Chi Wan Sung

Convergence of Iterative Waterfilling Algorithm for Gaussian Interference Channels

The full diversity gain provided by a multi-antenna channel can be achieved by transmit beamforming and receive combining. This requires the knowledge of channel state information (CSI) at the transmitter which is difficult to obtain in practice. Quantized beamforming where fixed codebooks known at both the transmitter and the receiver are used to quantize the CSI has been proposed to solve this problem. Most recent works focus attention on limited feedback codebook design for the uncorrelated Rayleigh fading channel. Such designs are sub-optimal when used in correlated channels. In this paper, we propose systematic codebook design for correlated channels when channel statistical information is known at the transmitter. This design is motivated by studying the performance of pure statistical beamforming in correlated channels and is implemented by maps that can rotate and scale spherical caps on the Grassmannian manifold. Based on this study, we show that even statistical beamforming is near-optimal if the transmitter covariance matrix is ill-conditioned and receiver covariance matrix is well-conditioned. This leads to a partitioning of the transmit and receive covariance spaces based on their conditioning with variable feedback requirements to achieve an operational performance level in the different partitions. When channel statistics are difficult to obtain at the transmitter, we propose a universal codebook design (also implemented by the rotation-scaling maps) that is robust to channel statistics. Numerical studies show that even few bits of feedback, when applied with our designs, lead to near perfect CSI performance in a variety of correlated channel conditions.The full diversity gain provided by a multi-antenna channel can be achieved by transmit beamforming and receive combining. This requires the knowledge of channel state information (CSI) at the transmitter which is difficult to obtain in practice. Quantized beamforming where fixed codebooks known at both the transmitter and the receiver are used to quantize the CSI has been proposed to solve this problem. Most recent works focus attention on limited feedback codebook design for the uncorrelated Rayleigh fading channel. Such designs are sub-optimal when used in correlated channels. In this paper, we propose systematic codebook design for correlated channels when channel statistical information is known at the transmitter. This design is motivated by studying the performance of pure statistical beamforming in correlated channels and is implemented by maps that can rotate and scale spherical caps on the Grassmannian manifold. Based on this study, we show that even statistical beamforming is near-optimal if the transmitter covariance matrix is ill-conditioned and receiver covariance matrix is well-conditioned. This leads to a partitioning of the transmit and receive covariance spaces based on their conditioning with variable feedback requirements to achieve an operational performance level in the different partitions. When channel statistics are difficult to obtain at the transmitter, we propose a universal codebook design (also implemented by the rotation-scaling maps) that is robust to channel statistics. Numerical studies show that even few bits of feedback, when applied with our designs, lead to near perfect CSI performance in a variety of correlated channel conditions.

Low complexity subcarrier and power allocation for utility maximization in uplink OFDMA systems

We consider the joint subcarrier and power allocation problem with the objective of maximizing the total utility of users in the uplink of an OFDMA system. Our formulation includes the problems of sum rate maximization, proportional fairness and max-min fairness as special cases. Unlike some previous algorithms, which are iterative and time consuming, our proposed one is non-iterative and with time complexity of only O(KN log2 N), where K and N are the number of users and subcarriers respectively. We prove that it provides a solution that is Pareto optimal within a large neighborhood of itself. Besides, we derive an efficiently computable upper bound of the optimal solution. Simulation results show that our algorithm is nearly optimal.

User speed estimation and dynamic channel allocation in hierarchical cellular system

The huge amount of handoffs generated by microcells creates a problem for the future PCN. To alleviate the problem, we propose a hierarchical cellular system which comprises cells of different sizes. Ideally, one would like to use large cells to serve high-mobility users. A challenging issue is to obtain a good estimate of the user speed. A simple speed estimation is proposed and based on this estimate one can implement a number of dynamic channel allocation algorithms on such a hierarchical network. A comparative study of these algorithms will be presented based on a detailed simulation model.<<ETX>>

A distributed fixed-step power control algorithm with quantization and active link quality protection

A distributed fixed-step power control algorithm is presented. It is a simple feedback adjustment algorithm using only local information. In the ideal case where there is no power constraint, it is guaranteed that existing users will not be dropped due to admission of new users. If it is infeasible to accommodate all of them, the new user will be blocked. When the constraint on the maximum power is imposed, it is shown by simulation that blocking a new call is more probable than dropping any existing calls, if the capacity is exceeded. Besides, its convergence property is demonstrated. The convergence rate, which depends on the step size, is studied through simulation. In addition, the issue of power quantization is addressed.

Power control and rate management for wireless multimedia CDMA systems

We consider a wireless multimedia code-division multiple-access system, in which the terminals transmit at different rates. We formulate the problem as a constrained optimization problem, with the objective of maximizing the total effective rate. An optimal power control strategy is derived. When the scale of the system is large, the optimal solution takes a simple form, which is easy to be applied practically. Furthermore, our basic model can be extended to include delay-sensitive traffic.

An opportunistic power control algorithm for cellular network

We propose an opportunistic power control algorithm, which exploits channel fluctuation in order to maximize system throughput. The basic idea is that it instructs a transmitter to increase its power when the channel is good and to decrease its power when the channel is bad. The transmission rate is adjusted according to the received signal-to-interference ratio. The proposed algorithm is distributed and can be applied to systems in which the transmitters are connected to different receivers. We prove that the algorithm always converge to a unique fixed point and thus is stable. Simulation results show that a tremendous increase in system capacity can be achieved, when compared with other power control algorithms. Furthermore, the algorithm works well for nonreal-time terminals when other real-time terminals employ the target-tracking power control. It can also be extended to cases where maximum power constraint is imposed and soft handoff is executed

Log-convexity property of the feasible SIR region in power-controlled cellular systems

Power optimization problems are sometimes more convenient to be solved in the signal-to-interference ratio (SIR) domain. However, this methodology requires a characterization of the feasible SIR region. We derive a log-convexity property of the feasible SIR region, which is potentially useful for the design of a power-controlled system.

Sequential packing algorithm for channel assignment under cochannel and adjacent-channel interference constraint

Generally, the channel-assignment problem (CAP) for mobile cellular systems is solved by graph-coloring algorithms. These algorithms, though sometimes can yield an optimal solution, do not supply any information on whether an optimal solution has been found or bow far away it is from the optimum. In view of these undesirable features, two relevant results are presented. First, a lower bound for the minimum number of channels required to satisfy a given call-traffic demand is derived. This lower bound is tighter than the existing ones under certain conditions and can be used as a supplement for other approximate algorithms. Second, we propose an efficient heuristic algorithm to solve this problem. Although the CAP is nondeterministic polynomial (NP) complete in general, our algorithm provides an optimal solution for a special class of network topologies. For the general case, promising results are obtained, and numerical examples show that our algorithm has a better performance than many existing algorithms.

Shift-Invariant Protocol Sequences for the Collision Channel Without Feedback

The authors consider collision channel without feedback in which collided packets are considered unrecoverable. For each user, the transmission of packets follows a specific periodical pattern, called the protocol sequence. Due to the lack of feedback, the beginning of the protocol sequences cannot be synchronized and nonzero relative offsets are inevitable. It results in variation of throughput. In this paper, we investigate optimal protocol sequence sets, in the sense that the throughput variance is zero. Such protocol sequences are said to be shift-invariant (SI). The characterizing properties of SI protocol sequences are presented. We also prove that SI sequences are identifiable, meaning that the receiver is able to determine the sender of each successfully received packet without any packet header. A general construction of SI sequences that meets the lower bound on sequence length is given. Besides, we study the least periods of SI sequences, and show that the least periods must be distinct in some cases. The throughput performance is compared numerically with other protocol sequences.

On the stability of distributed sequence adaptation for cellular asynchronous DS-CDMA systems

We consider the sequence adaptation problem for cellular asynchronous code-division multiple-access (CDMA) systems. A game-theoretic approach is used to investigate the stability issues of distributed adaptation algorithms. It is shown that the Nash equilibrium may not exist for cellular CDMA systems if the traditional interference measure is used. In turn we propose a new interference measure which ensures system stability.