Pub Date : 2014-06-22DOI: 10.1109/SPAWC.2014.6941307
David Neumann, M. Joham, W. Utschick
We propose a novel channel estimation method for suppression of interference during uplink training in massive MIMO systems. The method makes use of the received uplink data to improve upon the estimation of solely training based estimators. It is based on the maximum a-posteriori criterion and outperforms state-of-the-art methods in terms of estimation accuracy and robustness. We further propose a simplified semi-blind method.
{"title":"Suppression of pilot-contamination in massive MIMO systems","authors":"David Neumann, M. Joham, W. Utschick","doi":"10.1109/SPAWC.2014.6941307","DOIUrl":"https://doi.org/10.1109/SPAWC.2014.6941307","url":null,"abstract":"We propose a novel channel estimation method for suppression of interference during uplink training in massive MIMO systems. The method makes use of the received uplink data to improve upon the estimation of solely training based estimators. It is based on the maximum a-posteriori criterion and outperforms state-of-the-art methods in terms of estimation accuracy and robustness. We further propose a simplified semi-blind method.","PeriodicalId":420837,"journal":{"name":"2014 IEEE 15th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","volume":"173 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114739189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-06-22DOI: 10.1109/SPAWC.2014.6941808
J. Bartelt, G. Fettweis
The use of soft information instead of hard bits has been widely adapted in signal processing for digital communication to improve the reliability of data transmission by techniques like turbo equalization, turbo decoding, or LDPC codes. For future mobile networks employing a centralized architecture in which the antenna and the baseband processing are separated by an additional fronthaul channel that forwards digitalized samples, we have identified another process that can be redesigned to embrace the concept of soft information: the dequantizer. A dequantizer transforms a vector of bits into amplitudes representing digitalized samples. However, if the bits were transmitted through a lossy fronthaul channel, the soft information that can be extracted from this channel's detection process is lost in a classical dequantizer. In this work, we propose a soft-input/soft-output dequantizer that passes this information through to the subsequent signal processing steps and can thereby improve the overall reliability of centralized, cloud-based mobile networks.
{"title":"A soft-input/soft-output dequantizer for cloud-based mobile networks","authors":"J. Bartelt, G. Fettweis","doi":"10.1109/SPAWC.2014.6941808","DOIUrl":"https://doi.org/10.1109/SPAWC.2014.6941808","url":null,"abstract":"The use of soft information instead of hard bits has been widely adapted in signal processing for digital communication to improve the reliability of data transmission by techniques like turbo equalization, turbo decoding, or LDPC codes. For future mobile networks employing a centralized architecture in which the antenna and the baseband processing are separated by an additional fronthaul channel that forwards digitalized samples, we have identified another process that can be redesigned to embrace the concept of soft information: the dequantizer. A dequantizer transforms a vector of bits into amplitudes representing digitalized samples. However, if the bits were transmitted through a lossy fronthaul channel, the soft information that can be extracted from this channel's detection process is lost in a classical dequantizer. In this work, we propose a soft-input/soft-output dequantizer that passes this information through to the subsequent signal processing steps and can thereby improve the overall reliability of centralized, cloud-based mobile networks.","PeriodicalId":420837,"journal":{"name":"2014 IEEE 15th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121788477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-06-22DOI: 10.1109/SPAWC.2014.6941890
G. Sridharan, Wei Yu
This paper proposes an algorithm to compute the uplink transmit beamformers for linear interference alignment in MIMO cellular networks without symbol extensions. In particular, we consider interference alignment in a network consisting of G cells and K users/cell, having N and M antennas at each base station (BS) and user respectively. Using an alternate interpretation of the conditions for interference alignment, we frame the problem of finding aligned transmit beamformers in the uplink as an optimization problem to minimize the rank of a set of interference matrices subject to affine constraints. The interference matrix of a BS consists of all the interfering vectors at that BS. The proposed algorithm approximates rank using the weighted Frobenius norm and iteratively updates the weights so that the weighted Frobenius norm is a close approximation of the rank of the interference matrix. A crucial aspect of this algorithm is the weight update rule that guides the algorithm towards aligned beamformers. We propose a novel weight update rule that discourages the algorithm from converging to local minima that do not generate the requisite number of interference free dimensions. The proposed algorithm is computationally efficient since it only requires solving a simple quadratic program in each iteration. Simulation results indicate much faster convergence to aligned beamformers when compared to algorithms of similar complexity.
{"title":"Beamformer design for interference alignment using reweighted frobenius norm minimization","authors":"G. Sridharan, Wei Yu","doi":"10.1109/SPAWC.2014.6941890","DOIUrl":"https://doi.org/10.1109/SPAWC.2014.6941890","url":null,"abstract":"This paper proposes an algorithm to compute the uplink transmit beamformers for linear interference alignment in MIMO cellular networks without symbol extensions. In particular, we consider interference alignment in a network consisting of G cells and K users/cell, having N and M antennas at each base station (BS) and user respectively. Using an alternate interpretation of the conditions for interference alignment, we frame the problem of finding aligned transmit beamformers in the uplink as an optimization problem to minimize the rank of a set of interference matrices subject to affine constraints. The interference matrix of a BS consists of all the interfering vectors at that BS. The proposed algorithm approximates rank using the weighted Frobenius norm and iteratively updates the weights so that the weighted Frobenius norm is a close approximation of the rank of the interference matrix. A crucial aspect of this algorithm is the weight update rule that guides the algorithm towards aligned beamformers. We propose a novel weight update rule that discourages the algorithm from converging to local minima that do not generate the requisite number of interference free dimensions. The proposed algorithm is computationally efficient since it only requires solving a simple quadratic program in each iteration. Simulation results indicate much faster convergence to aligned beamformers when compared to algorithms of similar complexity.","PeriodicalId":420837,"journal":{"name":"2014 IEEE 15th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","volume":"231 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115016601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-06-22DOI: 10.1109/SPAWC.2014.6941849
Daniel Romero, Roberto López-Valcarce
We present designs for compression matrices minimizing the Cramér-Rao bound for estimating the power of a stationary Gaussian process, whose second-order statistics are known up to a scaling factor, in the presence of (possibly colored) Gaussian noise. For known noise power, optimum designs can be found assuming either low or high signal-to-noise ratio (SNR). In both cases the optimal schemes sample the frequency bins with highest SNR, suggesting near-optimality for all SNR values. In the case of unknown noise power, optimal patterns in both SNR regimes sample two subsets of frequency bins with lowest and highest SNR, which also suggests that they are nearly-optimal for all SNR values.
{"title":"Nearly-optimal compression matrices for signal power estimation","authors":"Daniel Romero, Roberto López-Valcarce","doi":"10.1109/SPAWC.2014.6941849","DOIUrl":"https://doi.org/10.1109/SPAWC.2014.6941849","url":null,"abstract":"We present designs for compression matrices minimizing the Cramér-Rao bound for estimating the power of a stationary Gaussian process, whose second-order statistics are known up to a scaling factor, in the presence of (possibly colored) Gaussian noise. For known noise power, optimum designs can be found assuming either low or high signal-to-noise ratio (SNR). In both cases the optimal schemes sample the frequency bins with highest SNR, suggesting near-optimality for all SNR values. In the case of unknown noise power, optimal patterns in both SNR regimes sample two subsets of frequency bins with lowest and highest SNR, which also suggests that they are nearly-optimal for all SNR values.","PeriodicalId":420837,"journal":{"name":"2014 IEEE 15th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130311009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-06-22DOI: 10.1109/SPAWC.2014.6941514
N. N. Moghadam, H. Farhadi, P. Zetterberg, M. Skoglund
This paper presents for the first time the test-bed implementation of an iterative interference alignment and power control algorithm for downlink transmission in a multiple-input multiple-output (MIMO) cellular network. The network is composed of three cells where within each cell one base station (BS) communicates with one mobile station (MS). Each terminal is equipped with two antennas. All the BSs transmit at the same time and the same frequency band. Transmitter beamforming vectors and receiver filtering vectors are computed according to the interference alignment concept, and power control is performed to guarantee successful communication of each BS-MS pair at a desired fixed rate. The indoor measurements performed on an universal software radio peripheral (USRP) based test-bed, show that the power can be reduced by at least 4 dB, 90% of the time, while at the same time reducing the bit-error-rate (BER).
{"title":"Test-bed implementation of iterative interference alignment and power control for wireless MIMO interference networks","authors":"N. N. Moghadam, H. Farhadi, P. Zetterberg, M. Skoglund","doi":"10.1109/SPAWC.2014.6941514","DOIUrl":"https://doi.org/10.1109/SPAWC.2014.6941514","url":null,"abstract":"This paper presents for the first time the test-bed implementation of an iterative interference alignment and power control algorithm for downlink transmission in a multiple-input multiple-output (MIMO) cellular network. The network is composed of three cells where within each cell one base station (BS) communicates with one mobile station (MS). Each terminal is equipped with two antennas. All the BSs transmit at the same time and the same frequency band. Transmitter beamforming vectors and receiver filtering vectors are computed according to the interference alignment concept, and power control is performed to guarantee successful communication of each BS-MS pair at a desired fixed rate. The indoor measurements performed on an universal software radio peripheral (USRP) based test-bed, show that the power can be reduced by at least 4 dB, 90% of the time, while at the same time reducing the bit-error-rate (BER).","PeriodicalId":420837,"journal":{"name":"2014 IEEE 15th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","volume":"os-42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127781673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-06-22DOI: 10.1109/SPAWC.2014.6941524
S. Gherekhloo, A. Chaaban, A. Sezgin
This paper studies the performance gains of coordination in an elemental cellular network consisting of a multiple-access channel (MAC) and a point-to-point channel (P2P) interfering with each other. It is assumed that this network, denoted as PIMAC, is operating in the noisy (very-weak) interference regime. Three schemes, denoted as naive-TIN, TDMA-TIN, and IA-TIN, each with different coordination requirements among the transmitters (and receivers), are compared with each other in terms of achievable sum rates. It is shown that, although the PIMAC is in the noisy interference regime, allowing more coordination between the users might increase the performance, depending on the channel parameters. Consequently, this proves the sub-optimality of TDMA-TIN and naive-TIN in those regimes, which is in contrast to existing results for K-user interference and X channels. The analytical finding are verified by numerical evaluations.
{"title":"Coordination gains in the cellular uplink with noisy interference","authors":"S. Gherekhloo, A. Chaaban, A. Sezgin","doi":"10.1109/SPAWC.2014.6941524","DOIUrl":"https://doi.org/10.1109/SPAWC.2014.6941524","url":null,"abstract":"This paper studies the performance gains of coordination in an elemental cellular network consisting of a multiple-access channel (MAC) and a point-to-point channel (P2P) interfering with each other. It is assumed that this network, denoted as PIMAC, is operating in the noisy (very-weak) interference regime. Three schemes, denoted as naive-TIN, TDMA-TIN, and IA-TIN, each with different coordination requirements among the transmitters (and receivers), are compared with each other in terms of achievable sum rates. It is shown that, although the PIMAC is in the noisy interference regime, allowing more coordination between the users might increase the performance, depending on the channel parameters. Consequently, this proves the sub-optimality of TDMA-TIN and naive-TIN in those regimes, which is in contrast to existing results for K-user interference and X channels. The analytical finding are verified by numerical evaluations.","PeriodicalId":420837,"journal":{"name":"2014 IEEE 15th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121490134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-06-22DOI: 10.1109/SPAWC.2014.6941353
M. Bashar, D. Slock
The Multi-User MIMO downlink or MIMO Broadcast Channel (BC) formulation is relevant for cell center users. Whereas multiple receive antennas do not allow to increase the total number of streams (or degrees of freedom (DoF)) in the BC, they allow the sharing of zero-forcing (ZF) between transmitter and receivers so that a secondary base station (SBS) can serve its secondary users (SU) while ZF beamforming (BF) to primary users (PU). Channel State Information at the Transmitter (CSIT), which is crucial in multi-user systems, is always imperfect in practice, especially for the SBS-PU link. We consider mean and covariance Gaussian partial CSIT, and the special case of a (possibly location based) MIMO Ricean channel model. In this paper we focus on the optimization of beamformers for the secondary expected weighted sum rate (EWSR) under expected PU interference power constraints. We apply a perfect CSI technique, based on a difference of convex functions approach, to a number of deterministic approximations of the EWSR, involving the Massive MIMO limit (large number of transmit antennas), Massive MIMO with a second-order refinement, and the large MIMO limit (both large transmit and receive antenna numbers).
{"title":"Cognitive Multi-User MIMO downlink with mixed feedback/location based Gaussian CSIT","authors":"M. Bashar, D. Slock","doi":"10.1109/SPAWC.2014.6941353","DOIUrl":"https://doi.org/10.1109/SPAWC.2014.6941353","url":null,"abstract":"The Multi-User MIMO downlink or MIMO Broadcast Channel (BC) formulation is relevant for cell center users. Whereas multiple receive antennas do not allow to increase the total number of streams (or degrees of freedom (DoF)) in the BC, they allow the sharing of zero-forcing (ZF) between transmitter and receivers so that a secondary base station (SBS) can serve its secondary users (SU) while ZF beamforming (BF) to primary users (PU). Channel State Information at the Transmitter (CSIT), which is crucial in multi-user systems, is always imperfect in practice, especially for the SBS-PU link. We consider mean and covariance Gaussian partial CSIT, and the special case of a (possibly location based) MIMO Ricean channel model. In this paper we focus on the optimization of beamformers for the secondary expected weighted sum rate (EWSR) under expected PU interference power constraints. We apply a perfect CSI technique, based on a difference of convex functions approach, to a number of deterministic approximations of the EWSR, involving the Massive MIMO limit (large number of transmit antennas), Massive MIMO with a second-order refinement, and the large MIMO limit (both large transmit and receive antenna numbers).","PeriodicalId":420837,"journal":{"name":"2014 IEEE 15th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125941083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-06-22DOI: 10.1109/SPAWC.2014.6941899
S. Abdallah, S. Blostein
Rate adaptation which adjusts the transmission rate based on channel quality, plays a key role in the performance of 802.11 networks and is critical for achieving high throughput. Traditional statistics-based methods for rate adaptation are unsuited for mobility scenarios because of the delay involved in statistics gathering. Methods based on channel state information (CSI) perform better but still fall short of optimal performance in high mobility. In this paper, we consider adaptive modulation based on Slepian channel prediction as a basis for rate adaptation in high mobility scenarios. Our proposed method utilizes low-complexity projection on a subspace spanned by discrete prolate spheroidal (DPS) sequences. These sequences are simultaneously bandlimited and highly energy concentrated, and they can be used to obtain a minimum energy bandlimited extension of a finite sequence. Using the predicted channel coefficients, we select the modulation scheme resulting in the highest expected throughput. Unlike Wiener prediction, the proposed method does not require detailed knowledge of the channel correlation, but only of the Doppler bandwidth. Our numerical results show that adaptive modulation based on the low-complexity Slepian prediction is substantially better than using outdated CSI and performs very close to Wiener prediction.
速率适应可根据信道质量调整传输速率，对 802.11 网络的性能起着关键作用，是实现高吞吐量的关键。传统的基于统计的速率适应方法不适合移动场景，因为统计收集会产生延迟。基于信道状态信息（CSI）的方法性能较好，但在高移动性情况下仍无法达到最佳性能。在本文中，我们考虑将基于 Slepian 信道预测的自适应调制作为高移动性场景中速率适应的基础。我们提出的方法利用了离散球面（DPS）序列所跨子空间的低复杂度投影。这些序列同时具有带限和高能量集中的特点，可用于获得有限序列的最小能量带限扩展。利用预测的信道系数，我们可以选择预期吞吐量最高的调制方案。与维纳预测不同，所提出的方法无需详细了解信道相关性，只需了解多普勒带宽。我们的数值结果表明，基于低复杂度 Slepian 预测的自适应调制大大优于使用过时的 CSI，其性能非常接近于 Wiener 预测。
{"title":"Rate adaptation using long range channel prediction based on discrete prolate spheroidal sequences","authors":"S. Abdallah, S. Blostein","doi":"10.1109/SPAWC.2014.6941899","DOIUrl":"https://doi.org/10.1109/SPAWC.2014.6941899","url":null,"abstract":"Rate adaptation which adjusts the transmission rate based on channel quality, plays a key role in the performance of 802.11 networks and is critical for achieving high throughput. Traditional statistics-based methods for rate adaptation are unsuited for mobility scenarios because of the delay involved in statistics gathering. Methods based on channel state information (CSI) perform better but still fall short of optimal performance in high mobility. In this paper, we consider adaptive modulation based on Slepian channel prediction as a basis for rate adaptation in high mobility scenarios. Our proposed method utilizes low-complexity projection on a subspace spanned by discrete prolate spheroidal (DPS) sequences. These sequences are simultaneously bandlimited and highly energy concentrated, and they can be used to obtain a minimum energy bandlimited extension of a finite sequence. Using the predicted channel coefficients, we select the modulation scheme resulting in the highest expected throughput. Unlike Wiener prediction, the proposed method does not require detailed knowledge of the channel correlation, but only of the Doppler bandwidth. Our numerical results show that adaptive modulation based on the low-complexity Slepian prediction is substantially better than using outdated CSI and performs very close to Wiener prediction.","PeriodicalId":420837,"journal":{"name":"2014 IEEE 15th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126000206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-06-22DOI: 10.1109/SPAWC.2014.6941315
Daniel Calabuig, R. Gohary, H. Yanikomeroglu
In this paper we develop an algorithm for computing the optimal transmission parameters, which include the transmission covariance, the time-shares and the user-orderings that minimize a particular class of objectives defined over the capacity region of Gaussian multiple antenna multiple access channels. This class includes objectives that are twice-differentiable, non-increasing and convex in the users' rates, but not necessarily convex in the aforementioned transmission parameters. As such, this class includes design objectives that are non-convex and that, without the proposed algorithm, are difficult to solve in general. The proposed algorithm is iterative with polynomial complexity per iteration and with convergence to the global optimal guaranteed. The utility of this algorithm is illustrated via a numerical example for maximizing proportional fairness.
{"title":"Optimization of a class of non-convex objectives on the Gaussian MIMO multiple access channel: Algorithm development and convergence analysis","authors":"Daniel Calabuig, R. Gohary, H. Yanikomeroglu","doi":"10.1109/SPAWC.2014.6941315","DOIUrl":"https://doi.org/10.1109/SPAWC.2014.6941315","url":null,"abstract":"In this paper we develop an algorithm for computing the optimal transmission parameters, which include the transmission covariance, the time-shares and the user-orderings that minimize a particular class of objectives defined over the capacity region of Gaussian multiple antenna multiple access channels. This class includes objectives that are twice-differentiable, non-increasing and convex in the users' rates, but not necessarily convex in the aforementioned transmission parameters. As such, this class includes design objectives that are non-convex and that, without the proposed algorithm, are difficult to solve in general. The proposed algorithm is iterative with polynomial complexity per iteration and with convergence to the global optimal guaranteed. The utility of this algorithm is illustrated via a numerical example for maximizing proportional fairness.","PeriodicalId":420837,"journal":{"name":"2014 IEEE 15th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126003210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-06-22DOI: 10.1109/SPAWC.2014.6941305
Marcus Karlsson, E. Larsson
The paper considers the issue of activating inactive terminals by control signaling in the downlink in a massive MIMO system. There are two basic difficulties with this. First, the lack of CSI at the transmitter. Second, the short coherence interval, which limits the number of orthogonal pilots in the case of many antennas. The proposed scheme deals with these issues by repeating the transmission over the antennas. We show that this repetition does not affect the spectral efficiency significantly, while making it possible to estimate the channel in a standard way using MMSE. The paper also sheds some light the uplink-downlink power balance in massive MIMO.
{"title":"On the operation of massive MIMO with and without transmitter CSI","authors":"Marcus Karlsson, E. Larsson","doi":"10.1109/SPAWC.2014.6941305","DOIUrl":"https://doi.org/10.1109/SPAWC.2014.6941305","url":null,"abstract":"The paper considers the issue of activating inactive terminals by control signaling in the downlink in a massive MIMO system. There are two basic difficulties with this. First, the lack of CSI at the transmitter. Second, the short coherence interval, which limits the number of orthogonal pilots in the case of many antennas. The proposed scheme deals with these issues by repeating the transmission over the antennas. We show that this repetition does not affect the spectral efficiency significantly, while making it possible to estimate the channel in a standard way using MMSE. The paper also sheds some light the uplink-downlink power balance in massive MIMO.","PeriodicalId":420837,"journal":{"name":"2014 IEEE 15th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125125095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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