Asynchronous Co-channel Interference Suppression in MIMO OFDM Systems Qiang Li†, Jing Zhu*, Xingang Guo* and C. N. Georghiades† †Electrical and Computer Engineering Department, Texas A&M University E-mail:{qiangli,georghiades}@ece.tamu.edu * Communication Technology Lab (CTL), Intel Corporation, E-mail:{jing.z.zhu,xingang.guo}@intel.com Abstract— We present algorithms to suppress the asynchronous co-channel interference (CCI) in MIMO OFDM systems, which is becoming the dominant limiting factor in the performance of the emerging high-density WLANs. The key challenge is that the cyclic prefix of the interference signal does not line up with that of the intended signal due to asynchronous transmission in WLAN. Therefore, the orthogonality among the different tones of the in- terference signal is destroyed and conventional frequency domain minimum mean square error (MMSE) cancelation techniques that measure the interference channel response for each tone can not work effectively. To suppress the asynchronous interference, we design an efficient estimator to measure the interference spatial covariance matrix using Cholesky decomposition and low- pass smoothing. Both a MMSE and a maximum a posteriori (MAP) receiver are derived based on the estimated interference statistics. Simulation results demonstrate the effectiveness of our solution. I. I NTRODUCTION Increasingly, co-channel interferences (CCI) is becoming the dominant performance limiting factor in emerging high- density WLAN (HD-WLAN)[6]. The problem is exacerbated when more and more access points (AP)s are deployed in areas, such as office building, airport, university campus, etc., to provide network access for increasing number of mobile users. Only limited orthogonal channels (typically 3 or 8) are available. As a result, multiple cells that are operated on the same channel cannot be separated far enough and will interfere with each other if active at the same time. The next generation WLAN technology - 802.11n - combines orthogonal frequency division multiplex (OFDM) and multiple input multiple output (MIMO) techniques, providing good op- portunities for achieving not only higher per-link throughput, but also better interference suppression capability. Researchers have investigated the issue of CCI suppression extensively since Winters’s seminal paper [1]. The use of multiple antennas brings extra degrees of freedom for CCI suppression. [2] proposed a technique based on multiuser detection to cancel MIMO CCI for flat fading channels. Considering OFDM modulation and a time-varying channel, [3] designed an adaptive array processing scheme by using a MMSE diversity combiner. As pointed out in [4], the previous frequency domain approaches have difficulties in suppressing asynchronous interference, so they proposed a space-time filter to suppress CCI by utilizing the OFDM cyclic-prefix structure. [5] is the most relevant to our work, which adopted a MMSE method and proposed to estimate the interference covariances for each subcarrier (or tone) by short training and utilizing the correlation among different tones. Besides the physical layer signal processing approaches, [6] designed a medium access control (MAC) based solution which adapts carrier sensing threshold to mitigate CCI from neighboring cells. It was shown by test-bed experiments that the proposed adaptive CSMA scheme can effectively address so-called “hidden and exposed terminal” problems and significantly improve network throughput. Typically, CCI in a WLAN is asynchronous due to the use of a random access protocol, namely CSMA/CA (Carrier Sensing Medium Access/ Collision Avoidance). It was shown in [4] that the conventional frequency domain CCI cance- lation by estimating both channels cannot work effectively because the cyclic padding OFDM modulation structure to maintain inter subcarrier orthogonality has been destroyed. Hence, we adopted a statistical methodology – modeling the asynchronous (co-channel) interference as a zero-mean, time uncorrelated and spatially colored stationary Gaussian random process, and designed an efficient spatial covariance estimation algorithm by utilizing the OFDM symbol structure and matrix decomposition techniques. Simulation results show that our method can achieve packet error rate (PER) performance comparable to synchronized cancellation. The rest of the paper is organized as follows. Section II describes the system model, and introduces the effect of asynchronous interference. An efficient spatial covariance estimation method for MIMO OFDM signals is proposed in Section III. In Section IV, the MMSE receiver enhanced with asynchronous CCI suppression capability is presented, as well as a modification for space-time coded systems is discussed. Then, the optimum MAP detector to minimize bit error probability is developed. Section VI shows the performance of our algorithms by extensive simulations. Finally, Section VII concludes. Throughout this paper, normal letters indicate scalar quan- tities and boldface fonts denote matrices and vectors. For any matrix M we write its transpose as M T and M H is its conjugate transpose. x * denotes the conjugate of x. The superscript k represents the k-th subcarrier. 1-4244-0353-7/07/$25.00 ©2007 IEEE This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the ICC 2007 proceedings.