A low complexity suboptimal MIMO receiver: the combined ZF-MLD algorithm

Abstract

IEMN-DHS UMRCNRS X520. ENlC CitC Scicntifcquc -Rue Gugliclnio Mat-coni. 50650 Villcneuvc d'Ascq. Frailcc 4 I, Bd. Vaukin. 5W46 Lillc ~IEMN-DHS UMRCNRS. ISEN A b r n .~~~r -R e c e~i t l~. nirelcss technologies have known an incrc;iring succcss. rhos becoming an interesting field for study. O n e nf tlie topics o f r rch are multiple ante!ina arrays. Signal rreowr! in that rase is not obvious. Different methods with different performances have been suggestcd. F r o m il statistical analysis of wrvrs a t the outpiit o f Zero-Forcing, we have constructed a method. which w c present in this article. that combines Zero-Fvrcing and hlarimum Likelihood. We will demonstrate that it provides bath a lo\% complexity and nearly aplimal results regarding Binary Error Rare (BER). Furthermore. w e will show its rele\.;tnr> compared to t h e YBLAST algorithm.

Classifier based low-complexity MIMO detection for spatial multiplexing systems

“…5. In the same figure, the performance of the following three MIMO detectors are shown for comparison: (1) ZF detector, (2) ML detector, and (3) combined ZF-ML detector [3]. As can be seen in the BER performance of the proposed classifier based MIMO detector is significantly better than that of the ZF-detector, i.e.…”

“…On the other end of the complexity spectrum the equalizer based MIMO detection schemes can be found. These include zero-forcing (ZF) detector [3] and minimum-mean-squareerror (MMSE) detector [4]. The ZF-detector and the MMSEdetector have the minimal computational burden as they require only matrix operations, e.g.…”

Performance Analysis of the Cooperative ZP-OFDM: Diversity, Capacity and Complexity

“…(11) enjoys the best performance; However, it requires the highest complexity as well. As shown in [33], the number of arithmetic operations for the MLE in Eq. (11) is O |x| N M N. We learn from the comparison that the major advantage of LEs is their low decoding complexity.…”

Broadband transmission performance and antenna displacement tolerance in 4×4 short-range MIMO simple decoding

“…Although transmission rate can be improved by increasing frequency bandwidth and the number of antenna elements to be used for SR-MIMO transmission, signal processing complexity per unit time for MIMO detection is also increased, and as a result the power consumption is increased [5]. To solve the problem, we have proposed a simple decoding method [6] that reduces the complexity by performing MIMO detection with an analog circuit.…”