Multiuser orthogonal frequency division multiplexing (OFDM) with adaptive multiuser subcarrier allocation and adaptive modulation is considered. Assuming knowledge of the instantaneous channel gains for all users, we propose a multiuser OFDM subcarrier, bit, and power allocation algorithm to minimize the total transmit power. This is done by assigning each user a set of subcarriers and by determining the number of bits and the transmit power level for each subcarrier. We obtain the performance of our proposed algorithm in a multiuser frequency selective fading environment for various time delay spread values and various numbers of users. The results show that our proposed algorithm outperforms multiuser OFDM systems with static time-division multiple access (TDMA) or frequency-division multiple access (FDMA) techniques which employ fixed and predetermined time-slot or subcarrier allocation schemes. We have also quantified the improvement in terms of the overall required transmit power, the bit-error rate (BER), or the area of coverage for a given outage probability.

Recently it was proposed to adapt several transmission methods, including modulation, power control, channel coding and antenna diversity to rapidly time variant fading channel conditions. Prediction of the channel coefficients several tens-to-hundreds of symbols ahead is essential to realize these methods in practice. We describe a novel adaptive long range fading channel prediction algorithm (LRP) and its utilization with adaptive transmission methods. This channel prediction algorithm computes the linear Minimum Mean Squared Error (MMSE) estimates of future fading coefficients based on past observations. This algorithm can forecast fading signals far into the future due to its significant memory span, achieved by using a sufficiently low sampling rate for a given fixed filter size. The LRP is validated for standard stationary fading models, and tested with measured data and with data produced by our novel realistic physical channel model. This model accounts for the variation of the amplitude, frequency and phase of each reflected component of the fading signal. Both numerical and simulation results show that long range prediction makes adaptive transmission techniques feasible for mobile radio channels.

There has been burgeoning interest in wireless technologies that can use wider frequency spectrum. Technology advances, such as 802.11n and ultra-wideband (UWB), are pushing toward wider frequency bands. The analog-to-digital TV transition has made 100-250 MHz of digital whitespace bandwidth available for unlicensed access. Also, recent work on WiFi networks has advocated discarding the notion of channelization and allowing all nodes to access the wide 802.11 spectrum in order to improve load balancing. This shift towards wider bands presents an opportunity to exploit frequency diversity. Specifically, frequencies that are far from each other in the spectrum have significantly different SNRs, and good frequencies differ across sender-receiver pairs. This paper presents FARA, a combined frequency-aware rate adaptation and MAC protocol. FARA makes three departures from conventional wireless network design: First, it presents a scheme to robustly compute per-frequency SNRs using normal data transmissions. Second, instead of using one bit rate per link, it enables a sender to adapt the bitrate independently across frequencies based on these per-frequency SNRs. Third, in contrast to traditional frequency-oblivious MAC protocols, it introduces a MAC protocol that allocates to a sender-receiver pair the frequencies that work best for that pair. We have implemented FARA in FPGA on a wideband 802.11-compatible radio platform. Our experiments reveal that FARA provides a 3.1 × throughput improvement in comparison to frequency-oblivious systems that occupy the same spectrum.

OF THE DISSERTATION Energy-Aware Wireless Communications by Curt Schurgers Doctor of Philosophy in Electrical Engineering University of California, Los Angeles, 2002 Professor Mani B. Srivastava, Chair Embedded systems are evolving from single stand-alone entities into true networks of wirelessly connected devices, providing ubiquitous access and sensor-based information gathering. A key challenge is the management of energy in these systems, as they are battery powered for untethered operation. More and more, their energy consumption is dominated not by data processing, but by wireless communication. To ensure economic viability, this communication energy has to be reduced beyond what is achievable through digital circuit techniques, improvements in semiconductor technology, or advances in radio architectures alone.

We consider the linear precoded OFDM approach proposed in [1], where a non-redundant precoding was applied to the symbol blocks before entering the OFDM system. The precoding, while maintained the transmit power, introduced a structure to the transmitted signal that allowed for blind channel estimation by a simple auto-correlation performed at the receiver. We propose an adaptive modulation based extension of the method of [1] in order to combat channel with deep fading. Bits are allocated on each subcarrier so that the overall transmit power is minimized under a fixed bit error rate (BER). The obtained bit allocation can also be viewed as minimizing BER for the precoded system, under a fixed overall transmit power constraint. The proposed approach provides large performance gains over the uniformly loaded one, especially under deep fading conditions for the same overall throughput and transmit power.