Pilot Contamination Elimination for Large-Scale Multiple-Antenna Aided OFDM Systems

Zhang, Jiankang; Zhang, Bo; Chen, Sheng; Mu, Xiaomin; El‐Hajjar, Mohammed; Hanzo, Lajos

doi:10.1109/jstsp.2014.2309936

Cited by 137 publications

(127 citation statements)

References 24 publications

Supporting

Mentioning

124

Contrasting

Unclassified

Order By: Relevance

“…It is worthy to remind that most of the above schemes must know not only the secondorder statistics of desired user channels, but also the secondorder statistics of interfering channels from users of different cells. Recently, the authors in [7] proposed a channel estimation strategy which can eliminate pilot contamination without the knowledge of any side-information. This strategy consists of an amalgam of downlink and uplink training.…”

Section: Introductionmentioning

confidence: 99%

Successive Pilot Contamination Elimination in Multiantenna Multicell Networks

Vu²,

Quek

2014

IEEE Wireless Commun. Lett.

View full text Add to dashboard Cite

Abstract-This paper addresses the problem of channel estimation in time-division duplex (TDD) multicell cellular systems, where the performance of such systems is usually bounded by a bottleneck due to pilot contamination. We propose two channel estimation schemes that completely remove pilot contamination. The exact closed-form expression for average mean square error (MSE) of the proposed estimators is derived. More importantly, our proposed estimators do not need to know the second-order statistics of either desired user channels or interfering user channels. Finally, simulated results confirm gains over existing channel estimation schemes.

show abstract

Section: Introductionmentioning

confidence: 99%

Successive Pilot Contamination Elimination in Multiantenna Multicell Networks

Vu²,

Quek

2014

IEEE Wireless Commun. Lett.

View full text Add to dashboard Cite

show abstract

“…This is in contrast to the conventional ZF, where W = H −1 . Afterwards, W is multiplied by the received signal using the transformed MIMO model presented in (5). Then, the output of the LLL-aided ZF will be z = z + H −1 n and since z = (T −1 x) ∈ Z, the original constellation symbols x can be recovered by multiplying with T after shifting, scaling and rounding as follows [7]:…”

Section: A Lll-aided Zf Detectormentioning

confidence: 99%

“…MIMO has been adopted as a key technique in the fourth generation (4G) mobile communications standards. Recently, large-scale MIMOs have been proposed in order to scale up the MIMO gains [4], [5].…”

Section: Introductionmentioning

confidence: 99%

Element-based Lattice Reduction aided K-Best detector for large-scale MIMO systems

Toma

El‐Hajjar

2016

2016 IEEE 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

Self Cite

View full text Add to dashboard Cite

Abstract-Recently, large-scale Multiple-Input MultipleOutput (MIMO) systems have caught great attention for increasing the system throughput as well as improving the system performance. The main challenge in the design of these MIMO systems is the detection techniques used at the receiver. Lattice Reduction (LR) techniques have shown good potential in MIMO decoding due to their good performance and low complexity compared to Maximum Likelihood (ML) detector. The Lenstra, Lanstra, and Lovasz (LLL) LR algorithm has been employed for decoding while combined with linear detectors such as ZF as well as with K-Best detection. However, the LLL-aided detectors have shown limited performance, when increasing the number of antennas at the transmitter and receiver. Therefore, in this paper we propose to use the so-called Element-based Lattice Reduction (ELR) combined with K-Best detector for the sake of attaining a better BER performance and lower complexity than the LLL-aided detection. Explicitly, the ELR-aided detectors are capable of attaining a 2 dB performance improvement at BER of 10 −5 compared to the LLL-aided detectors when considering a MIMO system with 200 transmit and receive antennas. Furthermore, for the same MIMO configuration, the ELR basis update requires nearly an order of magnitude reduction in the number of arithmetic operations compared to the LLL algorithm.

show abstract

“…Multiple-Input Multiple-Output (MIMO) techniques are characterised by an increased capacity as well as improved performance and hence the research in the MIMO design has seen a great interest for the last few years [1][2][3]. Recently, large-scale MIMOs have been proposed in order to scale up the MIMO gains [4,5], where, for example a large number of antennas can be implemented at the base station for supporting a large number of users.…”

Section: Introductionmentioning

confidence: 99%

Hardware Efficient Architecture for Element-Based Lattice Reduction Aided K-Best Detector for MIMO Systems

Halak

El‐Hajjar

Hassanein

2018

JSAN

Self Cite

View full text Add to dashboard Cite

Multiple-Input Multiple-Output (MIMO) systems are characterised by increased capacity and improved performance compared to the single-input single-output (SISO) systems. One of the main challenge in the design of MIMO systems is the detection of the transmitted signals due to the interference caused by the multiple simultaneously transmitted symbols from the multiple transmit antennas. Several detection techniques have been proposed in the literature in order to reduce the detection complexity, while maintaining the required quality of service. Among these low-complexity techniques is the Lattice Reduction (LR), which can provide good performance and significantly lower complexity compared to Maximum Likelihood (ML) detector. In this paper we propose to use the so-called Element-based Lattice Reduction (ELR) combined with K-Best detector for the sake of attaining a better Bit Error Ratio (BER) performance and lower complexity than the conventional Lenstra, Lanstra, and Lovasz (LLL) LR-aided detection. Additionally, we propose a hardware implementation for the ELR-aided K-Best detector for a MIMO system equipped with four transmit and four receive antennas. The ELR-aided K-Best detector requires an extra 18% increase in power consumption and an extra 20% in area overhead compared to a regular K-Best detector dispensing with ELR, where this increase in the hardware requirements is needed in order to achieve a 2 dB performance improvement at a bit error rate of 10 −5 .

show abstract

Pilot Contamination Elimination for Large-Scale Multiple-Antenna Aided OFDM Systems

Cited by 137 publications

References 24 publications

Successive Pilot Contamination Elimination in Multiantenna Multicell Networks

Successive Pilot Contamination Elimination in Multiantenna Multicell Networks

Element-based Lattice Reduction aided K-Best detector for large-scale MIMO systems

Hardware Efficient Architecture for Element-Based Lattice Reduction Aided K-Best Detector for MIMO Systems

Contact Info

Product

Resources

About