Pioneering studies on adaptive spatio-temporal signal processing for mobile communications

Structure of interference canceling equalizer (ICE)

Fig.1 Structure of interference canceling equalizer (ICE)

Structure of OFDM MAP receiver

Fig.2 Structure of OFDM MAP receiver

 A main purpose of mobile communications is to use radio frequency resources more efficiently. For this purpose, cellular systems that reuse the same frequency channels at distant places have been introduced. Afterward, as multiple access, time-division multiple access (TDMA) and code division multiple access (CDMA) have been adopted, which results in much higher frequency efficiency than analog transmission. Furthermore, to accommodate a larger number of uses and to achieve high bit-rate transmission under a limited frequency band condition, “spatial channels” are needed as a new dimension.

The study on an interference canceller that can separate different spatial channels by adaptive spatial signal processing has begun since 1990s. First, a non-linear interference canceller called interference canceling equalizer (ICE) has been theoretically derived from the maximum likelihood detection. ICE can eliminate co-channel interference in addition to inter-symbol interference, which can be considered an enhanced version of an adaptive equalizer based on the maximum likelihood criterion. In contrast with conventional interference cancellers, ICE supposes that fading channels are time-varying and can track very fast fading channels. Therefore, ICE can maintain excellent performance even in the fast fading environment. Transmission performance of ICE has been evaluated by not only computer simulation but also field research. The field research installed ICE into DSP, and demonstrated that ICE with two receive antennas can separate two users’ signals which simultaneously share the same frequency channel. It was also shown that the ICE can almost double the system capacity. Since 2000, multiple-input multiple-output (MIMO) that spatially multiplexes signals by multiple transmit antennas has attacked munch attention. The channel capacity of MIMO with a constant frequency band grows proportionally with a number of antennas. Although MIMO is a kind of one-to-one communications, MIMO can be considered an extended version of ICE that exploits spatial channels.

Furthermore, a combination of an adaptive array antenna and ICE has been investigated and it was demonstrated that the combination can suppress interference which has the same incidence angle as that of a desired signal, or asynchronous interference which has different incidence angels with different training sequences.

Following such a combination, the study has focused on a combination of MIMO and coded-OFDM that can achieve high spectrum efficiency, and has investigated effective realization of the optimal MAP estimation for MIMO-OFDM. A proposed scheme extends joint signal detection and adaptive channel estimation of ICE, and adopts the expectation maximization (EM) algorithm. In addition, the proposed scheme performs statistical signal processing by using a factor graph and could advance studies of MIMO-OFDM.


[1] H. Suzuki, "Signal transmission characteristics of diversity reception with least-squares combining – relationship between desired signal combining and interference cancelling", IEICE B-II, vol. J75-B-II, no. 8, pp. 524-534, Aug. 1992.
[2] Fukawa, K. and H. Suzuki, "Blind Interference Canceling Equalizer for Mobile Radio Communications", IEICE Trans. Communi. vol. E77-B, no. 5, pp. 589-597, May 1994.
[3] H. Yoshino, K. Fukawa, H. Suzuki, "Adaptive interference canceller based upon RLS-MLSE", IEICE B-II, vol. J77-B-II, no. 2, pp. 74-84, Feb. 1994. (IEICE Best Paper Award).
[4] H. Yoshino, K. Fukawa and H. Suzuki, "Interference Canceling Equalizer (ICE) for mobile radio communication," IEEE Trans. on Vehicular. Technol, vol. 46, no. 4, pp. 849-861, Nov. 1997.
[5] T. Kashima, K. Fukawa, and H. Suzuki, "Adaptive MAP receiver via the EM algorithm and message passings for MIMO-OFDM mobile communications," IEEE Jour. on Select. Area in Communi, vol. 24, no. 3, pp. 437- 447, March 2006.
[6] T. Kashima, K. Fukawa and H. Suzuki, "Adaptive MAP detection via the EM algorithm for LDPC-coded MIMO-OFDM mobile communications," IEICE Trans. on Communi., vol. E90-B, no. 2, pp. 312-322, Feb. 2007. (IEICE Communication Society Best Paper Award)

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