The problem of designing scheduling algorithm for multi-channel (e.g., OFDM-based) wireless downlink networks is considered, where the system has a large bandwidth and proportionally large number of users to serve. For this system, while the classical MaxWeight algorithm is known to be throughput-optimal, its buffer-overflow performance is very poor (formally, it is shown that it has zero rate function in our setting). To address this, a class of algorithms called iHLQF (iterated Heaviest matching with Longest Queues First) is proposed. The algorithms in this class are shown to be throughput-optimal for a general class of arrival/channel processes, and also rate-function optimal (i.e., exponentially small buffer overflow probability) for certain arrival/channel processes, where the channel-rates are 0 or 1 packets per timeslot. iHLQF however has higher computational complexity than MaxWeight (n⁴ vs. n² computations per timeslot respectively). To overcome this issue, a new algorithm called SSG (Server-Side Greedy) is proposed. It is shown that SSG is throughput-optimal, results in a much better per-user buffer overflow performance than the MaxWeight algorithm (positive rate function for certain arrival/channel processes), and has a computational complexity (n²) that is comparable to the MaxWeight algorithm. Thus, it provides a nice trade-off between buffer-overflow performance and computational complexity. For multi-rate channel processes, where the channels can serve multiple packets per timeslot, new Markov chain-based coupling arguments are used to derive rate-function positivity results for the SSG algorithm. Finally, an algorithm called DMEQ is proposed and shown to be rate-function optimal for certain multi-rate channel scenarios, whose definition characterizes the sufficient conditions for rate-function optimality in this regime. These results are validated by both analysis and simulations. / text

The evolved version of LTE is LTE-Advanced which is being developed by 3GPP. LTE-Advanced will meet or go beyond the requirements of the International Telecommunication Union (ITU) for the fourth generation (4G) radio communication standard known as IMT-Advanced. LTEAdvanced is primarily considered as a part of Release 10 of 3GPP specifications. The LTE-Advanced specifications will continue to be developed in subsequent 3GPP releases. The complete physical layer structure has been employed by using the latest 3GPP standards. Furthermore, technologies such as Orthogonal Frequency Division Multiplexing (OFDM) and Multiple Input Multiple Output (MIMO) have also been implemented and integrated with LTEAdvanced. The Multiple Access Scheme in Advanced Mobile radio system has to meet the specific requirements such as: high throughput, robustness, efficient Bit Error Rate (BER), high spectral efficiency, minimum delays, low computational complexity, low Peak to Average Power Ratio (PAPR), low error probability etc. In order to investigate the LTE-Advanced transceiver a thorough study has been carried out using MATLAB Simulink using AWGN and Rayleigh fading channel. This report investigates the performance of OFDMA and various MIMO configurations of LTEAdvanced physical layer, along with diverse modulation techniques such 16QAM and QPSK,the results are then demonstrated on BER and signal to noise ratio graphs. AWGN and Rayleigh fading models are also used to determine the performance of LTE-Advanced in presence of noise and fading.

Abstract Advanced multiple-input multiple-output (MIMO) transceiver structures which utilize the knowledge of channel state information (CSI) at the transmitter side to optimize certain link parameters (e.g., throughput, fairness, spectral efficiency, etc.) under different constraints (e.g., maximum transmitted power, minimum quality of services (QoS), etc.) are considered in this thesis. Adaptive transmission schemes for point-to-point MIMO systems are considered first. A robust link adaptation method for time-division duplex systems employing MIMO-OFDM channel eigenmode based transmission is developed. A low complexity bit and power loading algorithm which requires low signaling overhead is proposed. Two algorithms for computing the sum-capacity of MIMO downlink channels with full CSI knowledge are derived. The first one is based on the iterative waterfilling method. The convergence of the algorithm is proved analytically and the computer simulations show that the algorithm converges faster than the earlier variants of sum power constrained iterative waterfilling algorithms. The second algorithm is based on the dual decomposition method. By tracking the instantaneous error in the inner loop, a faster version is developed. The problem of linear transceiver design in MIMO downlink channels is considered for a case when the full CSI of scheduled users only is available at the transmitter. General methods for joint power control and linear transmit and receive beamformers design are provided. The proposed algorithms can handle multiple antennas at the base station and at the mobile terminals with an arbitrary number of data streams per scheduled user. The optimization criteria are fairly general and include sum power minimization under the minimum signal-to-interference-plus-noise ratio (SINR) constraint per data stream, the balancing of SINR values among data streams, minimum SINR maximization, weighted sum-rate maximization, and weighted sum mean square error minimization. Besides the traditional sum power constraint on the transmit beamformers, multiple sum power constraints can be imposed on arbitrary subsets of the transmit antennas.This extends the applicability of the results to novel system architectures, such as cooperative base station transmission using distributed MIMO antennas. By imposing per antenna power constraints, issues related to the linearity of the power amplifiers can be handled as well. The original linear transceiver design problems are decomposed as a series of remarkably simpler optimization problems which can be efficiently solved by using standard convex optimization techniques. The advantage of this approach is that it can be easily extended to accommodate various supplementary constraints such as upper and/or lower bounds for the SINR values and guaranteed QoS for different subsets of users. The ability to handle transceiver optimization problems where a network-centric objective (e.g., aggregate throughput or transmitted power) is optimized subject to user-centric constraints (e.g., minimum QoS requirements) is an important feature which must be supported by future broadband communication systems.

The diploma thesis deals with the design of the LTE radio part using the ICS Designer program. First, the work describes the signal processing in the physical layer LTE system, for downlink and uplink. Subsequently, it was made simple block diagram. The next part deals with models of signal propagation in the radio environment. The last part is an introduction to the ICS Designer. This section describes the base station design and demonstration of some simulations. The last part is devoted to the design of the mobile network in the given area, its simulation and subsequent comparison with the existing mobile network.

Today many societies rely on fast mobile networks, and the future seem to place even larger demand on the networks performance. This thesis analyzes which parameters affects the downlink speed of mobile networks. Various statistical analyses are performed on a large dataset provided by Bredbandskollen. We find that parameters such as the internet service provider, the type of phone, the time of day and the density of population affect the downlink speed. We also find that the downlink speeds are significantly higher in urban areas compared to more rural regions.

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第18532号 / 情博第536号 / 新制||情||95(附属図書館) / 31418 / 京都大学大学院情報学研究科通信情報システム専攻 / (主査)准教授 村田 英一, 教授 守倉 正博, 教授 梅野 健 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DGAM

This thesis focuses on the design of linear precoding schemes for downlink multiple-input multiple-output (MIMO) networks. These schemes are designed to be amenable to implementation in wireless networks that allow rate-limited feedback of channel state information (CSI). In the first half of this thesis, memoryless quantization codebooks are designed and incremental vector quantization techniques are developed for the representation of CSI in MIMO point-to-point links and isolated (single-cell) downlink networks. The second half of the thesis seeks to design linear precoding schemes for the multi-cell downlink networks that can achieve improved performance without requiring significantly more communication resources for CSI feedback than those required in the case of an isolated single-cell. For the quantization problem, smooth optimization algorithms are developed for the design of codebooks that possess attractive features that facilitate their implementation in practice in the addition to having good quantization properties. As one example, the proposed approach is used to design rank-2 codebooks that have a nested structure and elements from a phase-shift keying (PSK) alphabet. The designed codebooks have larger minimum distances than some existing codebooks, and provide tangible performance gains. To take advantage of temporal correlation that may exist in the wireless channel, an incremental approach to the Grassmannian quantization problem is proposed. This approach leverages existing codebooks for memoryless quantization schemes and employs a quantized form of geodesic interpolation. Two schemes that implement the principles of the proposed approach are presented. A distinguishing feature of the proposed approach is that the direction of the geodesic interpolation is specified implicitly using a point in a conventional codebook. As a result, the approach has an inherent ability to recover autonomously from errors in the feedback path. In addition to the development of the Grassmannian quantization techniques and codebooks, this thesis studies linear precoder design for the downlink MIMO networks in the cases of small networks of arbitrary topology and unbounded networks that have typical architectures. In particular, a linear precoding scheme for the isolated 2-cell network that achieves the optimal spatial degrees of freedom of the network is proposed. The implementation of a limited feedback model for the proposed linear precoding scheme is developed as well. Based on insight from that model, other linear precoding schemes that can be implemented in larger networks, but with finite size, are developed. For unbounded networks of typical architecture, such as the hexagonal arrangement of cells, linear precoding schemes that exploit the partial connectivity of the network are presented under a class of precoding schemes that is referred to as spatial reuse precoding. These precoding schemes provide substantial gains in the achievable rates of users in the network, and require only local feedback. / Thesis / Doctor of Philosophy (PhD)

This dissertation designs linear transceivers for the multiuser downlink in multiple-input multiple-output (MIMO) systems. The designs rely on an uplink/downlink duality for the mean squared error (MSE) of each individual data stream. We first consider the design of transceivers assuming channel state information (CSI) at the transmitter. We consider minimization of the sum-MSE over all users subject to a sum power constraint on each transmission. Using MSE duality, we solve a computationally simpler convex problem in a virtual uplink. The transformation back to the downlink is simplified by our demonstrating the equality of the optimal power allocations in the uplink and downlink. Our second set of designs maximize the sum throughput for all users. We establish a series of relationships linking MSE to the signal-to-interference-plus-noise ratios of individual data streams and the information theoretic channel capacity under linear minimum MSE decoding. We show that minimizing the product of MSE matrix determinants is equivalent to sum-rate maximization, but we demonstrate that this problem does not admit a computationally efficient solution. We simplify the problem by minimizing the product of mean squared errors (PMSE) and propose an iterative algorithm based on alternating optimization with near-optimal performance. The remainder of the thesis considers the more practical case of imperfections in CSI. First, we consider the impact of delay and limited-rate feedback. We propose a system which employs Kalman prediction to mitigate delay; feedback rate is limited by employing adaptive delta modulation. Next, we consider the robust design of the sum-MSE and PMSE minimizing precoders with delay-free but imperfect estimates of the CSI. We extend the MSE duality to the case of imperfect CSI, and consider a new optimization problem which jointly optimizes the energy allocations for training and data stages along with the sum-MSE/PMSE minimizing transceivers. We prove the separability of these two problems when all users have equal estimation error variances, and propose several techniques to address the more challenging case of unequal estimation errors.

This dissertation designs linear transceivers for the multiuser downlink in multiple-input multiple-output (MIMO) systems. The designs rely on an uplink/downlink duality for the mean squared error (MSE) of each individual data stream. We first consider the design of transceivers assuming channel state information (CSI) at the transmitter. We consider minimization of the sum-MSE over all users subject to a sum power constraint on each transmission. Using MSE duality, we solve a computationally simpler convex problem in a virtual uplink. The transformation back to the downlink is simplified by our demonstrating the equality of the optimal power allocations in the uplink and downlink. Our second set of designs maximize the sum throughput for all users. We establish a series of relationships linking MSE to the signal-to-interference-plus-noise ratios of individual data streams and the information theoretic channel capacity under linear minimum MSE decoding. We show that minimizing the product of MSE matrix determinants is equivalent to sum-rate maximization, but we demonstrate that this problem does not admit a computationally efficient solution. We simplify the problem by minimizing the product of mean squared errors (PMSE) and propose an iterative algorithm based on alternating optimization with near-optimal performance. The remainder of the thesis considers the more practical case of imperfections in CSI. First, we consider the impact of delay and limited-rate feedback. We propose a system which employs Kalman prediction to mitigate delay; feedback rate is limited by employing adaptive delta modulation. Next, we consider the robust design of the sum-MSE and PMSE minimizing precoders with delay-free but imperfect estimates of the CSI. We extend the MSE duality to the case of imperfect CSI, and consider a new optimization problem which jointly optimizes the energy allocations for training and data stages along with the sum-MSE/PMSE minimizing transceivers. We prove the separability of these two problems when all users have equal estimation error variances, and propose several techniques to address the more challenging case of unequal estimation errors.

Master of Science / Department of Electrical and Computer Engineering / Balasubramaniam Natarajan / In recent years, orthogonal frequency division multiplexing (OFDM) scheme has received significant research interest due to its capability of supporting high data rates in hostile environments. As compared to conventional single-carrier modulation schemes, OFDM benefits from low complexity equalization filters and high spectral efficiency. A multiple access implementation of OFDM, i.e., orthogonal frequency division multiple access (OFDMA) has been considered as the multiple access (MA) scheme in 3GPP LTE, or LTE advanced downlink. In cellular OFDMA, frequency hopping (FH) is widely used to exploit frequency diversity gain and improve system throughput; and pilot patterns that have low-cross correlation are employed to improve the quality of channel estimation. However, there are numerous unsolved problems that need to be addressed in frequency hopped and pilot assisted OFDMA systems. Surveying the prior works in the literature, we find that limited research efforts have focused on coping with the inherent disadvantages regarding OFDM in cellular OFDMA systems. In this thesis, we employ the so-called residue number system (RNS) arithmetic concentrating on (a) FH pattern design for minimizing/averaging intra/inter-cell interference, (b) pilot pattern design for improving the quality of channel estimation, and (c) pilot pattern design for facilitating time-frequency synchronization and device identification in multi-cell OFDMA. Regarding (a), RNS-based FH patterns not only preserve orthogonality within the same cell, but also have the minimum number of symbol collisions among adjacent cells. Additionally, the RNS-based method exhibits consistent system performance and more frequency diversity gains as compared to previous efforts. With respect to (b), RNS-based pilot pattern design generates more unique pilot patterns than conventional methods. This results in low probability of pilot-to-pilot collisions, which in turn, significantly improves the quality of channel estimation from the system level perspective. For (c), as a special case of linear congruence sequences, RNS-based pilot patterns have good auto-correlation properties, which are extremely helpful in time-frequency synchronization and device identification.