Interference Management

11 Jan

A. Interference Management with Delayed and Distributed CSIT

Channel state information at the transmitter (CSIT) plays an important role in interference management in wireless systems. Interference networks with global and instantaneous CSIT provide a great improvement of performance. In practice, however, obtaining global and instantaneous CSIT for transmitter cooperation is especially challenging, when the transmitters are distributed and the mobility of wireless nodes increases. In an extreme case where the channel coherence time is shorter than the CSI feedback delay, it is infeasible to acquire instantaneous CSIT in wireless systems. Obtaining global knowledge of CSIT is another obstacle for realizing transmitter cooperation when the backhaul or feedback link capacity is very limited for CSIT sharing between the distributed transmitters. Therefore, one of fundamental questions is that it still possible to obtain benefits in increasing the scaling law of the rate, i.e., degress-of-freedom (DoF), for interference networks under these two practical constraints?

Motivated by this question, I have proposed interference alignment algorithms exploiting local and moderately-delayed CSIT. The proposed method is a structured space-time repetition transmission technique that exploits both current and outdated CSIT jointly to align interference signals at unintended receivers in a distributed way. With this algorithm, they characterize trade-off regions between the sum of degrees of freedom (sum-DoF) and feedback delay in vector broadcast channels, the X channels, and a three-user interference channel to reveal the impact on how the CSI feedback delay affects the sum-DoF of the interference networks.

The key finding from this work is that distributed and moderately-delayed CSIT is useful to obtain strictly better the sum-DoF over the case of no CSI at the transmitter in a certain class of interference networks. For some classes of vector broadcast channels and X channels, I have illustrated how to optimally use distributed and moderately-delayed CSIT to yield the same sum-DoF as instantaneous and global CSIT. 

[Related Papers]
a. Namyoon Lee and Robert W. Heath Jr., “Space-Time Interference Alignment and Degrees of Freedom Regions for the MISO Broadcast Channel with Periodic CSI Feedback,” IEEE Transaction on Information Theory, vol. 60, no. 1, pp. 515-528, Jan. 2014.
b. Namyoon Lee, Ravi Tandon, and Robert W. Heath Jr., “Distributed Space-Time Interference Alignment,” Submitted to IEEE Transactions on Wireless Communications, April 2014.
c. Namyoon Lee and Robert W. Heath, “Not Too Delayed CSIT Achieves the Optimal Degrees of Freedom,” IEEE Allerton’12, Oct. 2012.
d. Namyoon Lee and Robert W. Heath, “CSI Feedback Delay and Degrees of Freedom Gain Trade-Off for the MISO Interference Channel,” IEEE Asilomar conference, Nov. 2012.

B. Interference Management for Multi-Way Communication Networks
   Due to the superposition and broadcast nature of the wireless medium, unmanaged interference results in diminishing data rates in wireless networks. With a recently developed network coding strategy, however, it was demonstrated that interference is no longer adverse in communication networks, provided that it can sagaciously be harnessed. This approach of exploiting interference has opened the possibility of better performance in the interference-limited communication regime than traditionally thought possible. For example, in wireless networks, the concept of physical layer (analog) network coding has shown that this strategy can attain higher rates over routing-based strategies under a certain network topology.
   To advance the idea of interference exploitation, I have proposed new physical-layer network coding strategies termed as signal space alignment for network coding and space-time physical-layer network coding (ST-PNC) for general multi-way communication network topologies. With theses strategies, I characterized the sum-DoF of general multi-way relay networks in terms of relevant system parameters, chiefly the number of users, the number of relays, and the number of antennas at relays. A major implication of the derived results is that efficiently harnessing both transmitted and overheard signals as side-information brings significant performance improvements to multi-way relay networks.
[Related Papers]
a. Namyoon Lee and Robert W. Heath Jr., “Space-Time Physical-Layer Network Coding,” Submitted to IEEE Journal of Selected Area on Communications, March 2014.
b. Namyoon Lee, Jong-Bu Lim, and Joohwan Chun, “Degrees of Freedom on the MIMO Y Channel : Signal Space Alignment for Network Coding,” IEEE Transaction on Information Theory, vol. 56, no. 7, pp. 3332-3342, July 2010.
c. Namyoon Lee and Joowhan Chun, “Degrees of Freedom for the MIMO Gaussian K-way Relay Channel: Successive Network Code Encoding and Decoding,” IEEE Transaction on Information Theory, vol. 60, no. 3, pp. 1814-1821, March 2014.

d. Kwang-Won Lee, Namyoon Lee, and Inkyu Lee, “Achievable Degrees of Freedom on MIMO Two-way Relay Interference Channels,” IEEE Transaction on Wireless Communications, vol. 12, no. 4, pp. 1472-1480, April. 2013.

e. Kwang-Won Lee, Namyoon Lee, and Inkyu Lee, “Achievable Degrees of Freedom on K-user Y Channels, ” IEEE Transaction on Wireless Communications, vol 11, pp. 1210 – 1219, Mar. 2012.
f. Hyun-Jong Yang, Young-Chul Kim, Namyoon Lee, and Arogyaswami Paulraj, “Achievable Sum-Rate of the Multiuser MIMO Two-Way Relay Channel in Cellular Systems: Lattice Coding-Aided Linear Precoding,” IEEE Journal of Selected Area on Communications, vol. 30, no. 8, pp. 1304-1318, Sep. 2012.

C. Interference Management for Multi-Hop Networks

   Interference management is complicated in the multi-hop networks because relay nodes between the source-destination pairs propagate the mixture of interference signals as well as desired signals on the network. This complicates the selection and design of relay strategies as it is not clear the extent to which a relay should forward, cancel, align, or otherwise manage interference. In this research direction, I have proposed interference-aware relay transmission techniques exploiting the concept of aligned interference neutralization for the multiple-input-multiple-output (MIMO) two-hop interference channels to characterize the scaling law of network sum-capacity.

[Related Papers]
a. Namyoon Lee and Chenwei Wang “Aligned Interference Neutralization and the Degrees of Freedom of the Two-User Wireless Networks with an Instantaneous Relay,” IEEE Transaction on Communications, vol. 61, no. 9, pp. 3611 – 3619, Sept. 2013.
b. Namyoon Lee and Robert W. Heath Jr., “Degrees of Freedom for the Two-Cell Two-Hop MIMO Interference Channel: Interference-Free Relay Transmission and Spectrally Efficient Relaying Protocol,” IEEE Transaction on Information Theory, vol. 59, no. 5 pp. 2882-2896, May 2013.
D. Interference Management with Limited Feedback
  Limited feedback is an essential technique for realizing advanced multi-antenna transmission techniques in multi-antenna wireless networks. With random vector quantization (RVQ) techniques, I have analyzed the impact of the limited channel state information feedback in various wireless networks.
[Related Papers]
a. Namyoon Lee and Wonjae Shin, “Adaptive Feedback Scheme on K-cell MISO Interfering Broadcast Channel with Limited Feedback,” IEEE Transaction on Wireless Communications, vol. 10, pp. 401-406, Feb. 2011

b. Junil Choi, Bruno Clerckx, Namyoon Lee, and Gil Kim, “A New Design of Polar-Cap Differential Codebook for Temporally/Spatially Correlated MISO Channels,” IEEE Transaction on Wireless Communications, vol. 11, pp. 703-711, Feb. 2012.
c. Namyoon Lee, Wonjae Shin, Robert W. Heath and Bruno Clerckx, “Interference Alignment with Limited Feedback on Two-cell Interfering MIMO-MAC,” IEEE International Symposium on Wireless Communication Systems (ISWCS), Aug. 2012. (Invited)


Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s

%d bloggers like this: