Two promising candidates for beyond 3rd generation (B3G) and 4G communication standards are multiple input multiple output (MIMO) and orthogonal frequency division multiple access (OFDMA) systems. OFDMA is a new technique that enables multiple users to transmit parallel data streams, allowing a much higher data rate than conventional systems, such as time division multiple access (TDMA) or code division multiple access (CDMA). Another research topic involving MIMO systems use antenna arrays at both the transmitter and the receiver. By using multiple antennas, the transmitter can adapt to the channel as it varies across time. This is accomplished by using a codebook of beamforming vectors which are known to both the transmitter and receiver. As the receiver acquires information about the channel, it calculates which beamforming vector matches the channel the best. The receiver then sends back the index of that vector to the transmitter. The symbol being transmitted is multiplied by the beamforming vector and sent over the channel, this is known as transmit beamforming (TB).;Transmit beamforming can not only increase performance in wireless MIMO systems, but also add increased performance when put in combination with other MIMO systems like spatial multiplexing and space time codes. TB has advantages over other MIMO schemes because by measuring the channel, one can use adaptive modulation techniques to achieve a coding gain not obtainable without channel state information (CSI). Past research assumed the feedback channel was error free and had no delay. This isolated the effects of finite rate feedback. We assume there is delay in the feedback channel along with imperfect channel estimation (ICE) at the receiver. We will show how detrimental these effects can be to TB's performance and can not be ignored.;OFDMA is a technique used to allow multiple users to communicate more reliably. This is possible because OFDMA utilizes CSI which can increase capacity, and decrease the total transmission power. With the amount of data being transmitted over wireless channels today, the need for faster, more efficient transmission techniques becomes essential. OFDMA uses adaptive modulation based on instantaneous channel conditions, to assign subcarriers to each user and allocate power to each carrier. Past research has focused on many different methods for OFDMA, using sum rate maximization techniques without fairness, or using short term fairness to improve the Quality of Service (QoS) to each mobile station. This thesis will address important issues that are missing, such as weighted SNR (w-SNR) based ranking with adaptive rate tracking to achieve long term rate proportional fairness (RPF) for downlink OFDMA. Long term RPF is less strict and performs better than short term RPF which is achieved through w-SNR ranking. The weight calculation can be implemented both online or offline. If channel statistics are known offline, a fixed weight vector can be calculated and used to allocate resources to each MS. When channel statistics are unknown, adaptive rate tracking can be used to calculate the weight vector online. Then resources are allocated based on each MS's weight factor. This sum rate maximization method with long term RPF and adaptive rate tracking has many advantages over traditional schemes, including ease of implementation, allowing a higher data rate with fairness, and allowing for distributed scheduling.