An effective method for mitigating transmitter nonlinear echo in 10GBASE-T transceivers is discussed. This method is based on approximating the nonlinear characteristics of the combined transmitter and the echo channel by smooth multidimensional functions. Results based on a chip fabricated in 0.13 mum CMOS technology show that approximately 6 dB of average cancellation of nonlinear echo can be achieved by this method.

We derive optimal and suboptimal multiuser transmit-optimization methods for a multicarrier broadcast channel with intersymbol interference under the frequency-division multiple-access (FDMA) restriction. The general FDMA-based multicarrier broadcast problem is formulated as a maximum weighted rate-sum problem. Given each user's subchannel assignment, the optimal transmit strategy is achieved by multilevel waterfilling. Unfortunately, the problem of finding the optimal subchannel assignments is combinatorial. However, by relaxing the FDMA restriction, we obtain a convex reformulation that allows for efficient computation of the optimal solution, and therefore, a characterization of the FDMA capacity region for a broadcast channel. If all users share the same transmission medium, we prove that the optimal frequency partitioning among the users has an ordered structure that can be exploited to significantly reduce the computational complexity. To make multiuser transmit-optimization schemes practical for applications with relatively fast time-varying user data-rate requirements or priorities, further reduction in computational complexity is necessary. This is achieved by restricting the energy distribution to be constant across the used subchannels. Simulations indicate the low-complexity constant-energy methods presented are very robust, and suffer from negligible performance loss.

This paper proposes a new method for decoding multicarrier symbols with severe nonlinear distortion. The first part evaluates mutual information expressions for practical nonlinear models and shows the performance bounds for commonly used receiver structures. Then, we derive the maximum-likelihood (ML) sequence estimator, which unfortunately has an exponential complexity due to the nonlinear distortion. This extremely large complexity can be reduced with a simple algorithm that iteratively estimates the nonlinear distortion, thereby reducing the exponential ML to the standard ML without nonlinear distortion. The proposed method can be used to reduce the peak-to-average power ratio of multicarrier signals by clipping the transmit sequence. It can also be used to correct any nonlinear distortion present in transmitter/receiver amplifiers that are operating close to saturation.

We consider the problem of optimal power allocation for a broadcast channel with ISI under the FDMA restriction. Due to the FDMA restriction, the resulting problem is combinatorial in nature and hard to solve. However, by relaxing the FDMA restriction, we obtain a convex reformulation that allows for efficient computation of the optimal solution and therefore, a characterization of the capacity region. It is also shown that under certain conditions on the channel responses, the optimal frequency partition has an ordered structure that can be exploited to further reduce the computational complexity.

This paper investigates peak-to-average power ratio (PAR) reduction in block transmission systems when the effects of transmit filters are included. Two new algorithms are presented that reduce the PAR more than conventional PAR methods. These algorithms are shown to be effective in multicarrier modulation. An improvement of over 2 dB is shown for block lengths of size 256.

This paper formulates the problem of embedded modulation applied to a multiuser multicarrier system. These embedded multiuser optimization problems are shown to be convex, for which globally optimal solutions can be computed efficiently. We also show that these embedded problems are convex relaxations of the combinatorial FDMA multiuser problems and thus provide performance bounds to the optimal and asymptotically optimal solutions proposed by Hoo, Tellado and Cioffi (see IEEE Global Telecommunications Conf. (Globecom), p.25-30, 1998 and IEEE PIMRC, p.278-82, 1998).

We analyze the general problem of multiuser transmit optimization for a Gaussian broadcast channel with ISI under the FDMA restriction. Due to the FDMA restriction, the resulting problem is combinatorial in nature and hard to solve. However, by relaxing the FDMA restriction, we obtain a convex reformulation that allows for efficient computation of the optimal solution. By enforcing a constant-energy restriction, further reduction in computational complexity is achieved. We present the optimal and one suboptimal constant-energy method with bandwidth optimization. Simulation results show that these methods suffer from negligible performance loss even at low SNRs where the constant-energy approximation is not valid.

We derive the optimal bit and energy allocation for a discrete multitone (DMT) modulation system simultaneously providing two services with different quality of services (QoS), and show that it is NP-hard. Thus, we propose three novel, fast, discrete dual loading algorithms. These methods apply Campello's (see IEEE International Symposium on Info. Theory, MIT, p.193, 1998) discrete loading algorithms and are based on a novel tone selection procedure that offers significant reduction in complexity but still achieves near optimal performance. Simulation results support our tone selection procedure by indicating the convergence in performance of these loading algorithms to the optimum with increasing N, N being the number of subchannels or tones.

It is well known that the minimum mean square error (MMSE) and minimum peak distortion (MPD) criteria do not minimize bit error rate (MinBER), and for some channels they can have a large degradation compared to the MinBER solution. Based on the strengths and weaknesses of the MMSE and MPD criteria, we have defined two new solutions, which we call minimum noise limited peak distortion (MNLPD) and min-/spl alpha/. The first solution is based on MPD but avoids the problem of noise enhancement. The second solution finds the optimal of a family of equalizers derived from the MMSE and MPD criteria. We have shown by numerical calculation that by using the MNLPD or the min-/spl alpha/ criteria we can achieve almost MinBER performance. The proposed methods have a larger complexity, but can be solved using well known techniques since they can be described as simple convex optimization problems.

We propose a novel loading algorithm for discrete multitone (DMT) modulation or orthogonal frequency division multiplex (OFDM) systems simultaneously providing two constant bit rate (CBR) services. Furthermore, these two services have different quality of services (QoS) characterized respectively by their target bit error rates (BER). We derive the optimal solution and show that it is NP-hard. Thus, we propose a method namely, disjoint bandwidth (DBW) which is O(N log N) that still gives near optimal performance. The reduction in complexity is enabled by the set selection procedure we propose. Simulation results for frequency selective Rayleigh fading channels with additive white Gaussian noise show that the DBW method is within 0.1% of the optimum for a total number of carriers N>12 and that it performs on the average 15% better than any previously reported method in the literature.

We simulate the performance of an equalized Gaussian minimum shift keying (GMSK) signal in an indoor radio environment with fading, noise, imperfect carrier recovery, cochannel interference (CCI), and intersymbol interference (ISI). We show that data rates of 20 Mb/s at bit error rates (BER) /spl les/10/sup -4/ are possible with root mean square (RMS) delay spreads up to 25 ns using a simple limiter-discriminator-integrator (LDI) receiver and a (6, 4) decision feedback equalizer (DFE). In environments with larger RMS delay spreads, coherent detection is required for the same performance. We show that using a decision-directed second-order digital carrier synchronizer with time varying loop filters, frequency offsets up to 200 kHz can be corrected with negligible performance degradation. This paper utilizes a DFE structure which compensates for both modulator and channel ISI, and yet requires no power-intensive multiplication operations in the feedback section. A DFE (8, 8) with two-level switched (selection) diversity is shown to allow 20 Mb/s data transfer at a BER/spl les/10/sup -4/ for RMS delay spreads under 150 ns, with CCI. A light BCH (26, 31) code allows error-free reception of over 90% of packets with RMS delay spreads under 150 ns, and up to 70% of packets with RMS delays of 150 ns.

We simulate the performance of an equalized Gaussian minimum shift keying (GMSK) signal in an indoor radio environment with fading, noise, cochannel interference and intersymbol interference (ISI). We show that data rates of 20 Mbps at bit error rates (BER) /spl les/10/sup -4/ are possible with RMS delay spreads up to 25 ns using a simple limiter-discriminator-integrator receiver and a (6,4) decision feedback equalizer (DFE). In environments with larger RMS delay spreads, coherent detection is required for the same performance. We introduce a DFE structure which compensates for both modulator and channel ISI, and yet requires no power-intensive multiplication operations in the feedback section. An (8,8) DFE with 2-level switched (selection) diversity is shown to allow 20 Mbps data transfer at BER /spl les/10/sup -4/ for RMS delay spreads under 150 ns, with cochannel interference. Adding a (26,31) BCH code allows error-free reception of over 90% of packets with RMS delay spreads under 150 ns, and up to 70% of packets with RMS delays of 150 ns.