The communications industry is experiencing an explosion in the demand for personal communications services (PCS). Several digital technologies have been proposed to replace overburdened analog systems. One system that has gained increasing popularity in North America is a 1.25 MHz Code Division Multiple Access (CDMA) system (IS-95). In CDMA systems, multiple access interference limits the capacity of any system using conventional single user correlation or matched filter receivers. Previous research has shown that multiuser detection receivers that employ interference cancellation techniques can significantly improve the capacity of a CDMA system. This thesis studies two such structures: the successive interference cancellation scheme and the parallel interference cancellation scheme. These multiuser receivers are integrated into an IS-95 compatible receiver model which is simulated in software. This thesis develops simulation software that simulates IS-95 with conventional and multiuser receivers in multipath channels and when near-far conditions exist. Simulation results present the robustness of multiuser receivers to near-far in a practical system. In addition to multiuser implemenations, quantization effects from finite bit analog to digital converters (ADC) in CDMA systems will also be simulated. / Master of Science

No description available.

In a multiuser system, several signals are transmitted simultaneously within the same frequency band. This can result in significant improvements both in spectral efficiency and system capacity. However, a detrimental effect of the shared transmissions (both in time and bandwidth), is that the signal received at the base station (BS) or access point (AP) suffers from cochannel interference (CCI) and inter-symbol interference (ISI). This situation presents challenges to receiver design. To combat the destructive nature of multipath fading, a receiver often employs multiple antennas to collect the faded superimposed versions of the transmitted signals. The multiple signals are combined and processed in such a way that the effects of CCI and ISI are minimized and the desired information is reliably recovered. The situation is even more challenging when the system is operating under overload, i.e. when there are fewer receive antennas than there are transmitted signals. Multiuser detection (MUD) is used to simultaneously estimate the information sent by the transmitters. To do this, the receiver exploits differences among the cochannel signals (through unique spatial signatures in this case). We consider a cochannel communication system where multiple transmitted signals arrive at a receiver (equipped with multiple receive antennas) after propagating through a Rayleigh fading channel. It is assumed that the receiver is operating in an overloaded scenario. For such systems, an optimum maximum a posterior probability (MAP) detector estimates the transmitted signal by maximizing the probability of correct decision. The MAP detector reduces to the maximum likelihood (ML) detector when all the transmitted signals are equiprobable. The computational complexity of both MAP and ML detectors increases exponentially with the number of transmitted signals and the channel memory. For large systems suffering severe CCI and ISI, this is clearly not a good choice for real-time implementation due to the associated computational expenses. The main factors that influence the complexity of MAP / ML detection are: (i) the number of transmitted signals (or equivalently the number of users sharing the system resources), (ii) modulation alphabet size, and (iii) length of the channel memory. On the other hand, linear detection approaches fail to offer acceptable performance while other nonlinear sub-optimum approaches incur high computational costs for reasonably improved system performance and exhibit an irreducible error-floor at medium to high signal to noise ratio (SNR) values. We develop receiver signal processing techniques for the frequency-flat fading channel (where all the multipaths of the transmitted signal arrive at the receiver within a symbol period). We develop an ant colony optimization (ACO) assisted soft iterative detection approach for binary phase-shift keying (BPSK) modulated signals which employs a simplified MAP criteria to extract the most probable signals from the search space. The structure of the receiver is such that it can continue operating under overloaded conditions. The technique achieves near maximum likelihood (ML) performance in critically loaded cases using much lower complexity. For the challenging case of overload it still offers performance close to ML at low to moderate SNR values. Second, an integrated framework comprising of ACO metaheuristic and a recursively defined ML search criteria is developed to handle multilevel modulations. The proposed receiver is capable of achieving near-ML performance for the considered system with significant savings in computational complexity. The receiver framework is independent of the system loading condition, and therefore it remains suitable for overloaded scenarios. Due to the branch and bound nature of the algorithm, an exact expression for the complexity cannot be determined. Instead, an upper bound on computational complexity is developed.

This thesis investigates two systems that exploit multi-user interference in wireless communication in which multiple users transmit simultaneously. The thesis consists of two parts that aim for two different wireless network setups: the first part focuses on the decoding of convolutional-coded physical-layer network coding (PNC) in a two-way relay network (TWRN); the second part presents a scalable multi-user multiple-input multiple-output (MU-MIMO) architecture supporting real-time MIMO decoding. Both systems take advantage of multi-user interference to boost the system performance. The investigations of the two systems involve both theoretical analysis and system prototyping on software radio. / The first part of this thesis investigates the decoding process of asynchronous convolutional-coded PNC systems. Specifically, we put forth a layered decoding framework for convolutional-coded PNC consisting of three layers: symbol realignment layer, codeword realignment layer, and joint channel-decoding network coding (Jt-CNC) decoding layer. Our framework can deal with phase asynchrony (phase offset) and symbol arrival-time asynchrony (symbol misalignment) between the signals simultaneously transmitted by multiple sources. A salient feature of this framework is that it can handle both fractional and integral symbol misalignments. For the decoding layer, instead of Jt-CNC, previously proposed PNC decoding algorithms (e.g., XOR-CD and reduced-state Viterbi algorithms) can also be used with our framework to deal with general symbol misalignments. Our Jt-CNC algorithm based on belief propagation (BP) is BER-optimal for synchronous PNC and near optimal for asynchronous PNC. Extending beyond convolutional codes, we further generalize the Jt-CNC decoding algorithm for all cyclic codes. Our simulations show that Jt-CNC outperforms the previously proposed XOR-CD algorithm and reduced-state Viterbi algorithm by 2 dB for synchronous PNC. For both phase-asynchronous and symbolasynchronous PNC, Jt-CNC performs better than the other two algorithms. Importantly, for real wireless network experimentation, we implemented our decoding algorithm in a PNC prototype built on the USRP software radio platform. Our experiment shows that the proposed Jt-CNC decoder works well in practice. / The second part of the thesis presents BigStation, a scalable architecture that enables real-time signal processing in large-scale MU-MIMO systems with tens or hundreds of antennas. Our strategy to scale the system is to extensively parallelize the MU-MIMO processing on many simple and low-cost commodity computing devices. Our design can incrementally support more antennas by proportionally adding more computing devices. To reduce the overall processing latency, which is a critical constraint for wireless communication, we parallelize the MU-MIMO decoding process with a distributed pipeline based on its computation and communication patterns. At each stage of the pipeline, we further use data partitioning and computation partitioning to speed up the signal processing. As a proof of concept, we have built a BigStation prototype based on commodity PC servers and SORA software radio platform. Our prototype employs 15 PC servers and can support realtime signal processing of 12 software radio antennas. Our results show that the BigStation is able to scale to tens to hundreds of antennas. With 12 antennas, our BigStation prototype can increase wireless throughput by 6.8 x with a low mean latency of 860μs. While this latency is not yet low enough for the 802.11 MAC, it already satisfies the real-time requirements of many existing wireless standards such as LTE and WCDMA. / 本論文探討了兩種可以利用多個無線用戶同時傳輸時所造成的多用戶干擾的無線通信系統。本文由旨在針對不同的無線網絡結構的兩部分構成：第一部分論述了雙向中繼網絡（TWRN）中卷積編碼的非同步物理層網絡編碼（PNC）的解碼; 第二部分介紹了一種支持實時解碼的可擴展的多用戶多輸入多輸出（MU-MIMO）架構。這兩種系統都利用了無線通信中的多用戶干擾以提高系統性能。在對這兩個系統的探討中，我們都進行了理論分析，並搭建了基於軟件無線電的原型系統。 / 論文的第一部分研究卷積編碼的非同步物理層網絡編碼系統的解碼過程。具體來說，我們提出了一種非同步物理層網絡編碼的分層解碼架構。該架構由三層組成：符號對齊層，碼字對齊層，以及聯合信道解碼網絡編碼（Jt-CNC）解碼層。我們的這種架構能夠處理由多個用戶同時發送信號時造成的相位不同步（相位偏移）和符號到達時間不同步（符號偏移）。這種架構的一個顯著特點是，它可以同時處理分數和整數的符號偏移。對於解碼層，除了Jt-CNC算法，先前提出的各種PNC解碼算法（例如，XOR-CD 和減少狀態的Viterbi算法）也可以應用於我們的解碼架構用來解決符號偏移問題。我們基於置信度傳播理論（BP）的Jt-CNC算法，對於同步PNC是比特差錯率（BER）最優的，對於非同步PNC是接近最優的。除了卷積碼以外，我們進一步將Jt-CNC解碼算法推廣到了所有循環碼。我們的仿真表明，對於同步PNC，Jt-CNC的性能超過先前提出的XOR-CD算法和減少狀態Viterbi算法2 dB。對於相位非同步和符號非同步PNC，Jt-CNC均優於前述兩種算法。重要的是，為了進行真實環境下的無線網絡實驗，我們在基於USRP軟件無線電平台的PNC原型系統上實現了我們的解碼算法。我們的實驗顯示，該Jt-CNC解碼器在真實環境下中表現優越。 / 論文的第二部分介紹了BigStation，一個可擴展的MU-MIMO系統架構。該架構支持帶有幾十甚至上百根天線的大規模MU-MIMO系統的實時信號處理。我們的系統擴展策略是將MU-MIMO信號處理並行化到大量簡單廉價的商用計算單元上。我們的這種設計可以通過成比例地增加計算單元以支持更多的天線。為了減少系統的整體處理延遲，我們根據MU-MIMO信號處理的計算和通信模式，利用分布式流水線把解碼過程並行化。在流水線的各級，我們進一步使用數據分割和計算分割來加速信號處理。作為概念驗證，我們基於商用個人電腦和SORA軟件無線電平台開發了BigStation原型系統。我們的原型使用了15 台個人電腦並且可以支持12 根軟件無線電天線的實時解碼。我們的實驗結果表明，BigStation系統能夠擴展到幾十甚至幾百根天線。當有12 根天線時，我們的BigStation原型系統將無線網絡吞吐量提高了6.8 倍，而平均延遲則低至860 μs。雖然這個延遲對於802.11 的MAC 還不足夠低，但它已滿足了許多現有的無線標准諸如LTE和WCDMA的實時性要求。 / Yang, Qing. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2015. / Includes bibliographical references (leaves 101-108). / Abstracts also in Chinese. / Title from PDF title page (viewed on 21, December, 2016). / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only.

We consider the uplink of a multicell multiuser single-input multiple-output system where the channel experiences both small and large-scale fading. The data detection is done by using the linear zero-forcing technique, assuming the base station (BS) has perfect channel state information of all users in its cell. We derive  new, exact analytical expressions for the uplink rate, symbol error rate, and outage probability per user, as well as alower bound on the achievable rate. This bound is very tight and becomes exact in the large-number-of-antennas limit. We further study the asymptotic system performance in the regimes of high signal-to-noise ratio (SNR), large number of antennas, and large number of users per cell. We show that at high SNRs, the system is interference-limited and hence, we cannot improve the system performance by increasing the transmit power of each user. Instead, by increasing the number of BS antennas, the effects of interference and noise can be reduced, thereby improving the system performance. We demonstrate that, with very large antenna arrays at the BS, the transmit power of each user can be made inversely proportional to the number of BS antennas while maintaining a desired quality-of-service. Numerical results are presented to verify our analysis.

In direct-sequence code division multiple access (DS-CDMA) systems, the heuristic optimization algorithms for multiuser detection include genetic algorithms (GA) and simulated annealing (SA) algorithm. In this thesis, we use particle swarm optimization (PSO) algorithms to solve the optimization problem of multiuser detection (MUD). PSO algorithm has several advantages, such as fast convergence, low computational complexity, and good performance in searching optimum solution. In order to enhance the performance and reduce the number of parameters, we propose two modified PSO algorithms, inertia weighting controlled PSO (W-PSO) and reduced-parameter PSO (R-PSO). From simulation results, the performance of our proposed algorithms can achieve that of optimal solution. Furthermore, our proposed algorithms have faster convergence performance and lower complexity when compared with other conventional algorithms.

In this thesis, we consider the uplink of a cooperative code division multiple access (CDMA) network, where users cooperate by relaying each other¡¦s messages to the base station. The sources adopt CDMA to share the informations offered by relays. In general, spreading waveforms of sources are not orthogonal to each others due to pratical design issues of CDMA network. Therefore, the source signals will suffer from multiple access interference (MAI) at the relays and destination. The MAI results in the increase of bit error rate increased, and diminishes the cooperative network diveristy gains. In order to mitigate MAI, the decorrelating multiuser detection and zero-forcing precoder have been commonly adopted. But, the decorrelating multiuser detection causes noise enhancement, while the zero-forcing precoder causes power expansion. In this thesis, we adopt relay-assisted decorrelating multiuser detector (RAD-MUD) to mitigate MAI as proposed in [1].In this scheme, the relays perform half of decorrelating operation and the destination performs the other half. In this way, neither noise enhancement nor power expansion will occur. However, in the reference [1], the authers assume the transmission is synchronous between sources and relays. The assumption is unrealistic, because it is difficult to achieve synchronization between all sources and relays due to various propagation delays. In this thesis, we extend the research in [1] and relax restriction of synchronization between all sources and relays. Besides, we also adopt cooperative strategies such as transmit beamforming or selective relaying to enhance system performance. Compared with other¡¦s multiuser detection schemes, we show that the proposed schemes can effectively reduce the bit error rate.

With perfect channel state information at all the transmission terminals, the asymptotic capacity of multi-hop multiple-input multiple-output(MIMO) amplify-andforward(AF) relay channels is derived. Although the derivation is based on the assumption of a large number of antennas, simulation results show that the derived expression is surprisingly accurate for even a small number of antennas, and may even be superior to existing results. In addition, based on the asymptotic result, we present different power allocation schemes to (i) minimization the transmit power; (ii) maximization the network throughput; (iii) minimization the transmit power over all source. Fortunately, the proposed power allocation problems can be formulated using geometric programming(GP). Therefore, the optimal power distribution among the multi-hop relay can be obtained efficiently. For multiuser scenarios, since it is possible that the QoS of each user cannot be satisfied simultaneously, we study jointly admission control and power allocation optimization problem. This joint problem is NP-hard. Therefor, we propose an iterative algorithm to reduced the complexity.

In this dissertation, adaptive power control for single and multiuser opportunistic systems is investigated. First, a new adaptive power-controlled diversity combining scheme for single user systems is proposed, upon which is extended to the multiusers case. In the multiuser case, we first propose two new threshold based parallel multiuser scheduling schemes without power control. The first scheme is named on-off based scheduling (OOBS) scheme and the second scheme is named switched based scheduling (SBS) scheme. We then propose and study the performance of thresholdbased power allocation algorithms for the SBS scheme. Finally, we introduce a unified analytical framework to determine the joint statistics of partial sums of ordered RVs with i.i.d. and then the impact of interference on the performance of parallel multiuser scheduling is investigated based on our unified analytical framework.

Frequency reuse scheme is used to enhance the spectral efficiency in a cellular system, but inevitably the system suffers from co-channel interference of other users. Signal-to-interference ratio (SIR) is often used as a quality index of communication links. Several wireless communication algorithms, such as channel assignment, handover and power control, need real-time SIR information. All of these algorithms are under the assumptions that real-time SIR is available, but the methods of obtaining real-time SIR are seldom mentioned with these algorithms. In this thesis, we investigate three simple SIR estimation methods including statistics of spreading chips method, decorrelation detection method, and orthogonal stochastic approximation method. The performance of these SIR estimation methods are evaluated by computer simulations in a WCDMA system.