Scheduling has always been an indispensable part of resource allocation in wireless networks. Accurate information about channel-state is assumed as a modeling simplification. However, in a real-life network ,e.g., Long Term Evolution(LTE) or IEEE 802.16e WiMAX, the channel-state information feedback to the transmitter can have uncertainty. The primary reason being that although resource allocation is done at the finer granularity of a Physical Resource Block (PRB), channel-state information is still feedback at the coarser granularity of a sub band, which is a group of PRBs. This is done to reduce the feedback traffic from the users to the Base Station. However, this averaging causes information loss and hence, the resulting uncertainty at the scheduler. Moreover, uncertainty might be present in the channel-estimates because of the very process of estimation. In the first part of the thesis, we model the channel-estimate in accuracy and characterize the network stability region. Compared to earlier works, we allow the channel estimates to have dependence among themselves, which is a more realistic situation in a modern LTE or WiMax network. We then propose two simple Max Weight based scheduling schemes that achieve any rate in the interior of the stability region. We also derive an asymptotically tight upper bound on the mean queueing delay in our system under one of the throughput-optimal policies we propose. The above policies ensure stability of the network and we have also obtained bounds on the mean queueing delays. However, different applications may require certain quality of service which may not be satisfied by these policies. Thus, we also propose a throughput-optimal policy for the network under traffic with heterogeneous QoS constraints and present some numerical results studying its performance. In the second part of the thesis, we study the problem of energy-efficient scheduling under average delay constraint. For wireless access technologies, the largest power consumer is the Base Station(BS). Any reduction in the power consumption in a BS will reduce carbon footprint from the Information and Communication Technology sector. We concentrate on the problem of minimizing the total non-renewable power consumed in a Green BS, that is powered by renewable energy sources ,e.g., solar/wind energy and may also be connected to the power grid or diesel generators. Specifically, we consider the problem of minimizing the average grid power consumption of a Green BS downlink in scheduling multiple users with average delay constraints. We have a packetized model for the data packets (i.e., the packets cannot be fragmented) which is a more realistic model for packet-switched networks. The power function is a non-decreasing convex function of the queue-lengths and only one user is allowed to transmit in a slot. We prove the existence of a power optimal policy under delay constraints for multiple users. We analyse the problem and provide some structural results for the optimal policy.

To explore spectral opportunities in wideband regime for cognitive radio we need a wideband spectrum sensing receiver. Current wideband receiver architectures need wideband analog to digital converter (ADC) to sample wideband signal. As current state-of-art ADC has limitation in terms of power and sampling rate, we need to explore some alternative solutions. Compressive sampling (CS) data acquisition method is one of the solutions. Cognitive Radio signal, which is sparse in frequency domain can be sampled at Sub-Nyquist rate using low rate ADC. To relax the receiver complexity in terms of performance requirement we can use Modulated Wideband Converter (MWC) architecture, a Sub-Nyquist sampling method. In this thesis circuit design of this architecture covers signal within a frequency range of 500 MHz to 2.1 GHz, with a channel bandwidth of 1600 MHz. By using 8 parallel lines with channel trading factor of 11, effective sampling rate of 550 MHz is achieved for successful support recovery of multi-band input signal of size N=12.

Modified discrete cosine transform (MDCT) derived from DCT IV has emerged as the most suitable choice for transform domain audio coding applications due to its time domain alias cancellation property and de-correlation capability. In the present research work, we focus on MDCT domain analysis of audio signals for compression and other applications. We have derived algorithms for linear filtering in DCT IV and DST IV domains for symmetric and non-symmetric filter impulse responses. These results are also extended to MDCT and MDST domains which have the special property of time domain alias cancellation. We also derive filtering algorithms for the DCT II and DCT III domains. Comparison with other methods in the literature shows that, the new algorithm developed is computationally MAC efficient. These results are useful for MDCT domain audio processing such as reverb synthesis, without having to reconstruct the time domain signal and then perform the necessary filtering operations. In audio coding, the psychoacoustic model plays a crucial role and is used to estimate the masking thresholds for adaptive bit-allocation. Transparent quality audio coding is possible if the quantization noise is kept below the masking threshold for each frame. In the existing methods, the masking threshold is calculated using the DFT of the signal frame separately for MDCT domain adaptive quantization. We have extended the spectral integration based psychoacoustic model proposed for sinusoidal modeling of audio signals to the MDCT domain. This has been possible because of the detailed analysis of the relation between DFT and MDCT; we interpret the MDCT coefficients as co-sinusoids and then apply the sinusoidal masking model. The validity of the masking threshold so derived is verified through listening tests as well as objective measures. Parametric coding techniques are used for low bit rate encoding of multi-channel audio such as 5.1 format surround audio. In these techniques, the surround channels are synthesized at the receiver using the analysis parameters of the parametric model. We develop algorithms for MDCT domain analysis and synthesis of reverberation. Integrating these ideas, a parametric audio coder is developed in the MDCT domain. For the parameter estimation, we use a novel analysis by synthesis scheme in the MDCT domain which results in better modeling of the spatial audio. The resulting parametric stereo coder is able to synthesize acceptable quality stereo audio from the mono audio channel and a side information of approximately 11 kbps. Further, an experimental audio coder is developed in the MDCT domain incorporating the new psychoacoustic model and the parametric model.

Our work focuses on wireless networks in general, but deals specifically with security in wireless sensor networks and energy consumption in IEEE 802.11 infrastructure WLANs. In the first part of our work, we focus on secure communication among sensor nodes in a wireless sensor network. These networks consists of large numbers of devices having limited energy and memory. Public key cryptography is too demanding for these resource-constrained devices because it requires high computation. So, we focus on symmetric key cryptography to achieve secure communication among nodes. For this cryptographic technique to work, two nodes have to agree upon a common key. To achieve this, many key distribution schemes have been proposed in the literature. Recently, several researchers have proposed schemes in which they have used group-based deployment models and assumed predeployment knowledge of the expected locations of nodes. They have shown that these schemes achieve better performance than the earlier schemes, in terms of connectivity, resilience against node capture and storage requirements. But in many situations expected locations of nodes are not available. We propose a solution which does not use the group-based deployment model and predeployment knowledge of the locations of nodes, and yet performs better than schemes which make the aforementioned assumptions. In our scheme, groups are formed after the deployment of sensor nodes on the basis of their physical locations. Nodes in different groups sample keys from disjoint key pools, so that compromise of a node affects secure links of its group only. Because of this reason, our scheme performs better than earlier schemes as well as the schemes using predeployment knowledge, in terms of connectivity, storage requirement, and security. Moreover, the post-deployment key generation process completes sooner than in schemes like LEAP+. In the second part of our work, we develop analytical models for estimating the energy spent by stations (STAs) in infrastructure WLANs when performing TCP-controlled file downloads. We focus on the energy spent in radio communication when the STAs are in the Continuously Active Mode (CAM), or in the static Power Save Mode (PSM). Our approach is to develop accurate models for obtaining the fractions of times the STA radios spend in idling, receiving and transmitting. We discuss two traffic models for each mode of operation: (i) each STA performs one large file download, and (ii) the STAs perform short file transfers with think times (short duration of inactivity)between two transfers. We evaluate the rate of STA energy expenditure with long file downloads, and show that static PSM is worse than using just CAM. For short file downloads, we compute the number of file downloads that can be completed with a given battery capacity, and show that PSM performs better than CAM for this case. We provide a validation of our analytical models using the NS-2 simulator. Although the PSM performs better than the CAM when the STAs download short files over TCP with think times, its performance degrades as the number of STAs associated to the access point (AP) increases. To address this problem, we propose an algorithm, which we call opportunistic PSM (OPSM). We show through simulations that OPSM performs better than PSM. The performance gain achieved by OPSM increases as the file size requested by the STAs or the number of STAs associated with the AP increases. We implemented OPSM in NS-2.33, and to compare the performance of OPSM and PSM, we evaluate the number of file downloads that can be completed with a given battery capacity and the average time taken to download a file.

The conventional approach to validate the analog and mixed signal designs utilizes extensive SPICE-level simulations. The main challenge in this approach is to know when all important corner cases have been simulated. An alternate approach is to use the formal verification techniques. Formal verification techniques have gained wide spread popularity in the digital design domain; but in case of analog and mixed signal designs, a large number of test scenarios need to be designed to generate sufficient simulation traces to test out all the specified system behaviours. Analog and mixed signal designs can be formally modeled as hybrid systems and therefore techniques used for formal analysis and verification of hybrid systems can be applied to the analog and mixed signal designs. Generally, formal verification tools for hybrid systems work at the abstract level where we model the systems in terms of differential equations or algebraic equations. However the analog and mixed signal system designers are very comfortable in designing the circuits at the transistor level. To bridge the gap between abstraction level verification and the designs validation which has been implemented at the transistor level, the very important issue we need to address is: Can we formally verify the circuits at the transistor level itself? For this we have proposed a framework for doing the formal verification of analog and mixed signal designs using SPICE simulation traces in one of the hybrid systems formal verification tools (i.e. Checkmate from CMU). An extension to a formal verification approach of hybrid systems is proposed to verify analog and mixed signal (AMS) designs. AMS designs can be formally modeled as hybrid systems and therefore lend themselves to the formal analysis and verification techniques applied to hybrid systems. The proposed approach employs simulation traces obtained from an actual design implementation of AMS circuit blocks (for example, in the form of SPICE netlists) to carry out formal analysis and verification. This enables the same platform used for formally validating an abstract model of an AMS design to be also used for validating its different refinements and design implementation, thereby providing a simple route to formal verification at different levels of implementation. Our approach has been illustrated through the case studies using simulation traces form the different frameworks i.e. Simulink/Stateflow framework and the SPICE simulation traces. We demonstrate the feasibility of our approach around the Checkmate and the case studies for hybrid systems and the analog and mixed signal designs.

This thesis is concerned with analytical modeling of Wireless Local Area Networks (WLANs) that are based on IEEE 802.11 Distributed Coordination Function (DCF). Such networks are popularly known as WiFi networks. We have developed accurate analytical models for the following three network scenarios: (S1) A single cell WLAN with homogeneous nodes and Poisson packet arrivals, (S2) A multi-cell WLAN (a) with saturated nodes, or (b) with TCP-controlled long-lived downloads, and (S3) A multi-cell WLAN with TCP-controlled short-lived downloads. Our analytical models are simple Markovian abstractions that capture the detailed network behavior in the considered scenarios. The insights provided by our analytical models led to two applications: (i) a faster “model-based'” simulator, and (ii) a distributed channel assignment algorithm. We also study the stability of the network through our Markov models. For scenario (S1), we develop a new approach as compared to the existing literature. We apply a “State Dependent Attempt Rate'” (SDAR) approximation to reduce a single cell WLAN with non-saturated nodes to a coupled queue system. We provide a sufficient condition under which the joint queue length Markov chain is positive recurrent. For the case when the arrival rates into the queues are equal we propose a technique to reduce the state space of the coupled queue system. In addition, when the buffer size of the queues are finite and equal we propose an iterative method to estimate the stationary distribution of the reduced state process. Our iterative method yields accurate predictions for important performance measures, namely, “throughput'”, “collision probability” and “packet delay”. We replace the detailed implementation of the MAC layer in NS-2 with the SDAR contention model, thus yielding a ``model-based'' simulator at the MAC layer. We demonstrate that the SDAR model of contention provides an accurate model for the detailed CSMA/CA protocol in scenario (S1). In addition, since the SDAR model removes much of the details at the MAC layer we obtain speed-ups of 1.55-5.4 depending on the arrival rates and the number of nodes in the single cell WLAN. For scenario (S2), we consider a restricted network setting where a so-called “Pairwise Binary Dependence” (PBD) condition holds. We develop a first-cut scalable “cell-level” model by applying the PBD condition. Unlike a node- or link-level model, the complexity of our cell-level model increases with the number of cells rather than with the number of nodes/links. We demonstrate the accuracy of our cell-level model via NS-2 simulations. We show that, as the “access intensity” of every cell goes to infinity the aggregate network throughput is maximized. This remarkable property of CSMA, namely, “maximization of aggregate network throughput in a distributed manner” has been proved recently by Durvy et al. (TIT, March, 2009) for an infinite linear chain of nodes. We prove it for multi-cell WLANs with arbitrary cell topology (under the PBD condition). Based on this insight provided by our analytical model we propose a distributed channel assignment algorithm. For scenario (S3), we consider the same restricted network setting as for scenario (S2). For Poisson flow arrivals and i.i.d. exponentially distributed flow sizes we model a multi-cell WLAN as a network of processor-sharing queues with state-dependent service rates. The state-dependent service rates are obtained by applying the model for scenario (S2) and taking the access intensities to infinity. We demonstrate the accuracy of our model via NS-2 simulations. We also demonstrate the inaccuracy of the service model proposed in the recent work by Bonald et al. (SIGMETRICS 2008) and identify the implicit assumption in their model which leads to this inaccuracy. We call our service model which accurately characterizes the service process in a multi-cell WLAN (under the PBD condition) “DCF scheduling” and study the “stability region” of DCF scheduling for small networks with single or multiple overlapping “contention domains”.

No description available.

No description available.

No description available.

No description available.