Optimal training for Time-Division Duplexed systems with transmit beamforming

Muharar, Rusdha; Evans, Jamie

doi:10.1109/ausctw.2011.5728755

Cited by 5 publications

(9 citation statements)

References 10 publications

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“…Training optimization problems for base stations equipped with linear receivers and/or precoders have been addressed in several works, e.g., [8], [16]- [19] for single-cell massive MIMO systems and in [20] for multi-cell massive MIMO networks. In [16], [17], the authors study the optimal training period and the optimal power allocation for the training and uplink data transmission that maximize the uplink sum rate with matched filter (MF) and zero-forcing (ZF) receivers.…”

Section: Introductionmentioning

confidence: 99%

“…A similar scenario to [17] has been investigated previously in [19] but the authors consider both weighted sum rate and weighted minimum rate as the objective functions. Similar optimization problems with a more complex linear receiver, i.e., minimum mean square error (MMSE) receiver, have been considered in [8], [18]. In [8], by ignoring the large-scale fading components, the expression for the signal to interference plus noise ratio (SINR) or the corresponding sum-rate was obtained by performing the analysis in the large system regime where the number of antennas and the number of single antennas users go to infinity with a fixed ratio (also called as cell-loading).…”

Section: Introductionmentioning

confidence: 99%

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Optimal Power Allocation and Training Duration for Uplink Multiuser Massive MIMO Systems With MMSE Receivers

Muharar

2020

IEEE Access

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This paper investigates the optimal training duration and the optimal power allocation for the training and the data transmission that maximize the ergodic sum rate in single-cell uplink massive MIMO with MMSE receivers. Our channel model assumes that each user experiences the same spatial channel correlation. The expression for the ergodic sum rate is obtained in the large system regime where the number of antennas (N) at the base station and the number of users (K) tend to infinity with a fixed ratio. Interestingly, we show that the optimal training duration is equal to K and independent of the spatial correlation. We also derive the optimal power allocation that in facts depends on the spatial correlation, the channel coherence interval, and the uplink SNR. We show that more energy should be allocated for the training if the data transmission duration (t d) is less than K , and vice versa. Moreover, equal power allocation is optimal when t d = K. We also obtain an approximation for the optimal power allocation that depends on the mean of the correlation matrix eigenvalues. Numerical simulations show that our results based on the large system approximation are accurate and applicable for finite-size systems. The simulations also show that (1) the resulting ergodic sum rates obtained by employing the optimal power allocation and its approximation are indistinguishable, and (2) the optimal power allocation obtained from the uncorrelated channel model can be applied to the cases involving the correlated channels with indiscernible penalties on the ergodic sum rates.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Power Allocation and Training Duration for Uplink Multiuser Massive MIMO Systems With MMSE Receivers

Muharar

2020

IEEE Access

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“…In the following lemma, we show that (17) has the intuitively obvious solution mentioned above: the BS transmits to the m groups that have the largest path gains. This will reduce the number of candidate mode/group combinations for (18) to L. Under G , let us choosep G =p S and ρ G = ρ S for the power allocation and ρ, respectively. Even though those choices are not optimal in maximizing R (m),∞ sum (G ), they satisfy the constraint in (16).…”

Section: A Binary Group Loadingmentioning

confidence: 99%

“…The analysis in this paper assumes perfect CSI at the BS even though this is hard to obtain in practical scenarios. The impact of imperfect CSI at the BS with RCI precoder has been investigated in some work, e.g., [18], [19] and [20]. The optimization problems considered in this paper together with imperfect CSI can be a subject for future investigation.…”

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Optimal Power Allocation and User Loading for Multiuser MISO Channels with Regularized Channel Inversion

Muharar

Zakhour

Evans

2013

IEEE Trans. Commun.

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We consider a multiuser system where a single transmitter equipped with multiple antennas (the base station) communicates with multiple users each with a single antenna. Regularized channel inversion is employed as the precoding strategy at the base station. Within this scenario we are interested in the problems of power allocation and user admission control so as to maximize the system throughput, i.e., which users should we communicate with and what power should we use for each of the admitted users so as to get the highest sum rate. This is in general a very difficult problem but we do two things to allow some progress to be made. Firstly we consider the large system regime where the number of antennas at the base station is large along with the number of users. Secondly we cluster the downlink path gains of users into a finite number of groups. By doing this we are able to show that the optimal power allocation under an average transmit power constraint follows the well-known water filling scheme. We also investigate the user admission problem which reduces in the large system regime to optimization of the user loading in the system. Index Terms-Multiuser precoding, regularized channel inversion, power allocation, large system analysis.

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“…2 mengindikasikan bahwa strategi yang optimal adalah mendapatkan durasi transmisi data downlink yang maksimum walaupun kualitas CSI yang didapatkan tidak terlalu bagus. Strategi ini juga telah dibuktikan optimal pada kasus transmisi data uplink dengan penerima MMSE untuk komunikasi MIMO pengguna jamak sel tunggal[19]. Pembuktian nilai optimal secara teoretis untuk skenario pada makalah ini merupakan pekerjaan lanjutan yang penting untuk dikaji.Gbr.…”

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Analisis Kinerja MIMO Masif dengan Teknik Precoding Maximum Ratio Transmission

Muharar¹

2019

Jurnal Nasional Teknik Elektro dan Teknologi Informasi

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Channel State Information (CSI) at the base stations obtained via the uplink training is an important factor in cellular and multiuser Multi-Input Multi-Output (MIMO) communication networks. In massive MIMO cellular networks with pilotbased training, the most adopted approach is to employ the same set of orthogonal training symbols in each cell. This is called the full-pilot reuse (FPR) scheme. In this paper, we consider the lesscommon but a more practical approach where each cell uses different sets of orthogonal training symbols and call this scheme as the Different Orthogonal Pilot (DOP) sequences. In particular, we focus on the downlink performance of massive MIMO networks with the Maximum Ratio Transmission (MRT) precoder at the base stations. The analysis is performed in the large system regime where the number of antennas at each base station and the number of users at each cell tend to infinity with a fixed ratio. We obtain a new expression for the Signal to Interference plus Noise Ratio (SINR) in that regime, called the limiting SINR. Numerical simulations show that it can approximate the finite-size systems accurately. Furthermore, the simulations also indicate that the DOP scheme can give a better SINR and a higher user capacity compared to those of the FPR scheme. Intisari-Informasi keadaan kanal atau Channel State Information (CSI) pada Base Station (BS) yang diperoleh saat pelatihan dalam transmisi uplink merupakan faktor penting dalam komunikasi pada jaringan seluler pengguna jamak (multiuser) Multi-Input Multi-Output (MIMO). Pada jaringan seluler MIMO dengan jumlah antena masif (massive MIMO) dan pelatihan berbasis pengiriman simbol pilot, pendekatan yang paling sering diadopsi adalah dengan menggunakan deretan simbol latih ortogonal yang sama untuk setiap sel. Pendekatan ini dinamakan dengan Full-Pilot Reuse (FPR). Pada makalah ini dikaji pendekatan yang jarang digunakan tetapi lebih praktis, yaitu setiap sel menggunakan deretan simbol latih ortogonal yang berbeda dan disebut sebagai skema Different Orthogonal Pilot sequences (DOP). Kajian pada makalah ini berfokus pada transmisi downlink dengan teknik precoding Maximum Ratio Transmission (MRT) pada BS. Analisis kinerja dilakukan pada dimensi tak-hingga (large system regime). Pada dimensi ini, jumlah antena dan jumlah pengguna di setiap sel menuju tak hingga dengan rasio yang tetap. Analisis pada dimensi ini menghasilkan persamaan baru untuk SINR, yang disebut dengan limiting SINR. Hasil simulasi numerik menunjukkan bahwa limiting SINR merupakan perkiraan atau pendekatan (approximation) yang akurat untuk SINR pada dimensi berhingga. Selain itu, hasil simulasi juga mengindikasikan bahwa skema DOP dapat menghasilkan SINR dan kapasitas pengguna yang lebih besar dibandingkan dengan skema FPR.

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Optimal training for Time-Division Duplexed systems with transmit beamforming

Cited by 5 publications

References 10 publications

Optimal Power Allocation and Training Duration for Uplink Multiuser Massive MIMO Systems With MMSE Receivers

Optimal Power Allocation and Training Duration for Uplink Multiuser Massive MIMO Systems With MMSE Receivers

Optimal Power Allocation and User Loading for Multiuser MISO Channels with Regularized Channel Inversion

Analisis Kinerja MIMO Masif dengan Teknik Precoding Maximum Ratio Transmission

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