Managing Randomness in Wireless Networks: Random Power Control and Successive Interference Cancellation

Considering wireless networks whose channel quality and node distribution are random, this thesis studies two types of techniques that can potentially significantly boost the network performance: random power control and successive interference cancellation (SIC).

Random power control generalizes conventional (deterministic) power control by allowing the transmitters to randomly vary their transmit power. In the first part of the thesis, we study random power control in two types of wireless networks: the noise-limited networks and the interference-limited networks. In noise-limited networks, we show that random power control can significantly reduce the local delay, and the optimal power control policies are ALOHA-type random on-off policies. In interference-limited networks, we take a game theoretic framework and focus on two sets of strategies: single-node optimal power control (SNOPC) strategies and Nash equilibrium power control (NEPC) strategies. SNOPC strategies maximize the expected throughput of the power controllable link given that all the other transmitters do not use power control. Under NEPC strategies, no individual node of the network can achieve a higher expected throughput by unilaterally deviating from these strategies. We prove that under mean and peak power constraints at each transmitter, the SNOPC and NEPC strategies are ALOHA-type random on-off power control policies.

Successive interference cancellation (SIC) allows the receiver to decode and cancel signal components from users sequentially and thus can potentially significantly boost the network throughput. However, the feasibility of SIC depends on the received signal power ordering which further depends on the fading distribution, network geometry, and many other system parameters. In the second part of the thesis, we provide a unified framework to study the performance of SIC in d-dimensional wireless networks with arbitrary fading distribution and power-law path loss. Using this framework, we are able to analytically characterize the performance of SIC. The results suggest that the marginal benefit of enabling the receiver to successively decode k users diminishes very fast with k, especially in networks of high dimensions and small path loss exponent. On the other hand, SIC is highly beneficial when the users are clustered around the receiver and/or very low-rate codes are used, and with multiple packet reception, a lower per-user information rate always results in higher aggregate throughput in interference-limited networks. In contrast, there exists a positive optimal per-user rate that maximizes the aggregate throughput in noisy networks.

The analytical results serve as useful tools to understand the potential gain of SIC in heterogeneous cellular networks (HCNs). Using these tools, we quantify the gain of SIC on the coverage probability in HCNs with non-accessible base stations. An interesting observation is that, for contemporary narrow-band systems (e.g., LTE and WiFi), most of the gain of SIC is achieved by canceling a single interferer.