Beam-Domain Anti-Jamming Transmission for Downlink Massive MIMO Systems: A Stackelberg Game Perspective

Shen, Zhexian; Xu, Kui; Xia, Xiaochen

doi:10.1109/tifs.2021.3063632

Cited by 50 publications

(45 citation statements)

References 55 publications

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“…Similar phenomenon occurs when taking into account channel estimation error, although its impact is relatively minor. M affects S.E.E in a non-monotonic way as shown in equation (27), which implies the existence of optimal value of M. Theorem 1, presents a simple closedform formula that maximizes the S.E.E by finding the optimal value of M . Binary search algorithm gives the chance for determining the optimal value of M, so as to attain the maximum S.E.E.…”

Section: ) Impact Of M On See Analysismentioning

confidence: 99%

Impact of Circuit Intake Power on the Spectral Energy Efficiency of Massive MIMO With Channel Estimation Errors

Kibona

Liu

et al. 2021

IEEE Access

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The influence of circuit intake power on Spectral Energy Efficiency (S.E.E) of massive Multiple-Input-Multiple-Output (MIMO) under the existence of channel estimation errors is examined using Zero-Forcing (ZF) linear precoding scheme. The system model which includes new defined total intake power involving the transmit power of amplifiers and the circuit power intake of the analog devices is developed. To analyze the impact of circuit intake power on S.E.E, the S.E.E with and without circuit intake power is investigated and presented after formulating a closed-form expression of S.E.E that incorporates new defined power model. Our investigation reveals that, the impact of circuit intake power is very significant when Base Station (BS) is arrayed with large number of antennas. Using the new S.E.E closed-form formula, derived from our new defined power intake model, the S.E.E is evaluated when the number of BS antennas (M) rises and it is observed that, S.E.E behaves like a concave function. The same results for S.E.E are also observed when transmit power increases. We conclude that, it is easy to get maximum S.E.E using a small number of BS antennas and optimal transmit power, when circuit power intake is included in the power consumption model. When transmit power totally dominates the circuit intake power, the maximum S.E.E is obtained only when all antennas are used (meaning maximum S.E.E is obtained when the number of BS antennas becomes very large). The numerical results reveal the importance of circuit intake power on optimizing S.E.E of massive MIMO under the presence of channel estimation errors.

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Section: ) Impact Of M On See Analysismentioning

confidence: 99%

Impact of Circuit Intake Power on the Spectral Energy Efficiency of Massive MIMO With Channel Estimation Errors

Kibona

Liu

et al. 2021

IEEE Access

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“…In order to design a feasible TS for DL FDD mMIMO system, the secondorder channel statistic is exploited and an objective function based on maximizing the achievable sum rate is used instead of minimizing the MSE of DCE. The proposed TS design can be considered as a special case of beam-domain or angular-domain channel estimation [46]- [49]. This is because the second order channel statistic denoted by the channel covariance matrix is used in this paper in the design of DL training sequence.…”

Section: A Paper Contributions and Findingsmentioning

confidence: 99%

Sum Rate Maximization Versus MSE Minimization in FDD Massive MIMO Systems With Short Coherence Time

et al. 2021

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The increasing demand for higher data rates motivates the exploration of advanced techniques for future wireless networks. To this end, massive multiple-input multiple-output (mMIMO) is envisioned as the most essential technique to meet this demand. However, the expansion of the number of antennas in mMIMO systems with short coherence time makes the downlink channel estimation (DCE) overhead potentially overwhelming. As such, the number of training sequence (TS) needs to be significantly reduced. However, reducing the number of TS reduces the mean-squared error (MSE) accuracy significantly and to date it is not clear to what extend can this TS reduction affects the achievable sum rate performance. Therefore, this paper develops a low complexity and tractable TS solution for DCE and establishes an analytical framework for the optimum TS. Furthermore, the tradeoff between the achievable sum rate maximization criteria and the MSE minimization criteria is investigated. This investigation is essential to characterize the optimum TS length and the actual performance of mMIMO systems when the channel exhibits a limited coherence time. To this end, the statistical structure of mMIMO channels is exploited. In addition, this paper utilizes a random matrix theory (RMT) method to characterize the downlink achievable sum rate and MSE in a closed-form. This paper shows that maximizing the downlink sum rate criterion is more important than minimizing the MSE of the SINR only, which is typically considered in the conventional MIMO systems and/or in the time division duplex (TDD) mMIMO systems. The results demonstrate that a feasible downlink achievable sum rate can be achieved in an frequency division duplex (FDD) mMIMO system. This finding is necessary to extend the benefit of mMIMO systems to high frequency bands such as millimeter-wave (mmWave) and Terahertz (THZ) communications.INDEX TERMS Massive MIMO transmission, downlink channel estimation, achievable sum rate maximization, frequency division duplex operation mode, second order channel statistics, random matrix theory, mean square error minimization.

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“…The use of a large number of antennas results in several advantages over lower-dimensional MIMO systems, e.g., mutual orthogonality between the channel vectors of different users, mitigation of uncorrelated noise and intracell interference, and reduction in the required per user equipment (UE) transmit power [4]- [6]. Some of the recent works which studied different aspects of massive MIMO systems are [7]- [9]. Traditional MIMO systems have a separate radio-frequency (RF) chain for each antenna-element due to which these systems are also known as fully-digital (FD) MIMO systems.…”

Section: Introductionmentioning

confidence: 99%

Compensation of Transmitter IQ Imbalance in Multi-User Hybrid Beamforming Systems

2021

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In this paper, we consider the uplink (UL) communication of a massive multi-user (MU) multiple-input multiple-output (MIMO) hybrid beamforming system (HBFS) in which the transmitting userequipments are affected by IQ imbalance (IQI). We first show that if the transmitter IQI is not compensated, it will result in a finite ceiling of the UL achievable sum-rate at high signal-to-noise ratio, which only depends on the transmitter IQI matrices and is independent of the propagation channel and the choice of the hybrid combining matrices. This justifies the need for transmitter IQI compensation in massive MU-MIMO HBFS. Therefore, we propose a novel zero-forcing based transmitter IQI compensation algorithm to be implemented at the base station which effectively mitigates the undesired effects of transmitter IQI and is applicable for any channel model and any choice of the number of RF chains. For uncorrelated Rayleigh fading channel, we derive an approximate closed-form expression of the UL sum-rate achieved by the massive MU-MIMO HBFS with the proposed transmitter IQI compensation. Finally, numerical results are presented which confirm the effectiveness of the proposed transmitter IQI compensation algorithm in mitigating the undesired effects of transmitter IQI in different channel environments.INDEX TERMS Amplitude and phase mismatch, hybrid beamforming systems, IQ imbalance compensation, massive MIMO, multi-user communication, transmitter IQ imbalance.

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Beam-Domain Anti-Jamming Transmission for Downlink Massive MIMO Systems: A Stackelberg Game Perspective

Cited by 50 publications

References 55 publications

Impact of Circuit Intake Power on the Spectral Energy Efficiency of Massive MIMO With Channel Estimation Errors

Impact of Circuit Intake Power on the Spectral Energy Efficiency of Massive MIMO With Channel Estimation Errors

Sum Rate Maximization Versus MSE Minimization in FDD Massive MIMO Systems With Short Coherence Time

Compensation of Transmitter IQ Imbalance in Multi-User Hybrid Beamforming Systems

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