Mitigating Pilot Contamination by Pilot Reuse and Power Control Schemes for Massive MIMO Systems

Saxena, Vidit; Fodor, Gábor; Karipidis, Eleftherios

doi:10.1109/vtcspring.2015.7145932

Cited by 81 publications

(61 citation statements)

References 10 publications

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“…Currently, pilot contamination reduction schemes in massive MIMO systems can be classified into three groups: channel estimation [6][7][8][9][10][11], precoding [12], and pilot scheduling [13][14][15][16][17][18][19][20]. In [6], pilot contamination was tackled by a multi-cell precoding method based on the minimum mean square error channel estimation.…”

Section: Introductionmentioning

confidence: 99%

“…Unfortunately, this method needs a control mechanism to make sure the pilot sequences are synchronous in adjacent cells; thus, it becomes inefficient or even inapplicable when the number of antennas at the BS grows large. In [16], the authors developed techniques based on existing long-term evolution measurementsopen loop power control and pilot sequence reuse schemes, that avoid pilot contamination within a group of cell. While in [17], a power control problem to minimize D2D links' data transmit power is formulated and an iterative scheme is adopted to solve the problem.…”

Section: Introductionmentioning

confidence: 99%

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Pilot contamination reduction in massive MIMO systems based on pilot scheduling

Liu

Cao

et al. 2018

J Wireless Com Network

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The pilot contamination caused by sharing the non-orthogonal pilots among users is considered to be a bottleneck of the massive multi-input multi-output (MIMO) systems. This paper proposes a pilot scheduling scheme based on the degradation to address this problem. Through computing the degradation of the users, the proposed scheduling assigns the optimal pilot sequence to the user who suffers from the greatest degradation in a greedy way. Moreover, the proposed scheme is further optimized with an extra set of orthogonal pilot sequences, which is called pilot scheduling scheme based on user grouping. Simulation results show that the target cell's achievable sum rate of the proposed scheme is much higher than the random pilot scheduling (RPS) and the smart pilot assignment (SPA) schemes; also, our scheme can reduce the impact of shadowing fading on the target cell's achievable sum rate effectively.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Pilot contamination reduction in massive MIMO systems based on pilot scheduling

Liu

Cao

et al. 2018

J Wireless Com Network

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“…In [23], a binary search PPA algorithm was provided to maximize the achievable downlink sum rate with matched filter based precoding in single cell massive MIMO. A pilot power control scheme was provided in [24], which can improve the channel estimation performance. Moreover, in [25], as the number of antennas increased, simulation results show that more power should be allocated for pilot transmission to improve the channel estimation performance.…”

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confidence: 99%

Pilot Power Allocation Through User Grouping in Multi-Cell Massive MIMO Systems

Liu

Jin

Jiang

et al. 2017

IEEE Trans. Commun.

108

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Abstract-In this paper, we propose a relative channel estimation error (RCEE) metric, and derive closed-form expressions for its expectation Exp rcee and the achievable uplink rate holding for any number of base station antennas M , with the least squares (LS) and minimum mean squared error (MMSE) estimation methods. It is found that RCEE and Exp rcee converge to the same constant value when M → ∞, which renders the pilot power allocation (PPA) substantially simplified and a PPA algorithm is proposed to minimize the average Exp rcee per user with a total pilot power budget P in multi-cell massive multiple-input multiple-output systems. Numerical results show that the PPA algorithm brings considerable gains for the LS estimation compared with equal PPA (EPPA), while the gains are significant only with large frequency reuse factor (FRF) for the MMSE estimation. Moreover, for large FRF and large P , the performance of the LS approaches to the MMSE. Besides, a scheduling strategy is proposed to allocate pilot power whole system, which can approach the optimal performance. For the achievable uplink rate, the PPA scheme delivers almost the same average achievable uplink rate and improves the minimum achievable uplink rate compared with the EPPA scheme.Index Terms-Massive multiple-input multiple-output (MI-MO), pilot power allocation, relative channel estimation error, achievable uplink rate.

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“…One such example is [9], which aims to exploit the spatial orthogonality between different users and proposes a greedy pilot assignment algorithm, which minimizes the sum of estimation errors in multipath channels by assigning the same pilot sequence to UTs with non-overlapping angle spread. Later results in [16], [17] suggest that this method achieves the same performance as a simple random pilot assignment. Partial pilot reuse is proposed in [11], [12], assigning nonorthogonal pilots only to cell-centered UTs, while UTs located at the edge of the cell are assigned orthogonal ones.…”

Section: Introductionmentioning

confidence: 93%

“…One approach for treating (16), is to approximate the fullydigital solution (17) with an analog one. It was shown in [31] that minimizing the approximation gap between the analog combiner W and the fully-digital combiner W FD minimizes an upper bound on the MSE (16).…”

Section: B Magiq -Minimal Gap Iterative Quantizationmentioning

confidence: 99%

Pilot contamination mitigation with reduced RF chains

Ioushua

Eldar

2017

2017 IEEE 18th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

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Abstract-Massive multiple-input multiple-output (MIMO) communication is a promising technology for increasing spectral efficiency in wireless networks. Two of the main challenges massive MIMO systems face are degraded channel estimation accuracy due to pilot contamination and increase in computational load and hardware complexity due to the massive amount of antennas. In this paper, we focus on the problem of channel estimation in massive MIMO systems, while addressing these two challenges: We jointly design the pilot sequences to mitigate the effect of pilot contamination and propose an analog combiner which maps the high number of sensors to a low number of RF chains, thus reducing the computational and hardware cost. We consider a statistical model in which the channel covariance obeys a Kronecker structure. In particular, we treat two such cases, corresponding to fully-and partially-separable correlations. We prove that with these models, the analog combiner design can be done independently of the pilot sequences. Given the resulting combiner, we derive a closed-form expression for the optimal pilot sequences in the fully-separable case and suggest a greedy sum of ratio traces maximization (GSRTM) method for designing sub-optimal pilots in the partially-separable scenario. We demonstrate via simulations that our pilot design framework achieves lower mean squared error than the common pilot allocation framework previously considered for pilot contamination mitigation.

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Mitigating Pilot Contamination by Pilot Reuse and Power Control Schemes for Massive MIMO Systems

Cited by 81 publications

References 10 publications

Pilot contamination reduction in massive MIMO systems based on pilot scheduling

Pilot contamination reduction in massive MIMO systems based on pilot scheduling

Pilot Power Allocation Through User Grouping in Multi-Cell Massive MIMO Systems

Pilot contamination mitigation with reduced RF chains

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