Pilot distribution optimization in multi-cellular large scale MIMO systems

Marinello, José Carlos; Abrão, Taufik

doi:10.1016/j.aeue.2016.05.007

Cited by 25 publications

(25 citation statements)

References 12 publications

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“…Finally, we adapt the power control algorithm in the work of Rasti and Sharafat to the Ma‐MIMO scenario with a finite number of BS antennas and show that much more significant gains can be attained by the PA schemes when combined with an efficient power control algorithm. Different than the work of Zhu et al, which proposed a PA technique that optimizes only the UL, and than the work of Marinello and Abrão, which proposed a PA technique that optimizes only DL, our proposed PA metric is able to provide an improved performance for UL and DL at the same time. This is particularly interesting since the entire communication process occurs in practice with a single pilot distribution, and UL and DL PA metrics are conflicting, as we demonstrate in this paper.…”

Section: Introductionmentioning

confidence: 82%

“…We consider a similar system model in the works of Zhu et al and Marinello and Abrão, which is composed of L hexagonal cells, each one equipped with N antennas BS serving K single‐antenna users. Time‐division duplex (TDD) is assumed, thus reciprocity holds, and channel state information (CSI) is acquired by UL training sequences transmission.…”

Section: System Modelmentioning

confidence: 99%

“…In this section, the Ma‐MIMO system performance is improved by suitably assigning the pilot sequences to the users. () We assume a decentralized allocation procedure, in which PA is performed sequentially by each cell, regarding its covered users. The convergence of this procedure is discussed in the work of Marinello and Abrão and shown by numerical results in Zhu et al In addition, in this PA stage, it is assumed that the knowledge of the users' power distribution in the cells, and the focus is at the asymptotic performance expressions in Equation for simplicity.…”

Section: Pa Optimizationmentioning

confidence: 99%

“…() Due to this issue, it can be shown that the interference seen by each user is dependent on the pilot sequence he is using. Thus, one can improve system performance by suitably assigning the pilots to the users in the cell, as discussed in the works of Zhu et al and Marinello and Abrão . The pilot assignment (PA) problem was solved in the work of Zhu et al from the uplink (UL) perspective, and a low‐complexity near‐optimal solution was proposed.…”

Section: Introductionmentioning

confidence: 99%

“…For this sake, the pilot allocation metric of maximizing the minimum SINR is the most suitable, and our proposed scheme amalgamates such metric with the power control algorithm in the work of Rasti and Sharafat, by only knowing the power and the long‐term fading coefficients of users in adjacent cells. We first propose a low‐complexity suboptimal solution of the MaxminSINR DL PA problem in the work of in the work of Marinello and Abrão . Then, we show that the optimization under DL and UL perspectives are conflicting, since the optimal performance in both directions cannot be simultaneously achieved with any pilot configuration.…”

Section: Introductionmentioning

confidence: 99%

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Joint uplink and downlink optimization of pilot assignment for massive MIMO with power control

Marinello

Panazio

Abrão

2017

Trans Emerging Tel Tech

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In this paper, we investigate the effects of pilot assignment (PA) in multicell massive multiple‐input–multiple‐output systems. When deploying linear detection/precoding algorithms and a large number of antennas at base station (BS), it is well‐known that system performance in both uplink (UL) and downlink (DL) is mainly restricted by pilot contamination. Such interference is proper of each pilot sequence, and thus, system performance can be improved by suitably assigning the pilots to the users within a given cell, according to a certain desired metric. We show in this paper that UL and DL performances constitute conflicting metrics, since it is not possible to achieve the best performance in UL and DL concomitantly. Thus, we propose an alternative metric, namely, total capacity, aiming to simultaneously achieve a suitable performance in both directions, ie, UL and DL. Since the PA problem is combinatorial, and the search space grows with the number of pilots in a factorial fashion, we also propose a low‐complexity suboptimal algorithm that achieves promising capacity performance avoiding the exhaustive search. In addition, to fully benefit from the large excess of BS antennas, we combine our proposed PA schemes with an efficient power control algorithm, unveiling the great potential of the proposed schemes to provide improved performance for more users, even with a not‐so‐large number of BS antennas. In a limit condition, for example, our numerical results demonstrate that with 64 BS antennas serving 10 users, our proposed method can assure a 95% likely rate of 4.2 Mbps for both DL and UL, and a symmetric 95% likely rate of 1.4 Mbps when serving 32 users. If a higher number of antennas is allowed at BS, the guaranteed rates can be significantly higher.

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Section: Introductionmentioning

confidence: 82%

Section: System Modelmentioning

confidence: 99%

Section: Pa Optimizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Joint uplink and downlink optimization of pilot assignment for massive MIMO with power control

Marinello

Panazio

Abrão

2017

Trans Emerging Tel Tech

Self Cite

View full text Add to dashboard Cite

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Joint distance‐based user grouping and pilot assignment schemes for pilot decontamination in massive MIMO systems

Kalantarinejad

Abbasi‐Moghadam

2019

Int J Communication

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SummaryPilot contamination (PC) is one of the most crucial problems in massive multiple‐input multiple‐output (MIMO) systems, due to a limited source of the coherence block. In the current study, two pilot assignment schemes proposed for massive MIMO uplink transmission. We divided each cell into two groups of edge and center users under distance‐based user grouping algorithm (DUG), which the aim is finding the best user grouping boundary. The best boundary is where both signal to interference plus noise Ratio (SINR) of edge and center users is maximum, according to the user's distance to base stations (BS). We investigated the location‐aware pilot assignment (LPA) scheme to enhance the quality of services for both groups. In LPA by assuming three pilot groups for adjacent cells and determining the user's distance to BS, the planned pilots assigned to the users according to their distance to the BS. Then, we optimized pilot schedules in each group by maximizing uplink (UL) rate of each user with auction‐based optimization pilot assignment (AOPA). Simulation results show that both DUG and LPA improve the rate of edge users about 70% and the rate of center users about 30%. Joint DUG and AOPA enhance the rate of the edge and center users about 100% and 80% in each group than conventional schemes and about 50% and 10%, compared with the LPA method. Simulation results show that the proposed method is efficient in reducing PC and improving spectral efficiency.

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Efficient pilot reuse algorithms for massive MIMO cellular system

Dey

Pattanayak

Gurjar

et al. 2020

Int J Communication

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Summary Pilot contamination has come up as one of the major limitations of massive multiple‐input multiple‐output. In the recent past, the pilot contamination resulted by the pilot reuse in inter‐cell system has been successfully handled. In this paper, three efficient algorithms have been proposed to reduce the pilot contamination in intra‐cell system. These schemes emphasize on assigning the available pilots to the users based upon their channel qualities by considering the interfering degree of the various pilot sequences. The first proposed algorithm is based on water filling approach, which attains the system throughput very close to that of brute‐force exhaustive search algorithm (ESA) and performs the best among the three proposed algorithms in terms of system throughput. The second algorithm is designed for achieving better user fairness (by assigning less interfering pilots to the poor channel conditioned users). The third algorithm improves the system throughput as compared to the second algorithm without losing much in terms of user fairness. Furthermore, the computational complexity incurred by all the proposed algorithms is much less than that of ESA.

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Pilot distribution optimization in multi-cellular large scale MIMO systems

Cited by 25 publications

References 12 publications

Joint uplink and downlink optimization of pilot assignment for massive MIMO with power control

Joint uplink and downlink optimization of pilot assignment for massive MIMO with power control

Joint distance‐based user grouping and pilot assignment schemes for pilot decontamination in massive MIMO systems

Efficient pilot reuse algorithms for massive MIMO cellular system

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