Abstract
The impact of interference on multiple-input multiple-output (MIMO) systems has recently attracted interest. Most studies of channel estimation and data detection for MIMO systems consider spatially and temporally white interference at the receiver. In this paper, we address channel estimation, interference correlation estimation, and data detection for MIMO systems under both spatially and temporally colored interference. We examine the case of one dominant interferer in which the data rate of the desired user could be the same as or a multiple of that of the interferer. Assuming known temporal interference correlation as a benchmark, we derive maximum likelihood (ML) estimates of the channel matrix and spatial interference correlation matrix, and apply these estimates to a generalized version of the Bell Labs Layered Space-Time (BLAST) ordered data detection algorithm. We then investigate the performance loss by not exploiting interference correlation. For a (5,5) MIMO system undergoing independent Rayleigh fading, we observe that exploiting both spatial and temporal interference correlation in channel estimation and data detection results in potential gains of 1.5 dB and 4 dB for an interferer operating at the same data rate and at half the data rate, respectively. Ignoring temporal correlation, it is found that spatial correlation accounts for about 1 dB of this gain.
Highlights
Wireless systems with multiple transmitting and receiving antennas have been shown to have a large Shannon channel capacity in a rich scattering environment [1, 2]
While the majority of the studies deals with channel capacity, in this paper we focus on the achievable symbol error rate performance of a multiple-input multi-output (MIMO) link with interference
In the case of a single dominant interferer and large signal-to-noise ratio (SNR), we show that spatial and temporal second-order interference statistics can be decoupled in the form of a matrix Kronecker product
Summary
Wireless systems with multiple transmitting and receiving antennas have been shown to have a large Shannon channel capacity in a rich scattering environment [1, 2]. While the majority of the studies deals with channel capacity, in this paper we focus on the achievable symbol error rate performance of a MIMO link with interference. Most studies of channel estimation and data detection for MIMO systems assume spatially and temporally white interference. The new ML algorithm serves as a performance benchmark when temporal and spatial interference correlation are exploited in joint channel estimation and data detection. Comparisons are made to the well-known direct matrix inversion (DMI) algorithm [17], generalized to multiple input signals, a batch method that does not require estimates of channel and spatial interference correlation matrices. The notation (·)T refers to transpose, (·)∗ refers to conjugate, (·)† refers to conjugate transpose, and IN refers to an N × N identity matrix
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
