This paper presents the capacity region of frequency-selective Gaussian interference channels under the condition of strong interference, assuming an average power constraint per user. First, a frequency-selective Gaussian interference channel is modeled as a set of independent parallel memoryless Gaussian interference channels. Using nonfrequency selective results, the capacity region of frequency-selective Gaussian interference channels under strong interference is expressed mathematically. Exploiting structures inherent in the problem, a dual problem is constructed for each independent memoryless channel, in which both mathematical and numerical analysis are performed. Furthermore, three suboptimal methods are compared to the capacity-achieving coding and power allocation scheme. Iterative waterfilling, a suboptimal scheme, provides close-to-optimum performance and has a distributed coding and power allocation scheme, which are attractive in practice.

This letter examines a discrete bit-loading problem of upstream and downstream for discrete multitone digital subscriber lines with echo cancellation. Both far-end crosstalk and near-end crosstalk are taken into account. An optimal discrete bit-loading algorithm is developed when the loop lengths of all same-service users in a common binder are the same. Simulation results show that the optimal algorithm achieves a substantially higher data rate than existing suboptimal schemes.

This paper proposes adaptive modulation and coding (AMC) as a method for the bit-interleaved coded OFDM (BIC-OFDM) packet transmission. Following a pair-wise error probability (PEP) analysis of AMC-BIC-OFDM in a slowly fading frequency selective channel, AMC scheme maximizes the total rate by optimally selecting the code and efficiently allocating rate and power over the frequency band. The proposed method improves upon the performance of uniform rate and power allocation scheme by 6.5 to 10 dB

Adaptive modulation and coding (AMC) is receiving increasing attention as an effective method to enhance the performance of wireless systems. This paper proposes AMC as a method for the bit-interleaved coded OFDM (BIC-OFDM) packet transmission. We provide a pair-wise error probability (PEP) analysis of AMC-BIC-OFDM in a slowly fading frequency selective channel. We maximize the total rate by optimally selecting the code and efficiently allocating rate and power over the frequency band. The proposed method improves the performance of uniform rate and power allocation scheme by 8 to 19 dB.

This paper presents the capacity region of frequency-selective Gaussian interference channels under the condition of strong interference, assuming an average power constraint per user. First, a frequency-selective Gaussian interference channel is modeled as a set of independent parallel memoryless Gaussian interference channels. Using non-frequency selective results, the capacity region of frequency-selective Gaussian interference channels under strong interference is expressed mathematically. Exploiting structures inherent in the problem, a dual problem is constructed for each independent memoryless channel, and solved. Furthermore, three suboptimal methods are compared with the capacity-achieving coding and power allocation scheme. Iterative waterfilling, a suboptimal scheme, provides close-to-optimum performance and has a distributed coding and power allocation scheme, which are attractive in practice.

Maximizing the total rate with no coordination is an attractive option to increase the throughput of existing multiuser communication systems. The paper compares a suboptimal method for rate and power allocation in a two-user multicarrier channel with the optimal method, subject to individual power constraints. The suboptimal method, iterative waterfilling (IW), closely approximates the performance of the optimal method when interference power is small. Moreover, IW is easy to deploy in existing systems in which different transmission paths may not be coordinated.

Using multiple antennas at both the transmitter and receiver, BLAST exploits the multipath characteristics of a wireless channel to enable very large capacities. In an extended V-BLAST, those capacities are approached with single-dimensional coding and rate adaptation. However, such results require infinite precision for rate and power settings and perfect channel estimation. These assumptions are not practical due to a limited data rate of the feedback channel and a rapidly changing nature of a wireless channel. An algorithm for discretizing the rates and power control levels is proposed. We show that the loss in spectral efficiency due to rate and power control discretization is about 1-2 dB compared to that of an eigenmode transmission. We also consider the effects of imperfect channel estimation. We show that the performance loss is minimal when the channel estimation error is less than 2-3%.

Using multiple antennas at both the transmitter and receiver, BLAST exploits the multipath characteristics of a wireless channel to enable very large capacities. In an extended V-BLAST, those capacities are approached with single-dimensional coding and rate adaptation. However, such results require infinite precision for rate and power, which is not implementable due to a limited data rate on the feedback channel. We show that discretizing the rates to QAM constellations causes a 3-5 dB penalty. We then propose SQPC (successive quantization with power control), an ad-hoc low-complexity algorithm that reduces that penalty to 1-3 dB. We show that SQPC closely approaches the performance limit attainable with discrete QAM rates, which we find numerically by exhaustive search.

Multiple antennas at the transmitter and receiver can achieve enormous capacities by transmitting on the channel's eigenmodes when the channel realization is known at the transmitter. If the transmitter has no knowledge of the channel, a significant fraction of the eigenmode capacity can be achieved in an open-loop mode, but multi-dimensional coding is required. We show how the open-loop capacity can be achieved with conventional single-dimensional coding using optimum successive decoding (OSD) and simple per-antenna rate control. Using power allocation, the capacity can be further increased, although only slightly.

We examine adaptive modulation schemes for flat-fading channels where the data rate, transmit power, and instantaneous BER are varied to maximize spectral efficiency, subject to an average power and BER constraint. Both continuous-rate and discrete-rate adaptation are considered, as well as average and instantaneous BER constraints. We find the general form of power, BER and data rate adaptation that maximizes spectral efficiency for a large class of modulation techniques and fading distributions. The optimal adaptation of these parameters is to increase the power and data rate and decrease the BER as the channel quality improves. Surprisingly, little spectral efficiency is lost when the power or rate is constrained to be constant. Hence, the spectral efficiency of adaptive modulation is relatively insensitive to which degrees of freedom are adapted.