Multi-Cell Massive MIMO Systems With Hardware Impairments: Uplink-Downlink Duality and Downlink Precoding

Zarei, Shahram; Gerstacker, Wolfgang H.; Aulin, Jocelyn; Schober, Robert

doi:10.1109/twc.2017.2705709

Cited by 26 publications

(24 citation statements)

References 27 publications

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“…Implementing the LIS, on the other hand, is challenging and brings many new research questions. One potential issue is the hardware impairments (HWI) such as Tx-RF impairments [10], [11], analog imperfectness and quantization errors [12], [13], nonlinearity of the power amplifies [14], time and frequency synchronization errors [15], etc. These HWI are commonly encountered in current communication systems, but with LIS it gets more severe since the surface-area of LIS is typically large (for instances, using facades of buildings or long walls in airports as LIS).…”

Section: Introductionmentioning

confidence: 99%

Capacity Degradation with Modeling Hardware Impairment in Large Intelligent Surface

Rusek

Edfors

2018

2018 IEEE Global Communications Conference (GLOBECOM)

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In this paper, we consider capacity degradations stemming from potential hardware impairments (HWI) of newly proposed Large Intelligent Surface (LIS) systems. Without HWI, the utility of surface-area (the first-order derivative of the capacity with respect to surface-area) is shown to be proportional to the inverse of it. With HWI, the capacity as well as the utility of surface-area are both degraded, due to a higher effective noise level caused by the HWI. After first modeling the HWI in a general form, we derive the effective noise density and the decrement of utility in closed-forms. With those the impacts of increasing the surface-area can be clearly seen. One interesting but also natural outcome is that both the capacity and utility can be decreased when increasing the surface-area in the cases with severe HWI. The turning points where the capacity and the utility start to decrease with HWI can be evaluated from the derived formulas for them. Further, we also consider distributed implementations of a LIS system by splitting it into multiple small LIS-Units, where the impacts of HWI can be significantly suppressed due to a smaller surface-area of each unit.

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Section: Introductionmentioning

confidence: 99%

Capacity Degradation with Modeling Hardware Impairment in Large Intelligent Surface

Rusek

Edfors

2018

2018 IEEE Global Communications Conference (GLOBECOM)

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“…Therefore, D can remove the interference component

from the received signal

. Once D can perfectly remove the interference, the instantaneous signal-to-interference-plus-noise ratio (SINR) received by the destination under joint impact of co-channel interference and hardware impairments can be formulated as [ 44 ]

where

is variance of additive noises

which are assumed to be same at all of the receivers,

and

.…”

Section: System Modelmentioning

confidence: 99%

Rateless Codes-Based Secure Communication Employing Transmit Antenna Selection and Harvest-To-Jam under Joint Effect of Interference and Hardware Impairments

Tin

Nguyen

et al. 2019

Entropy

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In this paper, we propose a rateless codes-based communication protocol to provide security for wireless systems. In the proposed protocol, a source uses the transmit antenna selection (TAS) technique to transmit Fountain-encoded packets to a destination in presence of an eavesdropper. Moreover, a cooperative jammer node harvests energy from radio frequency (RF) signals of the source and the interference sources to generate jamming noises on the eavesdropper. The data transmission terminates as soon as the destination can receive a sufficient number of the encoded packets for decoding the original data of the source. To obtain secure communication, the destination must receive sufficient encoded packets before the eavesdropper. The combination of the TAS and harvest-to-jam techniques obtains the security and efficient energy via reducing the number of the data transmission, increasing the quality of the data channel, decreasing the quality of the eavesdropping channel, and supporting the energy for the jammer. The main contribution of this paper is to derive exact closed-form expressions of outage probability (OP), probability of successful and secure communication (SS), intercept probability (IP) and average number of time slots used by the source over Rayleigh fading channel under the joint impact of co-channel interference and hardware impairments. Then, Monte Carlo simulations are presented to verify the theoretical results.

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“…In practice, the complexity of the channel estimation should be limited such that the computing time is less than the allowed interval of coherent time, typically less than 1 ms [3,4]. To compare with the conventional training strategy, we consider the channel estimates in (5) and in (19). Note that we can ignore the scalars in these equations since the floating-point operations per second (flops) to compute them are much smaller than those to calculate the matrices.…”

Section: Complexity Analysismentioning

confidence: 99%

“…Obviously, the first four terms of Θ P-MMSE are the same as those of Θ MMSE , because the size of the matrices in (5) and (19) is the same. The first term of (31) and (32) stands for the flop counts of a matrix inverse, while the next three terms of them are the flop counts of the matrix multiplication.…”

Section: Complexity Analysismentioning

confidence: 99%

“…Recently, massive multiple-input multiple-output (MIMO) or largescale MIMO has been considered as a promising technology that is applicable to future wireless systems. Such systems have a large number of antennas at the base station (BS), possibly up to several hundreds, and can provide many advantages for wireless communication [1][2][3][4][5]. Massive MIMO is extremely robust in that it works even when one or a few of antennas fail [1,2].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Uplink training with pilot optimisation for multicell massive multiple‐input multiple‐output systems

Nguyen

et al. 2018

IET Communications

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Multi-Cell Massive MIMO Systems With Hardware Impairments: Uplink-Downlink Duality and Downlink Precoding

Cited by 26 publications

References 27 publications

Capacity Degradation with Modeling Hardware Impairment in Large Intelligent Surface

Capacity Degradation with Modeling Hardware Impairment in Large Intelligent Surface

Rateless Codes-Based Secure Communication Employing Transmit Antenna Selection and Harvest-To-Jam under Joint Effect of Interference and Hardware Impairments

Uplink training with pilot optimisation for multicell massive multiple‐input multiple‐output systems

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