Abstract
For single‐carrier transmission over delay‐spread multi‐input multi‐output (MIMO) channels, the computational complexity of the receiver is often considered as a bottleneck with respect to (w.r.t.) practical implementations. Multi‐antenna interference (MAI) together with intersymbol interference (ISI) provides fundamental challenges for efficient and reliable data detection. In this paper, we carry out a systematic study on the interference structure of MIMO‐ISI channels, and sequentially deduce three different Gaussian approximations to simplify the calculation of the global likelihood function. Using factor graphs as a general framework and applying the Gaussian approximation, three low‐complexity iterative detection algorithms are derived, and their performances are compared by means of Monte Carlo simulations. After a careful inspection of their merits and demerits, we propose a graph‐based iterative Gaussian detector (GIGD) for severely delay‐spread MIMO channels. The GIGD is characterized by a strictly linear computational complexity w.r.t. the effective channel memory length, the number of transmit antennas, and the number of receive antennas. When the channel has a sparse ISI structure, the complexity of the GIGD is strictly proportional to the number of nonzero channel taps. Finally, the GIGD provides a near‐optimum performance in terms of the bit error rate (BER) for repetition encoded MIMO systems.
Highlights
In single-carrier mobile transmission systems not exploiting a guard interval, there are two sources of intersymbol interference (ISI): static ISI due to pulse shaping and receive filtering, and dynamic ISI due to the time-varying delay spread of the physical channel
We carry out a systematic study on the interference structure of multi-input multi-output (MIMO)-ISI channels, and sequentially deduce three different Gaussian approximations to simplify the calculation of the global likelihood function
After a careful inspection of their merits and demerits, we propose a graph-based iterative Gaussian detector (GIGD) for severely delay-spread MIMO channels
Summary
In single-carrier mobile transmission systems not exploiting a guard interval, there are two sources of intersymbol interference (ISI): static ISI due to pulse shaping and receive filtering, and dynamic ISI due to the time-varying delay spread of the physical channel. State-space-based detectors, such as the Viterbi algorithm [1, 2] and the BCJR algorithm [3], provide an excellent performance since they benefit from the diversity gain of dynamic ISI and MAI, but their computational complexity is typically prohibitive. The JGA is already well known [5,6,7,8,9,10], while the GJGA and the IGA are new approaches proposed by the authors Corresponding to these three Gaussian approximations, three low-complexity iterative parallel soft interference cancellation [5, 11] algorithms, namely, joint Gaussian detector (JGD), grouped joint Gaussian detector (GJGD), and graph-based iterative Gaussian detector (GIGD), will be described by utilizing factor graphs [12, 13] as a general framework.
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