Per-Stream MSE Based Linear Transceiver Design for MIMO Interference Channels With CSI Error

Zhang, Qian; He, Chen; Jiang, Lingge

doi:10.1109/tcomm.2015.2416237

Cited by 24 publications

(24 citation statements)

References 42 publications

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“…whereĥ k denotes the estimated CSI known at the BS, and e k represents the CSI uncertainty. The additive channel estimation errors can be modeled into two different forms, dependent on the duplex mode of the communication system [182]. In the time-division duplex (TDD) mode, the CSI can be directly estimated at the BS using the uplink-downlink reciprocity and is subject to estimation errors.…”

Section: G Robust CI Precodingmentioning

confidence: 99%

“…On the other hand, when the frequency-division duplex (FDD) mode is considered, the CSI error e k is usually modeled as norm bounded to characterize the quantization errors incurred by limited feedback [182]. In this case, the channel uncertainty can be considered as bounded by a spherical region V k = e k | e k 2 2 ≤ δ 2 k , and the robust precoding algorithms are usually designed based on the worst-case received SINR [183], [185]- [187].…”

Section: G Robust CI Precodingmentioning

confidence: 99%

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A Tutorial on Interference Exploitation via Symbol-Level Precoding: Overview, State-of-the-Art and Future Directions

Spano

Krivochiza

et al. 2020

IEEE Commun. Surv. Tutorials

211

127

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Interference is traditionally viewed as a performance limiting factor in wireless communication systems, which is to be minimized or mitigated. Nevertheless, a recent line of work has shown that by manipulating the interfering signals such that they add up constructively at the receiver side, known interference can be made beneficial and further improve the system performance in a variety of wireless scenarios, achieved by symbol-level precoding (SLP). This paper aims to provide a tutorial on interference exploitation techniques from the perspective of precoding design in a multi-antenna wireless communication system, by beginning with the classification of constructive interference (CI) and destructive interference (DI). The definition for CI is presented and the corresponding mathematical characterization is formulated for popular modulation types, based on which optimization-based precoding techniques are discussed. In addition, the extension of CI precoding to other application scenarios as well as for hardware efficiency is also described. Proof-of-concept testbeds are demonstrated for the potential practical implementation of CI precoding, and finally a list of open problems and practical challenges are presented to inspire and motivate further research directions in this area.

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Section: G Robust CI Precodingmentioning

confidence: 99%

Section: G Robust CI Precodingmentioning

confidence: 99%

A Tutorial on Interference Exploitation via Symbol-Level Precoding: Overview, State-of-the-Art and Future Directions

Spano

Krivochiza

et al. 2020

IEEE Commun. Surv. Tutorials

211

127

View full text Add to dashboard Cite

show abstract

“…We then proceed to investigate the imperfect CSI model and the performance of ESPAR-based MIMO system under scenarios with imperfect CSI and quantized loads. In this paper, we assume that the system is operating in TDD mode and therefore the CSIĤ is directly measured at the transmitter using uplink-downlink reciprocity and is subject to noise errors [43]. Then, the errors are modeled as inversely proportional to the transmit SNR, expressed as…”

Section: Performance Analysis -Quantized Loads Imperfect Csimentioning

confidence: 99%

MIMO Transmission for Single-Fed ESPAR With Quantized Loads

Masouros

Papadias

2017

IEEE Trans. Commun.

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Compact parasitic arrays in the form of electronically steerable parasitic antenna radiators (ESPARs) have emerged as a new antenna structure that achieves multipleinput-multiple-output (MIMO) transmission with a single RF chain. In this paper, we study the application of precoding on practical ESPARs, where the antennas are equipped with load impedances of quantized values. We analytically study the impact of the quantization on the system performance, where it is shown that while ideal ESPARs with ideal loads can achieve a similar performance to conventional MIMO, the performance of ESPARs will be degraded when only loads with quantized values are available. We further extend the performance analysis to imperfect channel state information (CSI). In order to alleviate the performance loss, we propose to approximate the ideal current vector by optimization, where a closed-form solution is further obtained. This enables the use of ESPARs in practice with quantized loads. Simulation results validate our analysis and show that a significant performance gain can be achieved with the proposed scheme over ESPARs with quantized loads. Finally, the tradeoff between performance and power consumption is shown to be favorable for the proposed ESPAR approaches compared to conventional MIMO, as evidenced by our energy efficiency results.

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“…Similar to [4] and [6], we assume that the imperfect channel state information (CSI) is modelled as the unified CSI mismatch, i.e., (5) where Hki is the observed mismatched CSI, Hki is the actuaJ channel matrix and Eki is the error matrix which is assumed to be independent of Hki. Defining the nominaJ signal-to-noise (SNR) as p = Pk/(d f7k ), then Eki is considered as a Gaussian matrix with zero mean and variance 7], i.e.,…”

Section: System Modelmentioning

confidence: 99%

“…The effect of imperfect CSI motivates [4] to investigate the performance of MIMO interference alignment (IA) subject to CSI mismatch. In [5], robust transceiver design has been considered for min-max per-stream mean square error (MSE) optimization. In [6], an adaptive beamformer design according to MMSE based IA is proposed for multiuser MIMO interfer ence channels with imperfect CSI.…”

Section: Introductionmentioning

confidence: 99%

Sum-MSE minimization for MIMO interference channels under CSI mismatch

Liu

et al. 2015

2015 Seventh International Conference on Ubiquitous and Future Networks

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This paper considers multiple-input multiple-output (MIMO) interference channels, where the robust transceiver is designed under imperfect channel state information (CSI). Our objective is to minimize the sum mean-square-error (MSE) sub ject to per-transmitter power constraints. An iterative algorithm is proposed to solve the optimization problem. The analysis shows that the optimal equalizer is equivalent to the minimum MSE (MMSE) receiver, while the optimal precoder is obtained distributively by exploiting the Lagrangian method. Simulation results verifies the effectiveness of the proposed algorithm under CSI mismatch.

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Per-Stream MSE Based Linear Transceiver Design for MIMO Interference Channels With CSI Error

Cited by 24 publications

References 42 publications

A Tutorial on Interference Exploitation via Symbol-Level Precoding: Overview, State-of-the-Art and Future Directions

A Tutorial on Interference Exploitation via Symbol-Level Precoding: Overview, State-of-the-Art and Future Directions

MIMO Transmission for Single-Fed ESPAR With Quantized Loads

Sum-MSE minimization for MIMO interference channels under CSI mismatch

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