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Proximity-based mobile social networking (PMSN) refers to the social interaction among physically proximate mobile users. The first step toward effective PMSN is for mobile users to choose whom to interact with. Profile matching refers to two users comparing their personal profiles and is promising for user selection in PMSN. It, however, conflicts with users' growing privacy concerns about disclosing their personal profiles to complete strangers. This paper tackles this open challenge by designing novel fine-grained private matching protocols. Our protocols enable two users to perform profile matching without disclosing any information about their profiles beyond the comparison result. In contrast to existing coarse-grained private matching schemes for PMSN, our protocols allow finer differentiation between PMSN users and can support a wide range of matching metrics at different privacy levels. The performance of our protocols is thoroughly analyzed and evaluated via real smartphone experiments.

In a mobile wireless system, fading effects can be classified into large-scale (long-term) effects and small-scale (short-term) effects. We use transmission power control to compensate for large-scale fading and exploit receiver antenna (space) diversity to combat small-scale fading. We show that the interferences across the antennas are jointly Gaussian in a large system, and then characterize the signal-to-interference ratio for both independent and correlated (across the antennas) small-scale fading cases. Our results show that when each user's small-scale fading effects are independent across the antennas, there is a clear separation between the gains of transmission power control and diversity combining, and the two gains are additive (in decibels). When each user's small-scale fading effects are correlated across the antennas, we observe that, in general, the gains of transmission power control and diversity combining are coupled. However, when the noise level diminishes to zero, using maximum ratio combining "decouples" the gains and achieves the same diversity gain as in the independent case. We then characterize the Pareto-optimal (minimum) transmission power allocation for the cases of perfect and noisy knowledge of the desired user's large-scale fading effects. We find that using antenna diversity leads to significant gains for the transmission power.