K-best List Sphere Detector Research Articles

Performance and ASIC Designs of the K-best LSD and LMMSE Detectors for LTE Downlink

We consider performance comparison and application specific integrated circuit (ASIC) designs of linear minimum mean-square error (LMMSE) and K-best list sphere detector (LSD) algorithms for 4 × 4 and 8 × 8 multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. Requirements for higher data rate and lower power consumption set new challenges for implementation. In order to minimize the power consumption, an optimal detector would be able to switch the detection algorithm to suit the channel conditions. The detectors are designed for three different modulation schemes using 28 nm complementary metal oxide semiconductor (CMOS) technology. The communications performance is evaluated in the Third Generation Partnership Project (3GPP) Long-Term Evolution (LTE) system. The impact of transmit precoding is considered. The ASIC designs aim at providing the hardware design aspects to the comparison of detectors. The designs are synthesized and complexity and power consumption results are found. Based on the ASIC synthesis and communications performance results, we show the performance–energy efficiency and performance–complexity comparison. We also present the most suitable scenarios for a low-power detector and show how the transmit precoding impacts the detector selection.

Parallel Distributed Arithmetic Based K-Best List Sphere Detection Algorithm for LTE Standard

3GPP Long Term Evolution (LTE) is the upcoming standard for cellular mobile communication. To meet the requirements of high data rate and low latency interactive services, Orthogonal Frequency Division Multiplexing (OFDM) in combination with MIMO is used. From a bit error rate (BER) performance perspective, maximum likelihood (ML) detection is the preferred detection method for multiple input multiple output (MIMO) communication systems. However, for high transmission rates, the K-best algorithm provides close-to-ML bit error rate (BER) performance with its iterative tree search, while its circuit complexity is reduced compared to an exhaustive search. In this paper, Distributed Arithmetic (DA) using parallel architecture based K-best List Sphere Detector (LSD) for a 3GPP LTE receiver is presented. About 50% of the computation time can be decreased and increase in speed with the help of this architecture.

Iterative Joint Detection, Decoding, and Channel Estimation in Turbo-Coded MIMO-OFDM

An iterative receiver for a multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) system is considered to jointly decode the transmitted bits and estimate the channel state. The receiver consists of a list detector, a turbo decoder, and a channel estimator that is based on the space-alternating generalized expectation-maximization (SAGE) algorithm. This paper proposes a way to improve the convergence of the iterative detection and decoding by using a priori information to also recalculate the candidate list, aside from the log-likelihood ratios (LLRs) of the coded bits. A new list parallel interference cancellation (PIC) detector is derived to approximate an a posteriori probability (APP) algorithm with reduced complexity and minimal losses of performance. Furthermore, the organization of spectrally efficient decision-directed (DD) SAGE channel estimation under a constrained number of detector-decoder iterations is optimized by computer simulations, and the SAGE algorithm itself is modified for nonconstant envelope constellations. The list recalculation is shown to improve convergence. It is also shown that the list PIC detector with good initialization outperforms the K-best list sphere detector (LSD) in the case of small list sizes, whereas the complexities of the algorithms are of the same order. Despite the low preamble density and fast-fading channel, the proposed iterative receiver shows robust performance.