Wideband Multiuser OFDM : Implementation and Capacity

Optimal bit and power allocation in OFDM wireless systems allows for dramatic increases in user and data capacity. This paper focuses on two main fronts. First, previous results are extended to include time-varying fading. Furthermore, a simple (but novel, or at least, not previously published) optimization goal, maximizing the sum of user rates, and an iterative algorithm is presented which allows for pseudo-optimal results. These are compared with previous work using a time-varying correlated Rayleigh frequency selective channel model. Second, the problem of high peak-to-average signal ratio is widely understood and studied within the OFDM community. However, attention has not been given to what effect optimal power and bit allocation have on the problem. Some simulation results are presented, and a direction for analytical work is proposed. Model High speed wireless data is the current industry fad. While there have not been successful widearea implementations of this paradigm, many are hopeful that consumers desire access to large bandwidth data in locations in which it is inconvenient for them to be plugged in to a wall. As a result, much of the research in the last few years has centered on technologies that would enable these high bandwidth systems. While some researchers are focusing on ad hoc network architectures, it is likely that structured networks will form the backbone of any high speed wireless infrastructure for the next decade. As a result, this paper centers on systems structured in such a way that there is one node (the base station) that is communicating with the rest of the nodes in a time-division-duplexing paradigm, and (somehow) is able to develop perfect information regarding the channels between it and the users. The attenuation of a high frequency wireless channels along a particular, (speficically not direct “line-of-sight”) path is well modeled in magnitude (given standard assumptions [1]) by a Rayleigh random variable. In this study, a frequency selective fading channel is constructed by forming an exponentially decreasing impulse response, where each of the five taps are Rayleigh random variates with uniformly distributed random phases. Within a symbol time, the channels between each user and the base station are assumed to be constant. However, to further enhance the channel model, between symbol times, each tap follows an independent, but self-correlated path according to the an auto-correlation function modeled on slow motion assuming a unidirectional received beam (see [2]). Figure 1 shows a timesegment of the channel. The correlated Rayleigh variables are generated according to [2], with an FFT size of 1024 (thus, 1024 are generated simultaneously. Scaling ensures that the average subcarrier power will be unity. Additionally, the power of the noise in each subcarrier band is assumed to be unity (without loss of generality). One failure of this model is that it only includes the fading process, and ignores path loss and shadowing. These omissions are especially unfortunate for the peak-power and clipping simulations. However, the assumption is made that the power amplifiers can be controlled using a feedback mechanism to compensate for the (relatively slow) processes of shadowing and path loss. In fact, the maximum and minimum signal amplitudes of a power amplifier can indeed be adjusted by adjusting the maximum and minimum voltage sources in the circuit. This adjustment process, however, is very inexact compared to DSP processing [8]. Figure 1: Channel Model Since the seminal paper ([3]) more than 20 years ago, it has been recognized that for capacity-maximizing transmission (in a multi-user total data rate sense), it is optimal to “waterfill” in a communications channel. The basic intuition involved is to transmit a lot of data and power in good channel states, and less in bad ones. Thus, in a frequency selective fading the optimal power is frequency dependent. The channel states can be