Linear and successive predistortion in the frequency domain: performance evaluation in SDMA systems

Degen, Christoph; Brühl, Lars

doi:10.1109/wcnc.2005.1424596

Cited by 11 publications

(13 citation statements)

References 11 publications

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“…In the following, the mathematical fundamentals needed for the description of a MIMO system consisting of K single-antenna mobile stations and a base station with an array of M antenna elements are presented (see References [2,6]). …”

Section: Notation and System Modelmentioning

confidence: 99%

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Evaluation of MIMO systems with respect to front‐end imperfections

Degen

Koch

Keusgen

et al. 2006

Trans Emerging Tel Tech

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In multiuser multiple-input multiple-output (MIMO) systems the performance of joint detection and joint predistortion techniques highly depends on the quality of radio-frequency (RF) components. Therefore, the focus of this paper is on front-end imperfections. We demonstrate the influence of erroneous calibration (which is essential for downlink predistortion), phase noise and nonlinear amplifiers. For all issues we elaborate on the different disturbances that arise, analyse the impact on symbol estimation and evaluate system performance in terms of coded bit error ratio (BER). A general result for all examined front-end imperfections is that their influence increases with the number of spatially multiplexed data streams culminating in unacceptable performance degradation in fully loaded systems. Moreover, Wiener-based detection and predistortion reduces the degradation due to front-end imperfections in low SNR regimes compared to zero forcing

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Section: Notation and System Modelmentioning

confidence: 99%

“…Here, however, we concentrate on SC-FDE systems for examination of front-end imperfections. The signal processing used in this paper is described in more detail for the uplink in Reference [2] and for the downlink in Reference [6].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of MIMO systems with respect to front‐end imperfections

Degen

Koch

Keusgen

et al. 2006

Trans Emerging Tel Tech

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“…This effectively doubles the capacity and bits/Hz of the channel. There are numerous formulations of how to best apply SDMA to a given WLAN [41,23,35,47,1,22,34,4,7,21,25,16,26,24,19,3] but they all share a common underlying model. The idea is, given some placement of n users and some number of antenna elements at the AP, how can we assign spatial channels to each user to maximize throughput.…”

Section: Multiple Input Multiple Output (Mimo) Spatial Division Multmentioning

confidence: 99%

“…Figure 7.5 shows the example of k = 7. Therefore, we have the following schedule: { (1,4,7,10,13,16,19), (2,5,8,11,14,17,20), (3,6,9,12,15,18,21)}. Thus we use 3 time slots and in each we simultaneously have 7 links.…”

Section: Linear Array: Constructing Stdma Schedulementioning

confidence: 99%

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High Speed Wireless Networking for 60GHz

Yiu¹

2000

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This thesis examines the problem of providing high data-rate wireless connectivity to users in indoor environments. The goal is to be able to reach Gbps/user rates even when there are multiple users present. The technology that we study is to use the 60 GHz spectrum whose special propagation properties make it ideally suited to this task. The approaches developed include using multiple spatially distributed smart antennas in a room or multiple co-located antennas to provide coverage where needed and when needed. All the antennas are connected to a single access point which allows us to dynamically change spectrum and link allocation among the users (as they move or as their needs change). The innovations in this work include the exploitation of the special properties of 60 GHz and the corresponding design of algorithms for efficient spectrum allocation. We use detailed simulations to demonstrate that very high data rates are indeed achievable.

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Adaptive joint precoding and pre‐equalization with reduced complexity in massive MIMO systems

Peng

Chen

et al. 2016

Wireless Communications

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In this paper, a massive multiple input multiple output downlink scenario is considered where the number of users varies in a large dynamic range. An adaptive joint precoding and pre-equalization with reduced complexity is proposed. Specifically, the successive over-relaxation method is employed in the pre-equalization process to avoid the high-dimensional channel matrix inversion, and a reduced-length feedback filter is proposed to reduce the computational complexity of the precoding. Moreover, an adaptive transceiver structure is proposed to switch on/off the precoding process so that multiple users can be accommodated with the least cost of the computational complexity. Simulation results show that, compared with the traditional scheme, the proposed adaptive joint precoding and pre-equalization can save about 90% of the computational complexity. 6 D. Xiong et al.Reduced complexity precoding and pre-equalization in massive MIMO complexity. Specifically, we first employ the successive over-relaxation (SOR) in the FPE process so that the highdimensional channel matrix inversion can be avoided and the computational complexity can be reduced. Then, we analyze the estimation error at the receiver in terms of the mean square error (MSE). The relationship between the MSE and the feedback length in the THP process is found, based on which we propose the reduced-length feedback filter (RLFF)-based THP. Moreover, an adaptive transceiver is proposed to switch on/off the precoding process so that the multiple users can be accommodated with the least cost of the computational complexity. Monte Carlo simulations are carried out to testify the performance of the proposed method. It is shown that the proposed adaptive joint RLFF-THP and SOR-FPE can achieve a similar bit error rate (BER) performance as the traditional joint THP and FPE and save about 90% of the computational complexity.The rest of this paper is organized as follows. The system model of the massive MIMO downlink transmission is described in Section 2. The reduced complexity adaptive joint RLFF-THP and SOR-FPE is proposed in Section 3. We analyze the computational complexity of the proposed algorithm in Section 4, and the numerical results are given in Section 5. Finally, the paper is concluded in Section 6.Notations: The superscript . / T stands for the transpose operation, and . / H stands for the Hermitian operation. Re. / and Im. / denote the real part and imaginary part of a complex number, respectively. The floor function b c gives the largest integer that is smaller than or equal to the real number. trf g denotes the trace of a square matrix. vecf g represents the operation that stacks the columns of a matrix into a column vector. k k stands for the norm of a vector, and Ef g denotes the operation of expectation.

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Linear and successive predistortion in the frequency domain: performance evaluation in SDMA systems

Cited by 11 publications

References 11 publications

Evaluation of MIMO systems with respect to front‐end imperfections

Evaluation of MIMO systems with respect to front‐end imperfections

High Speed Wireless Networking for 60GHz

Adaptive joint precoding and pre‐equalization with reduced complexity in massive MIMO systems

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