Broadcast MIMO techniques can significantly increase the throughput in the downlink of cellular networks, at the price of channel state information (CSI) feedback from the mobiles, sent over the uplink. Thus, these techniques create a mechanism that can tradeoff some uplink capacity for increased downlink capacity. In this work we quantify this tradeoff and study the exchange ratio between the feedback rate (over the uplink) and the downlink rate. We study both finite and infinite networks, and show that for high enough (but finite) SNR, the uplink rate can be exchanged for increased downlink rate with a favorable exchange ratio. This exchange ratio is an increasing function of the channel coherence time, and a decreasing function of the number of measured base stations. We also show that in finite networks, devoting a constant fraction of the uplink to CSI feedback can increase the downlink multiplexing gain continuously from 0 to 1, as a function of the fraction size. On the other hand, in infinite networks (with infinite connectivity) our lower bound is only able to show doubly logarithmic scaling of the rate with SNR. The presented results prove that the adaptation of the feedback rate can control the balance between the uplink and downlink rates. This capability is very important in modern cellular networks, where the operators need to respond to continuously changing user demands. I. Bergel is with

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Common Pilot cancellation in mobile receivers has recently gained attention for CDMA cellular networks [1-3]. This paper presents system simulation results showing that the network capacity gains achievable from both ideal and hardware resource limited pilot cancellation receivers are significant. We show that the highest gains are achieved for networks populated with high rate data users, rather than voice users. We also pay special attention to the interaction between pilot cancellation and soft handoff in a power controlled network. We show that pilot cancellation allows the network to operate with fewer mobiles in soft handoff, hence reducing network signaling overhead and infrastructure costs.