Thesis (M.Eng.(Electronic Engineering))--University of Pretoria, 2009. / Summaries in Afrikaans and English. Includes bibliographical references.

Thesis (Ph. D.)--Oregon State University, 2006. / Printout. Includes bibliographical references (leaves 97-105). Also available on the World Wide Web.

Thesis (M.E.)--University of Canterbury, 2005. / Typescript (photocopy). Includes bibliographical references (p. [109]-116). Also available via the World Wide Web.

Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2007. / Includes bibliographical references (leaves 73-77). Also available in electronic version.

Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references.

Thesis (M.S.)--University of Texas at Dallas, 2006. / Includes vita. Includes bibliographical references (leaves73 -75 )

Massive MIMO has been recognized as a key technology for 5G systems due to its high spectral efficiency. The capacity and optimal signaling for a MIMO channel under the total power constraint (TPC) are well-known and can be obtained by the water-filling (WF) procedure. However, much less is known about optimal signaling under the per-antenna power constraint constraint (PAC) or under the joint power constraints (TPC+PAC). In this thesis, we consider a massive MIMO Gaussian channel under favorable propagation (FP) and obtain the optimal transmit covariance under the joint constraints. The effect of the joint constraints on the optimal power allocation (OPA) is shown. While it has some similarities to the standard WF, it also has number of notable differences. The numbers of active streams and active PACs are obtained, and a closed-form expression for the optimal dual variable is given. A capped water-filling interpretation of the OPA is given, which is similar to the standard WF, where a container has both floor and ceiling profiles. An iterative water-filling algorithm is proposed to find the OPA under the joint constraints, and its convergence to the OPA is proven. The robustness of optimal signaling under FP is demonstrated in which it becomes nearly optimal for a nearly favorable propagation channel. An upper bound of the sub-optimality gap is given which characterizes nearly (or eps)-favorable propagation. This upper bound quantifies how close the channel is to the FP. A bisection algorithm is developed to numerically compute the optimal dual variable. Newton-barrier and Monte-Carlo algorithms are developed to find the optimal signaling under the joint constraints for an arbitrary channel, not necessarily for a favorable propagation channel. When the diagonal entries of the channel Gram matrix are fixed, it is shown that a favorable propagation channel is not necessarily the best among all possible propagation scenarios capacity-wise. We further show that the main theorems in [1] on favorable propagation are not correct in general. To make their conclusions valid, some modifications as well as additional assumptions are needed, which are given here.

Approved for public release; distribution unlimited / This thesis investigates the fundamentals of Multiple-Input-Multiple-Output (MIMO) radio communication systems with space-time codes. A MIMO system was design using the Alamouti space-time code. The modulation technique was binary phase-shift keying (BPSK). Matlab with Simulink was used to simulate the design, which was tested in both an additive white Gaussian noise (AWGN) channel and in a multipath fading channel with AWGN. Theoretical performance was derived for both channels and compared to simulated results. The original receiver design was changed to incorporate a maximal-ratio combiner (MRC) receiving technique with channel state information (CSI). The theoretical performance for this design was determined and compared to simulated and published results. / Lieutenant Commander, Canadian Navy

A research report submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Engineering. Johannesburg, 2016 / Multiple-Input Multiple-Output (MIMO) radar is a more general form of phased array radar, where each antenna in the array transmits linearly independent or mutually orthogonal signals. Sustained growth in computational power as well as the decline in the cost of integrated radio frequency (RF) components has made MIMO more viable than in the past. The potential emergence of practical MIMO radar has prompted an investigation into the detectability of MIMO radar signals using existing conventional Electronic warfare Support (ES) receivers such as the Crystal Video Receiver (CVR) and a specific type of superheterodyne receiver (superhet) known as the Zero IF Receiver (ZIFR). Literature on the detectability of MIMO radar signals is extremely scarce and this investigation aims to offer insights into the detectability of MIMO radar signals by means of computer simulations. The fundamental theory necessary for this research includes phased array radar theory, MIMO array radar theory and ES receiver signal detection theory. The detection of MIMO radar signals is compared to a reference phased array case to provide relative context. This investigation focusses on co-located Uniform Linear Arrays (ULA) based radar systems. The result of interest is the relative Signal-to-Noise Ratio (SNR) at which each type of radar can be detected by the ES receiver. Therefore, a lossless transmission, without loss of generality, is assumed. Constraints such as the equal transmit power over all antenna elements in the arrays, are used for a fair comparison. Many different array simulation setups are simulated. These setups are achieved by varying the number of elements in the array and the inter-element spacing. The phased array radar transmitted complex linear chirp signals, and the MIMO radar transmitted Hadamard sequences, interpolated using a Constant Envelope Linear-Route-of-Unity (CE-LRU) technique. The CVR and ZIFR detection thresholds were determined for a Probability of False Alarm (PFA) of 10-4. For all of the setups, the phased array radar was found to be more detectable than the MIMO radar at values of Probability of Detection (PD) below 0.6. The in phase coherent combination of phased array radar signals in its main beam resulted in a signal gain caused by the constructive addition of the signals. This gain thus increases with the number of antenna elements. In contrast, the MIMO signals also add coherently, but the instantaneous phase for each signal is a function of the transmitted signal as well as the direction of propagation relative to the array face. The set of orthogonal signals thus add constructively and destructively, resulting in the average signal power remaining approximately constant despite the number of antenna elements increasing. The difference in detectability of the phased array radar over MIMO radar therefore increases as the number of antenna elements is increased, due to the fact that each element is constrained to transmit a fixed power. Comparing the performance of the ZIFR and CVR, the ZIFR outperforms the CVR. This is due to the fact that the ZIFR implements a quadrature ES receiver, and was able to detect both types of radar signals at a lower SNR than the CVR. However, both ES receivers struggle to detect MIMO radar signals in comparison to detecting phased array radar signals and this performance margin widens as the number of transmitting elements is increased. This result suggests that research into dedicated techniques for the detection of MIMO radar signals using ES receivers may be necessary should the need arise to detect MIMO radar signals in future. This is the first quantitative analysis of the detectability of MIMO radar signals using conventional ES receivers that the author is aware of. / MT2017

认知无线电在处理频谱稀缺的问题上是一个非常有前途的解决方案。拥有多天线认知无线电的用戶通过发射波束成形技术可以和授权用在同一时刻同一频带共存，这样大大地增强了频谱效率。在实际系统中，最理想的情况是这些拥有多天线认知无线电用戶能够分布式地优化他们的发射波束形成向量以此达到系统的最优化。由于授权用戶受到的干扰是来自于所有认知无线电用戶的，为了实现分布式算法这些干扰必须被合理地规划以至于达到最优。也就是说，每个认知无线电用戶需要知道对授权用戶产生干扰的最佳约束上限。 / 从优化的角度处理这种解耦问题，最常用的方法是原始分解法和对偶分解法。然而这两种方法都需要用戶之间有大量的消息传递，这对于频谱效率来说是有害的。在对偶分解法中，指向授权用戶的耦合干扰被一协调者估测(通常是授权用戶本身)。协调者需要在每次迭代中更新和广播参数给认知无线电用戶。对于原始分解法，算法同样需要一协调者进行收集认知无线电用戶的目标函数信息以此计算每个用戶的最优干扰约束上限。协调者同样需要更新和广播大量消息给认知无线电用戶。这种大量的信息计算和传递在分布式系统中是不理想的，问题在认知无线电网络显得格外严重。因为授权用戶不希望担任这样的协调者除非他的计算参与降到最低。 / 在此论文中，我们提出了几种新型的基于认知无线电网络的分布式算法。目的是最小化授权用戶和认知无线电用戶的消息传递。通过研究半定规划中的最优分割法，我们指出不影响最优性条件下授权用戶和认知无线电用戶的大量消息传递是可以避免的。我们又提出了在多输入多数出认知无线电网络中一种基于对偶分解的鲁捧干扰控制。在此论文中提出的低消息传递算法大大地提高了多用戶多输入多数认知无线电网络的实用性。 / Cognitive radio (CR) is a promising solution to alleviate spectrum scarcity. In CR networks where mobile stations are equipped with multiple antennas, secondary users (SUs) can transmit at the same time as the primary users (PUs) by carefully controlling the interference through transmit beamforming, thus significantly enhancing the spectrum efficiency. In practical systems, it is desirable to have multiple SUs optimize their transmit beamforming vectors in a decentralized manner, and yet achieve an optimal system performance. In CR networks, the interference received by the PU is attributed to the transmission of all SUs. To facilitate distributed beamforming, the aggregate-interference constraint imposed by the PU must be decoupled, so that each individual SU knows the "fair share" of interference that is allowed to generate to the PU. / A commonly used technique for decoupling coupled constraintsin optimization problems is optimization decomposition, including dual and primal decompositions. Both the dual and primal decomposition methods require frequent message passing among users, which potentially offsets the spectrum benefit brought by cognitive radio techniques. Specifically, with dual decomposition, the aggregate interference generated to the PU must be measured by a coordinator,which is, naturally, the PU. The coordinator then updates and broadcasts the Lagrangian multiplier to all SUs. Likewise, the primal decomposition needs a coordinator, which can again be the PU, to gather the subgradient of the objective functions of each SUs for given interference partition. The coordinator then updates and broadcasts the permissible interference to all SUs. Whereas the large overhead incurred message computation and passing is undesirable in distributed systems, the problem is more acute in CR networks, because a typical PU would not be willing to take the coordinating role unless its involvement is minimized. / In this thesis, we propose several novel distributed optimization algorithms for CR networks with minimum message passing between the primary and secondary systems. By exploiting the theory of optimal partition (OP) for semi-definite programming (SDP), we show that most message passings between the primary and secondary systems can be eliminated without compromising the optimality of the solution. We also derive a robust interference control scheme based on the duality theory for MIMO CR network. The low message-passing distributed algorithms presented in this thesis greatly enhance the practicality of multiuser MIMO CR networks. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Yao, Leiyi. / Thesis (Ph.D.) Chinese University of Hong Kong, 2014. / Includes bibliographical references (leaves 114-123). / Abstracts also in Chinese.