Mobile Wireless Transmission - 2020
By 2020 we will need dramatic improvements in radio access networks. The ITU has defined goals for IMT-Advanced radio network to be fielded in the 2010-12 timeframe [G3-forum]. These are 1Gbps indoors and 100Mbps outdoors, coverage or areal reliability of 99% and round trip delays of <5ms. We should expect a 2020 radio network to be at least a factor of ten better than IMT-Advanced goals.
A number of technologies will be needed to meet these ambitious targets: higher spectrum efficiency, flexible spectrum sharing and improved link diversity/reliability. Promising techniques under development include cross-layer design, multiple antennas, cognitive radio, multi-user coding and opportunistic scheduling. These improvements have already entered 4G technologies such as WIMAX and 3GPP-LTE, but significant refinement and scaling of these techniques are still needed.
We focus on two key areas: The first is in fighting interference. Cellular networks are increasingly interference limited, rather than noise limited, and interference mitigation can yield dramatic improvements. Our approaches include eclectic combination of emerging ideas including spatial processing and coding, interference alignment, and avoidance. In all cases, better theoretical understanding and practical solutions are needed. The second is use of relays and network coding to buy improved network performance. This too is attacked from a theoretic and experimental (channel measurement) approaches.
(a) Based-Centralized Transmission Schemes for Multi-Antenna Broadcast Systems
Interference is one of the major limiting factors in cellular radio systems. With the introduction of multiple antennas in cellular networks, there are new opportunities to employ the spatial adaptation to mitigate the inter-cell interference. In order to increase the cell spectral efficiency in cellular networks, each base station employing multiple antennas send multiple data streams to multiple subscriber stations simultaneously on the same time-frequency resource as other adjacent BSs, which results in interference-limited networks. Therefore, multiple base stations should collaborate to minimize inter-cell interferences, especially in the edge region of the BSs’ cell. We study base-centralized transmission (BCT) for multi-antenna multi-cell systems . By the phrase "base-centralized transmission" we mean that all the required signal processing takes place at the BSs, while the users just read the received signals and detect the transmitted signals with trivial signal processing. The BCT system has the potential to suppress dominant inter-cell interferences, while offering multiplexing rate and diversity gain. In addition, the BCT approach has an edge from a complexity and cost perspective because the burden of complicated MIMO processing is shifted to the BS, which is less sensitive to the cost and power consumption of signal processing.
(b) MIMO network coding
Future generation of the wireless internet requires substantially large bandwidth with low latency. It has been shown that multiple antennas are a promising technique to improve the capacity of the wireless network. As modern communication systems are often interference-limited, managing and utilizing the interference in the wireless network becomes a key factor to achieve Gbps/sub-milliseconds delay communication.
Recently, in the two-way channel with relay, Physical-Layer Network Coding (PNC) was proposed, which doubles the throughput by introducing controlled interference in the relay and utilizing it with broadcast strategy. In AWGN channel, it is known that lattice-based encoding/decoding can provide near single user capacity. However, PNC in a fading channel is generally an open problem. As a practical transmission scheme in the fading channel, we consider Physical Network Coding with Bit-Interleaved Coded Modulation (BICM-PNC). We analyzed the performance of BICM-PNC in terms of capacity and bit error rate in various channel conditions. We found that Space-Time BICM with Iterative Demapping-and-Decoding (IDD) can approach near single-user performance with the moderate number of iterations.
List of papers/publications
- E. Stauffer, D Tujkovic and A. Paulraj. Code Rate-Diversity-Multiplexing Tradeoff, IEEE Trans.Information Theory, Volume 55, Vol. 1, Jan. 2009 Page(s):245 – 254.
- B Bandemer, C. Oestges, N Czink and A. Paulraj. Physically motivated fast-fading model for indoor peer-to-peer channels Electronics Letters Volume 45, Issue 10, May 7 2009 Page(s):515 – 517
- G Zheng, KK Wong and A Paulraj. Collaborative-Relay Beamforming With Perfect CSI: Optimum and Distributed Implementation IEEE Trans Signal Processing Letters Volume 16, Issue 4, April 2009 Page(s):257 – 260
- G Zheng, KK Wong and A Paulraj. Robust Collaborative-Relay Beamforming IEEE Trans Signal Processing, IEEE Transactions on : Accepted for publication
- A Sezgin, G Altay and A Paulraj. Generalized Partial Feedback Based Orthogonal Space-Time Block Coding IEEE Trans Wireless Communications, Volume 8, Issue 6, June 2009 Page(s):2771 - 2775
- M Charafeddine and A Paulraj. 2—Sector interference channel communication for sum rates and minimum rate maximization. CISS March 2009 Page(s):951 – 956
- M Charafeddine and A Paulraj. Maximum sum rates via analysis of 2-user interference channel achievable rates region CISS March 2009 Page(s):170 – 174
- L Jalloul, N. Czink, B. Hochwald and A Paulraj. Why Downlink Cyclic Delay Diversity Helps Uplink Transmit Diversity IEEE VTC Spring 2009, April 2009 Page(s):1 – 5
General Interest Talks (all Prof Paulraj)
Plenary, VTC Spring 2009, Barcelona, April 2009
Plenary, Telecom Asia, New Delhi, Dec 2008
Plenary, Broadband India, New Delhi, June 2009
Invited Talk, SESI Stanford Conf. Bangalore, Dec 2008
Invited Talk, KAIST Taejon, Korea Aug 2009
Invited Talk, SAIT, Samsung, Soeul, Korea Aug 2009
Invited Talk, ETRI, Taejon, Korea Aug 2009
Invited Talk, SK Telecom, Souel, Korea Aug 2009
Invited Talk, Univ. of Alberta, April 2009
Invited Talk, TWAS, Mexico City, Nov 2008
Professor Arogyaswami Paulraj
Post Doctoral Scholar Alireza Ghaderipoor
PhD Student Tae-Min Kim