• Title/Summary/Keyword: MIMO networks

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Frequency Domain Channel Estimation for MIMO SC-FDMA Systems with CDM Pilots

  • Kim, Hyun-Myung;Kim, Dongsik;Kim, Tae-Kyoung;Im, Gi-Hong
    • Journal of Communications and Networks
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    • v.16 no.4
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    • pp.447-457
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    • 2014
  • In this paper, we investigate the frequency domain channel estimation for multiple-input multiple-output (MIMO) single-carrier frequency-division multiple-access (SC-FDMA) systems. In MIMO SC-FDMA, code-division multiplexed (CDM) pilots such as cyclic-shifted Zadoff-Chu sequences have been adopted for channel estimation. However, most frequency domain channel estimation schemes were developed based on frequency-division multiplexing of pilots. We first develop a channel estimation error model by using CDM pilots, and then analyze the mean-square error (MSE) of various minimum MSE (MMSE) frequency domain channel estimation techniques. We show that the cascaded one-dimensional robust MMSE (C1D-RMMSE) technique is complexity-efficient, but it suffers from performance degradation due to the channel correlation mismatch when compared to the two-dimensional MMSE (2D-MMSE) technique. To improve the performance of C1D-RMMSE, we design a robust iterative channel estimation (RITCE) with a frequency replacement (FR) algorithm. After deriving the MSE of iterative channel estimation, we optimize the FR algorithm in terms of the MSE. Then, a low-complexity adaptation method is proposed for practical MIMO SC-FDMA systems, wherein FR is performed according to the reliability of the data estimates. Simulation results show that the proposed RITCE technique effectively improves the performance of C1D-RMMSE, thus providing a better performance-complexity tradeoff than 2D-MMSE.

Systolic Arrays for Lattice-Reduction-Aided MIMO Detection

  • Wang, Ni-Chun;Biglieri, Ezio;Yao, Kung
    • Journal of Communications and Networks
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    • v.13 no.5
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    • pp.481-493
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    • 2011
  • Multiple-input multiple-output (MIMO) technology provides high data rate and enhanced quality of service for wireless communications. Since the benefits from MIMO result in a heavy computational load in detectors, the design of low-complexity suboptimum receivers is currently an active area of research. Lattice-reduction-aided detection (LRAD) has been shown to be an effective low-complexity method with near-maximum-likelihood performance. In this paper, we advocate the use of systolic array architectures for MIMO receivers, and in particular we exhibit one of them based on LRAD. The "Lenstra-Lenstra-Lov$\acute{a}$sz (LLL) lattice reduction algorithm" and the ensuing linear detections or successive spatial-interference cancellations can be located in the same array, which is considerably hardware-efficient. Since the conventional form of the LLL algorithm is not immediately suitable for parallel processing, two modified LLL algorithms are considered here for the systolic array. LLL algorithm with full-size reduction-LLL is one of the versions more suitable for parallel processing. Another variant is the all-swap lattice-reduction (ASLR) algorithm for complex-valued lattices, which processes all lattice basis vectors simultaneously within one iteration. Our novel systolic array can operate both algorithms with different external logic controls. In order to simplify the systolic array design, we replace the Lov$\acute{a}$sz condition in the definition of LLL-reduced lattice with the looser Siegel condition. Simulation results show that for LR-aided linear detections, the bit-error-rate performance is still maintained with this relaxation. Comparisons between the two algorithms in terms of bit-error-rate performance, and average field-programmable gate array processing time in the systolic array are made, which shows that ASLR is a better choice for a systolic architecture, especially for systems with a large number of antennas.

Clipping Value Estimate for Iterative Tree Search Detection

  • Zheng, Jianping;Bai, Baoming;Li, Ying
    • Journal of Communications and Networks
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    • v.12 no.5
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    • pp.475-479
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    • 2010
  • The clipping value, defined as the log-likelihood ratio (LLR) in the case wherein all the list of candidates have the same binary value, is investigated, and an effective method to estimate it is presented for iterative tree search detection. The basic principle behind the method is that the clipping value of a channel bit is equal to the LLR of the maximum probability of correct decision of the bit to the corresponding probability of erroneous decision. In conjunction with multilevel bit mappings, the clipping value can be calculated with the parameters of the number of transmit antennas, $N_t$; number of bits per constellation point, $M_c$; and variance of the channel noise, $\sigma^2$, per real dimension in the Rayleigh fading channel. Analyses and simulations show that the bit error performance of the proposed method is better than that of the conventional fixed-value method.

A study on the Adaptive Neural Controller with Chaotic Neural Networks (카오틱 신경망을 이용한 적응제어에 관한 연구)

  • Sang Hee Kim;Won Woo Park;Hee Wook Ahn
    • Journal of the Institute of Convergence Signal Processing
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    • v.4 no.3
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    • pp.41-48
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    • 2003
  • This paper presents an indirect adaptive neuro controller using modified chaotic neural networks(MCNN) for nonlinear dynamic system. A modified chaotic neural networks model is presented for simplifying the traditional chaotic neural networks and enforcing dynamic characteristics. A new Dynamic Backpropagation learning method is also developed. The proposed MCNN paradigm is applied to the system identification of a MIMO system and the indirect adaptive neuro controller. The simulation results show good performances, since the MCNN has robust adaptability to nonlinear dynamic system.

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Resource Management in 5G Mobile Networks: Survey and Challenges

  • Chien, Wei-Che;Huang, Shih-Yun;Lai, Chin-Feng;Chao, Han-Chieh
    • Journal of Information Processing Systems
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    • v.16 no.4
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    • pp.896-914
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    • 2020
  • With the rapid growth of network traffic, a large number of connected devices, and higher application services, the traditional network is facing several challenges. In addition to improving the current network architecture and hardware specifications, effective resource management means the development trend of 5G. Although many existing potential technologies have been proposed to solve the some of 5G challenges, such as multiple-input multiple-output (MIMO), software-defined networking (SDN), network functions virtualization (NFV), edge computing, millimeter-wave, etc., research studies in 5G continue to enrich its function and move toward B5G mobile networks. In this paper, focusing on the resource allocation issues of 5G core networks and radio access networks, we address the latest technological developments and discuss the current challenges for resource management in 5G.

Codebook-Based Interference Alignment for Uplink MIMO Interference Channels

  • Lee, Hyun-Ho;Park, Ki-Hong;Ko, Young-Chai;Alouini, Mohamed-Slim
    • Journal of Communications and Networks
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    • v.16 no.1
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    • pp.18-25
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    • 2014
  • In this paper, we propose a codebook-based interference alignment (IA) scheme in the constant multiple-input multiple-output (MIMO) interference channel especially for the uplink scenario. In our proposed scheme, we assume cooperation among base stations (BSs) through reliable backhaul links so that global channel knowledge is available for all BSs, which enables BS to compute he transmit precoder and inform its quantized index to the associated user via limited rate feedback link. We present an upper bound on the rate loss of the proposed scheme and derive the scaling law of the feedback load to maintain a constant rate loss relative to IA with perfect channel knowledge. Considering the impact of overhead due to training, cooperation, and feedback, we address the effective degrees of freedom (DOF) of the proposed scheme and derive the maximization of the effective DOF. From simulation results, we verify our analysis on the scaling law to preserve the multiplexing gain and confirm that the proposed scheme is more effective than the conventional IA scheme in terms of the effective DOF.

Multi-Mode Precoding Scheme Based on Interference Channel in MIMO-Based Cognitive Radio Networks

  • Jung, Minchae;Hwang, Kyuho;Choi, Sooyong
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2011.07a
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    • pp.137-140
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    • 2011
  • A precoding strategy is one of the representative interference management techniques in cognitive radio (CR) network which is a typical interference-limited environment. The interference minimization approach to precoding is an appropriate scheme to mitigate the interference efficiently while it may cause the capacity loss of the desired channel. The precoding scheme for the maximal capacity of the desired channel improves the capacity of the desired channel while it increases the interference power and finally causes the capacity loss of the interfered users. Therefore, we propose a precoding scheme which satisfies these two conflicting goals and manages the interference signal in such an interference-limited environment. The proposed scheme consists of two steps. First, the precoder nulls out the largest singular value of the interference channel to mitigate the dominant interference signal based on the interference minimization approach. Second, the transmitter calculates the sum capacities per mode and selects a mode to maximize the sum capacity. In the second step, each mode consists of the right singular vectors corresponding to the singular values except the largest singular value eliminated in the first step. Simulation results show that the proposed precoding scheme not only efficiently mitigate the interference signal, but also has the best performance in terms of the sum capacity in a MIMO-based CR network.

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Implementation-Friendly QRM-MLD Using Trellis-Structure Based on Viterbi Algorithm

  • Choi, Sang-Ho;Heo, Jun;Ko, Young-Chai
    • Journal of Communications and Networks
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    • v.11 no.1
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    • pp.20-25
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    • 2009
  • The maximum likelihood detection with QR decomposition and M-algorithm (QRM-MLD) has been presented as a suboptimum multiple-input multiple-output (MIMO) detection scheme which can provide almost the same performance as the optimum maximum likelihood (ML) MIMO detection scheme but with the reduced complexity. However, due to the lack of parallelism and the regularity in the decoding structure, the conventional QRM-MLD which uses the tree-structure still has very high complexity for the very large scale integration (VLSI) implementation. In this paper, we modify the tree-structure of conventional QRM-MLD into trellis-structure in order to obtain high operational parallelism and regularity and then apply the Viterbi algorithm to the QRM-MLD to ease the burden of the VLSI implementation.We show from our selected numerical examples that, by using the QRM-MLD with our proposed trellis-structure, we can reduce the complexity significantly compared to the tree-structure based QRM-MLD while the performance degradation of our proposed scheme is negligible.

On the Design of a WiFi Direct 802.11ac WLAN under a TGn MIMO Multipath Fading Channel

  • Khan, Gul Zameen;Gonzalez, Ruben;Park, Eun-Chan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.3
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    • pp.1373-1392
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    • 2017
  • WiFi Direct (WD) is a state of the art technology for a Device-to-Device (D2D) communication in 802.11 networks. The performance of the WD system can be significantly affected by some key factors such as the type of application, specifications of MAC and PHY layer parameters, and surrounding environment etc. It is, therefore, important to develop a system model that takes these factors into account. In this paper, we focus on investigating the design parameters of the PHY layer that could maximize the efficiency of the WD 802.11 system. For this purpose, a basic theoretical model is formulated for a WD network under a 2x2 Multiple In Multiple Out (MIMO) TGn channel B model. The design level parameters such as input symbol rate and antenna spacing, as well as the effects of the environment, are thoroughly examined in terms of path gain, spectral density, outage probability and Packet Error Rate (PER). Thereafter, a novel adaptive algorithm is proposed to choose optimal parameters in accordance with the Quality of Experience (QoE) for a targeted application. The simulation results show that the proposed method outperforms the standard method thereby achieving an optimal performance in an adaptive manner.

Performance of Convolutionally-Coded MIMO Systems with Antenna Selection

  • Hamouda Walaa;Ghrayeb Ali
    • Journal of Communications and Networks
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    • v.7 no.3
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    • pp.307-312
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    • 2005
  • In this work, we study the performance of a serial concatenated scheme comprising a convolutional code (CC) and an orthogonal space-time block code (STBC) separated by an inter-leaver. Specifically, we derive performance bounds for this concatenated scheme, clearly quantify the impact of using a CC in conjunction with a STBC, and compare that to using a STBC code only. Furthermore, we examine the impact of performing antenna selection at the receiver on the diversity order and coding gain of the system. In performing antenna selection, we adopt a selection criterion that is based on maximizing the instantaneous signal-to­noise ratio (SNR) at the receiver. That is, we select a subset of the available receive antennas that maximizes the received SNR. Two channel models are considered in this study: Fast fading and quasi-static fading. For both cases, our analyses show that substantial coding gains can be achieved, which is confirmed through Monte-Carlo simulations. We demonstrate that the spatial diversity is maintained for all cases, whereas the coding gain deteriorates by no more than $10\;log_{10}$ (M / L) dB, all relative to the full complexity multiple-input multiple-output (MIMO) system.