The explosion in demand for wireless data traffic in recent years

has triggered rapid development and pervasive deployment of

wireless communication networks. To meet the exponentially

increasing demand, a promising solution is the concept of wideband

small cells, which is based on the idea of using broader frequency

bandwidth and employing more efficient radio frequency resource

reuse by dense deployment of wideband, short-range, low cost and

low power base-stations. Broader bandwidth provides substantial

degrees of freedom as well as challenges for system design due to

the abundant multipaths and thus interference in high speed

systems under large delay spread channels. Reducing the

transmission range and increasing the number of cells permit

better spatial reuse of spectrum. With the proliferation of

wideband small cells, the strategy of selection among multiple

networks has significant impacts to the performance of users and

to the load balance of the system. In this dissertation, we

address these problems with a focus on waveform design and network

selection.

In time-reversal communication systems, the time-reversal transmit

waveform can boost the signal-to-noise ratio at the receiver with

simple single-tap detection by utilizing channel reciprocity with

very low transmitter complexity. However, the large delay spread

gives rise to severe inter-symbol interference when the data rate

is high, and the achievable transmission rate is further degraded

in the multiuser downlink due to the inter-user interference. We

study the weighted sum rate optimization problem by means of

waveform design in the time-reversal multiuser downlink. We

propose a new power allocation algorithm, which is able to achieve

comparable sum rate performance to that of globally optimal power

allocation. Further, we study the joint waveform design and

interference pre-cancellation by exploiting the symbol information

to further improve the performance by utilizing the information of

previous symbols. In the proposed joint design, the causal

interference is subtracted using interference pre-cancellation and

the anti-causal interference can be further suppressed by waveform

design with more degrees of freedom.

The second part of this dissertation is concerned with the

wireless access network selection problem considering the negative

network externality, i.e, the influence of subsequent users'

decisions on an individual's throughput due to the limited

available resources. We formulate the wireless network selection

problem as a stochastic game with negative network externality and

show that finding the optimal decision rule can be modelled as a

multi-dimensional Markov decision process. A modified value

iteration algorithm is proposed to efficiently obtain the optimal

decision rule with a simple threshold structure, which enables us

to reduce the storage space of the strategy profile. We further

investigate the mechanism design problem with incentive

compatibility constraints, which enforce the networks to reveal

the truthful state information. We analyze a data set of wireless

LAN traces collected from campus networks, from which we observe

that the number of user arrivals is approximately Poisson

distributed; the session time and the waiting time to switch

network can be approximated by exponential distributions. Based on

the analysis, we formulate a wireless access network association

game with both arriving strategy and switching strategy and

validate the effectiveness of the proposed best response strategy.