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Doctor of Philosophy (PhD) / This thesis considers transmission techniques for current and future wireless and mobile communications systems. Many of the results are quite general, however there is a particular focus on code-division multiple-access (CDMA) and multi-input multi-output (MIMO) systems. The thesis provides analytical techniques and results for finding key performance metrics such as signal-to-interference and noise power ratios (SINR) and capacity. This thesis considers a large-system analysis of a general linear matrix-vector communications channel, in order to determine the asymptotic performance of linear fixed and adaptive receivers. Unlike many previous large-system analyses, these results cannot be derived directly from results in the literature. This thesis considers a first-principles analytical approach. The technique unifies the analysis of both the minimum-mean-squared-error (MMSE) receiver and the adaptive least-squares (ALS) receiver, and also uses a common approach for both random i.i.d. and random orthogonal precoding. The approach is also used to derive the distribution of sums and products of free random matrices. Expressions for the asymptotic SINR of the MMSE receiver are derived, along with the transient and steady-state SINR of the ALS receiver, trained using either i.i.d. data sequences or orthogonal training sequences. The results are in terms of key system parameters, and allow for arbitrary distributions of the power of each of the data streams and the eigenvalues of the channel correlation matrix. In the case of the ALS receiver, we allow a diagonal loading constant and an arbitrary data windowing function. For i.i.d. training sequences and no diagonal loading, we give a fundamental relationship between the transient/steady-state SINR of the ALS and the MMSE receivers. We demonstrate that for a particular ratio of receive to transmit dimensions and window shape, all channels which have the same MMSE SINR have an identical transient ALS SINR response. We demonstrate several applications of the results, including an optimization of information throughput with respect to training sequence length in coded block transmission.

In this dissertation, we explore the issues related to opportunistic and cooperative communications in a multiuser environment. In the first part of the dissertation, we consider opportunistic scheduling for delay limited systems. Multiuser communication over fading channels is a challenging problem due to fast varying channel conditions. On the other hand, it provides opportunities to exploit the varying nature of the channel and maximize the throughput by scheduling the user (or users) with good channel. This gain is termed as multiuser diversity. The larger the number of users, the greater is the multiuser diversity gain. However, there is an inherent scheduling delay in exploiting multiuser diversity. The objective of this work is to design the scheduling schemes which use multiuser diversity to minimize the system transmit energy. We analyze the schemes in large system limit and characterize the energy--delay tradeoff. We show that delay tolerance in data transmission helps us to exploit multiuser diversity and results in an energy efficient use of the system resources. We assume a general multiuser environment but the proposed scheduling schemes are specifically suitable for the wireless sensor network applications where saving of transmit energyat the cost of delay in transmission is extremely useful to increase the life of battery for the sensor node. In the first part of the thesis, we propose scheduling schemes withthe objective of minimizing transmit energy for a given fixed tolerable transmission delay. The fixed delay is termed as hard deadline. A group of users with channels better than a transmission threshold are scheduled for transmission simultaneously using superposition coding. The transmission thresholds depend onthe fading statistics of the underlying channel and hard deadline of the data to be scheduled. As deadline is approached, the thresholds decrease monotonically to reflect the scheduling priority for theuser. We analyze the proposed schedulers in the large system limit. We compute the optimized transmission thresholds for the proposed scheduling schemes. We analyze the proposed schemes for practically relevant scenarios when the randomly arriving packets have individual, non--identical deadlines. We analyze the case when loss tolerance of the application is exploited to further decrease the system energy. The transmitted energy is not a convex function oftransmission thresholds. Therefore, we propose heuristic optimization procedures to compute the transmission thresholds and evaluate the performance of the schemes. Finally, we study the effect of outer cell interference on the proposed scheduling schemes. The second part of the thesis investigates the problem of cooperative communication between the nodes which relay the data of other sources multiplex with their own data towards a common destination, i.e. a relay node performs as a relay and data source at the same time. This problem setting is very useful in case of some wireless sensor network (WSN) applications where all the nodes relay sensed data towards a common destination sink node. The capacity region of a relay region is still an open problem. We use deterministic network model to study the problem. We characterizethe capacity region for a cooperative deterministic network with single source, multiple relays and single destination. We also characterize the capacity region when communicating nodes have correlated information to be sent to the destination. / Cross Layer Optimization of Wireless Sensor Networks

Doctor of Philosophy (PhD) / This thesis considers transmission techniques for current and future wireless and mobile communications systems. Many of the results are quite general, however there is a particular focus on code-division multiple-access (CDMA) and multi-input multi-output (MIMO) systems. The thesis provides analytical techniques and results for finding key performance metrics such as signal-to-interference and noise power ratios (SINR) and capacity. This thesis considers a large-system analysis of a general linear matrix-vector communications channel, in order to determine the asymptotic performance of linear fixed and adaptive receivers. Unlike many previous large-system analyses, these results cannot be derived directly from results in the literature. This thesis considers a first-principles analytical approach. The technique unifies the analysis of both the minimum-mean-squared-error (MMSE) receiver and the adaptive least-squares (ALS) receiver, and also uses a common approach for both random i.i.d. and random orthogonal precoding. The approach is also used to derive the distribution of sums and products of free random matrices. Expressions for the asymptotic SINR of the MMSE receiver are derived, along with the transient and steady-state SINR of the ALS receiver, trained using either i.i.d. data sequences or orthogonal training sequences. The results are in terms of key system parameters, and allow for arbitrary distributions of the power of each of the data streams and the eigenvalues of the channel correlation matrix. In the case of the ALS receiver, we allow a diagonal loading constant and an arbitrary data windowing function. For i.i.d. training sequences and no diagonal loading, we give a fundamental relationship between the transient/steady-state SINR of the ALS and the MMSE receivers. We demonstrate that for a particular ratio of receive to transmit dimensions and window shape, all channels which have the same MMSE SINR have an identical transient ALS SINR response. We demonstrate several applications of the results, including an optimization of information throughput with respect to training sequence length in coded block transmission.

Multiple antennas at each side of the communication channel seem to be vital for future wireless communication systems. Multi-antenna communication provides throughput gains roughly proportional to the smallest number of antennas at the communicating terminals. On the other hand, multiple antennas at a terminal inevitably increase the hardware complexity of the latter. For efficient design of such systems relevant mathematical tools, capable of capturing the most significant features of the wireless multi-antenna channel - such as fading, spatial correlation, interference - are essential. This thesis, based on the asymptotic methods from statistical physics and random matrix theory, develops a series of asymptotic approximations for various metrics characterizing the performance of multi-antenna systems in different settings. The approximations become increasingly precise as the number of antennas at each terminal grows large and are shown to significantly simplify the performance analysis. This, in turn, enables efficient performance optimization, which would otherwise be intractable. After a general introduction, provided in Chapter 2, this thesis provides four different applications of large-system analysis. Thus, Chapter 3 analyzes multi-antenna multiple-access channel in the presence of non-Gaussian interference. The obtained large-system approximation of the sum rate is further used to carry out the precoder optimization routine for both Gaussian and finite-alphabet types of inputs. Meanwhile, Chapter 4 carries out the large-system analysis for a multi-hop relay channel with an arbitrary number of hops. Suboptimality of some conventional detectors has been captured through the concept of generalized posterior mean estimate. The obtained decoupling principle allows performance evaluation for a number of conventional detection schemes in terms of achievable rates and bit error rate. Chapter 5, in turn, studies achievable secrecy rates of multi-antenna wiretap channels in three different scenarios. In the quasi-static scenario, an alternating-optimization algorithm for the non-convex precoder optimization problem is proposed. The algorithm is shown to outperform the existing solutions, and it is conjectured to provide a secrecy capacity-achieving precoder. In the uncorrelated ergodic scenario, a large-system analysis is carried out for the ergodic secrecy capacity yielding a closed-form expression. In the correlated ergodic scenario, the obtained large-system approximation is used to address the corresponding problem of precoder optimization. Finally, Chapter6 addresses a practical case of random network topology for two scenarios: i) cellular mobile networks with randomly placed mobile users and ii) wiretap channel with randomly located eavesdroppers. Large-system approximations for the achievable sum rates are derived for each scenario, yielding simplified precoder optimization procedures for various system parameters. / <p>QC 20140901</p>