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See detailLocation-aware and Superimposed-Pilot based Channel Estimation of Sparse HAP Radio Communication Channels
Nawaz, Sayed Junaid; Mansoor, Babar; Sharma, Shree Krishna UL et al

in Proc. IEEE VTC-Spring 2017 (2017, November 16)

A superimposed (arithmetically added) Pilot (SiP) sequence based channel estimation method for beamforming assisted multi-antenna High Altitude Platform (HAP) land mobile radio communication systems is ... [more ▼]

A superimposed (arithmetically added) Pilot (SiP) sequence based channel estimation method for beamforming assisted multi-antenna High Altitude Platform (HAP) land mobile radio communication systems is proposed, which exploits the prior available information of users' spatial location, density of users, and beam-width of HAP directional antenna. A thorough characterization of HAP sparse multipath radio propagation channels' is presented in first part of the paper, where mathematical relationship of HAP antenna beam-width with channel's delay span and optimal length of SiP base sequence are presented. Further, a location information aided and low- power SiP sequence based Stage-wise Orthogonal Match Pursuit (StOMP) algorithm is proposed for estimation of channels from single-antenna user terminals to beamforming assisted large scale multiple-antenna HAP. A thorough analysis on the basis of Normalized Channel Mean Square Error (NCMSE) and Bit Error Rate (BER) performance of proposed method is presented; where the effect of channels' sparsity level, Pilot-to-Information power Ratio (PIR), beam-width of HAP's directional antenna, amount of HAP antenna elements, density of interfering users, and spatial location of active user terminal are thoroughly studied. A comparison of the proposed method with a notable reference technique available in the literature is also presented. [less ▲]

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See detailSuperimposed Training based Estimation of Sparse MIMO Channels for Emerging Wireless Networks
Mansoor, Babar; Nawaz, Syed Junaid; Amin, Bilal et al

in Proceedings of ICT 2016 (2016, May)

Multiple-input multiple-output (MIMO) systems constitute an important part of todays wireless communication standards and these systems are expected to take a fundamental role in both the access and ... [more ▼]

Multiple-input multiple-output (MIMO) systems constitute an important part of todays wireless communication standards and these systems are expected to take a fundamental role in both the access and backhaul sides of the emerging wireless cellular networks. Recently, reported measurement campaigns have established that various outdoor radio propagation environments exhibit sparsely structured channel impulse response (CIR). We propose a novel superimposed training (SiT) based up-link channels’ estimation technique for multipath sparse MIMO communication channels using a matching pursuit (MP) algorithm; the proposed technique is herein named as superimposed matching pursuit (SI-MP). Subsequently, we evaluate the performance of the proposed technique in terms of mean-square error (MSE) and bit-error-rate (BER), and provide its comparison with that of the notable first order statistics based superimposed least squares (SI-LS) estimation. It is established that the proposed SI-MP provides an improvement of about 2dB in the MSE at signal-to-noise ratio (SNR) of 12dB as compared to SI-LS, for channel sparsity level of 21.5%. For BER = 10^−2, the proposed SI-MP compared to SI-LS offers a gain of about 3dB in the SNR. Moreover, our results demonstrate that an increase in the channel sparsity further enhances the performance gain [less ▲]

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