less

21.4K

•Journal Article•10.1109/TIT.2008.926344

Interference Alignment and Degrees of Freedom of the $K$ -User Interference Channel

Viveck R. Cadambe, +1 more

- 01 Aug 2008

- IEEE Transactions on Information Theory

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.

...read moreread less

3.6K

Journal Article•10.1109/49.414651

A framework for uplink power control in cellular radio systems

Roy D. Yates

- 01 Sep 1995

- IEEE Journal on Selected Areas in Commun...

TL;DR: It is shown that systems in which transmitter powers are subject to maximum power limitations share these common properties, which permit a general proof of the synchronous and totally asynchronous convergence of the iteration p(t+1)=I(p(t)) to a unique fixed point at which total transmitted power is minimized.

...read moreread less

2.6K

Journal Article•10.1109/TVT.2003.819629

Solution of the multiuser downlink beamforming problem with individual SINR constraints

Martin C. Schubert, +1 more

- 30 Jan 2004

- IEEE Transactions on Vehicular Technolog...

TL;DR: The optimality and global convergence of the algorithm is proven and stopping criteria are given, and the global optimum of the downlink beamforming problem is equivalently obtained from solving a dual uplink problem, which has an easier-to-handle analytical structure.

...read moreread less

1.3K

Journal Article•10.1109/TIT.2008.926460

Communication Over MIMO X Channels: Interference Alignment, Decomposition, and Performance Analysis

Mohammad Ali Maddah-Ali, +2 more

- 01 Aug 2008

- IEEE Transactions on Information Theory

TL;DR: It is shown that by using mixed design schemes, rather than decomposition schemes, and taking the statistical properties of the interference terms into account, the power offset of the system can be improved.

...read moreread less

1.2K

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Distributed interference alignment and power control for wireless MIMO interference networks with noisy channel state information

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AI Agents for this Paper

Most frequently asked questions

1. What are the contributions in "Distributed interference alignment and power control for wireless mimo interference networks with noisy channel state information" ?

2. What is the filter output of Dk isyk?

3. what is the standard stochastic power control algorithm?

4. What is the interference covariance matrix for the receiver filter?

5. What is the simplest way to estimate interference?

6. What is the simplest way to calculate the transmission power of a data stream?

7. What is the way to estimate the interference?

8. What is the way to estimate interference signals?

9. what is the exact value of Qk(n 1)?

10. What is the mean condition of the stochastic power control algorithm?

Citations

Distributed interference alignment and power control for wireless MIMO interference networks

Reciprocity Calibration of TDD MIMO Channel for Interference Alignment

Interference Alignment — Practical Challenges and Test-bed Implementation

Coordinated Transmission for Wireless Interference Networks

On Multiantenna Cellular Communications: From Theory to Practice

References

Matrix analysis: Frontmatter

Interference Alignment and Degrees of Freedom of the $K$ -User Interference Channel

A framework for uplink power control in cellular radio systems

Solution of the multiuser downlink beamforming problem with individual SINR constraints

Communication Over MIMO X Channels: Interference Alignment, Decomposition, and Performance Analysis

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