Realistic beamforming design using SRS-based channel estimate for ns-3 5G-LENA module

Wireless mesh networks (WMNs) can provide flexible wireless connections in a smart city, internet of things (IoT), and device-to-device (D2D) communications. The performance of WMNs can be greatly enhanced by adopting a multi-radio technique, which enables a node to communicate with more nodes simultaneously. However, multi-radio WMNs face two main challenges, namely, energy consumption and physical layer secrecy. In this paper, both simultaneous wireless information and power transfer (SWIPT) and cooperative jamming technologies were adopted to overcome these two problems. We designed the SWIPT and cooperative jamming scheme, minimizing the total transmission power by properly selecting beamforming vectors of the WMN nodes and jammer to satisfy the individual signal-to-interference-plus-noise ratio (SINR) and energy harvesting (EH) constrains. Especially, we considered the channel estimate error caused by the imperfect channel state information. The SINR of eavesdropper (Eve) was suppressed to protect the secrecy of WMN nodes. Due to the fractional form, the problem was proved to be non-convex. We developed a tractable algorithm by transforming it into a convex one, utilizing semi-definite programming (SDP) relaxation and S-procedure methods. The simulation results validated the effectiveness of the proposed algorithm compared with the non-robust design.

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An Adaptive Multiple LS Channel Estimation Method for MIMO System

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.239-240.1084 ◽

2012 ◽

Vol 239-240 ◽

pp. 1084-1088

Author(s):

Jin Lun Chen

Keyword(s):

Numerical Simulation ◽

Channel Estimation ◽

Communication Systems ◽

Mimo System ◽

Estimation Method ◽

Linear Least Squares ◽

Mimo Communication ◽

Channel Estimate ◽

Wide Range ◽

Multiple Input

Accurate channel estimation plays a key role in multiple-input and multiple-output (MIMO) communication systems. In this paper, we firstly discuss the popular linear least squares (LS) channel estimation and the multiple LS (MLS) channel estimation. Then an adaptive multiple LS (AMLS) channel estimate approach is proposed. Using numerical simulation, it is found that the proposed estimation method outperforms LS and MLS for a wide range of training SNRs.

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Joint Channel Estimation and Data Detection for STBC MIMO-OFDM Wireless Communication System

Journal of Circuits System and Computers ◽

10.1142/s0218126615500590 ◽

2015 ◽

Vol 24 (04) ◽

pp. 1550059 ◽

Cited By ~ 2

Author(s):

Gajanan R. Patil ◽

Vishwanath K. Kokate

Keyword(s):

Channel Estimation ◽

Orthogonal Frequency Division Multiplexing ◽

Multiple Input Multiple Output ◽

Data Detection ◽

Channel Estimate ◽

Multiple Input ◽

Input Multiple Output ◽

Mimo Ofdm ◽

The Cost ◽

Joint Channel

This paper presents a joint channel estimation and data detection technique for multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Initial estimate of the channel is obtained using semi-blind channel estimation (SBCE). The whitening rotation (WR)-based orthogonal pilot maximum likelihood (OPML) method is used to obtain the channel estimate. The estimate is further enhanced by extracting information through the received data symbols. The performance of the proposed estimator is studied under various channel models. The simulation study shows that this approach gives better performance over training-based channel estimation (TBCE) and OPML SBCE methods but at the cost of higher computational complexity.

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MIMO IBC beamforming with combined channel estimate and covariance CSIT

2017 IEEE International Symposium on Information Theory (ISIT) ◽

10.1109/isit.2017.8006495 ◽

2017 ◽

Cited By ~ 3

Author(s):

Wassim Tabikh ◽

Dirk Slock ◽

Yi Yuan-Wu

Keyword(s):

Channel Estimate ◽

Combined Channel

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Smoothing techniques for decision-directed MIMO OFDM channel estimation

Advances in Radio Science ◽

10.5194/ars-9-139-2011 ◽

2011 ◽

Vol 9 ◽

pp. 139-143

Author(s):

P. Beinschob ◽

U. Zölzer

Keyword(s):

Channel Estimation ◽

Bit Error Rate ◽

Error Rate ◽

Error Propagation ◽

Orthogonal Frequency Division Multiplexing ◽

Mimo Systems ◽

Smoothing Techniques ◽

Time Frequency ◽

Channel Estimate ◽

Mimo Ofdm

Abstract. With the purpose of supplying the demand of faster and more reliable communication, multiple-input multiple-output (MIMO) systems in conjunction with Orthogonal Frequency Division Multiplexing (OFDM) are subject of extensive research. Successful Decoding requires an accurate channel estimate at the receiver, which is gained either by evaluation of reference symbols which requires designated resources in the transmit signal or decision-directed approaches. The latter offers a convenient way to maximize bandwidth efficiency, but it suffers from error propagation due to the dependency between the decoding of the current data symbol and the calculation of the next channel estimate. In our contribution we consider linear smoothing techniques to mitigate error propagation by the introduction of backward dependencies in the decision-based channel estimation. Designed as a post-processing step, frame repeat requests can be lowered by applying this technique if the data is insensitive to latency. The problem of high memory requirements of FIR smoothing in the context of MIMO-OFDM is addressed with an recursive approach that acquires minimal resources with virtual no performance loss. Channel estimate normalized mean square error and bit error rate (BER) performance evaluations are presented. For reference, a median filtering technique is presented that operates on the MIMO time-frequency grids of channel coefficients to reduce the peak-like outliers produced by wrong decisions due to unsuccessful decoding. Performance in terms of Bit Error Rate is compared to the proposed smoothing techniques.

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