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Wireless devices can exploit the knowledge of channel conditions to their advantage in achieving high throughput and robust communication. Current systems support multiple transmission rates and the ability to select a desirable rate. Higher transmission rates can be chosen when the channel quality is good thereby maximizing the throughput. Lower transmission rates can be selected when the channel quality is poor ensuring reliable message delivery. In order to achieve this, a wireless device needs some intelligence so it can assess the channel quality and adapt its transmission rate accordingly. This paper presents two novel algorithms to achieve throughput maximization and robust communication using intelligent link rate adaptation algorithms in the wireless device. The first of the two algorithms operates entirely at the sender and uses current channel quality information to guide the rate adaptation decision in finding the next transmission rate. The second algorithm relies on sender-receiver coordination in which feedback on current channel conditions at the recipient is provided to the sender via the rate used to transmit an acknowledgement (ACK). These algorithms were implemented in the ns-2 network simulator and their performance was evaluated against the classic Auto Rate Fallback (ARF) algorithm. Results from this study indicate that the proposed algorithms attain up to twice the throughput attained by ARF in certain scenarios. The results also confirm the limitations of ARF highlighted by previous studies.