Arak Sutivong

Multiple user writing on dirty paper

Writing on dirty paper, a variation of the standard additive white Gaussian noise (AWGN) channel with the channel output is considered. The Gaussian noise noncausally known at the transmitter does not affect the capacity of the AWGN channel. This is known as WDP property. The WDP property for three Gaussian multiple user channels with known capacity region is established. The achievable rate regions of corresponding discrete channels is proved. Although those regions may be suboptimal in general, they turn out to be optimal for these Gaussian channels. Alternative proofs can be obtained by successive uses of Costas WDP coding scheme, from which the WDP property can be established for more general noise and state distributions.

Writing on colored paper

A Gaussian channel when corrupted by an additive Gaussian interfering signal that is not necessarily stationary or ergodic, but whose complete sample sequence is known to the transmitter, has the same capacity as if the interfering signal were not present.

Channel capacity and state estimation for state-dependent Gaussian channels

We formulate a problem of state information transmission over a state-dependent channel with states known at the transmitter. In particular, we solve a problem of minimizing the mean-squared channel state estimation error E/spl par/S/sup n/ - S/spl circ//sup n//spl par/ for a state-dependent additive Gaussian channel Y/sup n/ = X/sup n/ + S/sup n/ + Z/sup n/ with an independent and identically distributed (i.i.d.) Gaussian state sequence S/sup n/ = (S/sub 1/, ..., S/sub n/) known at the transmitter and an unknown i.i.d. additive Gaussian noise Z/sup n/. We show that a simple technique of direct state amplification (i.e., X/sup n/ = /spl alpha/S/sup n/), where the transmitter uses its entire power budget to amplify the channel state, yields the minimum mean-squared state estimation error. This same channel can also be used to send additional independent information at the expense of a higher channel state estimation error. We characterize the optimal tradeoff between the rate R of the independent information that can be reliably transmitted and the mean-squared state estimation error D. We show that any optimal (R, D) tradeoff pair can be achieved via a simple power-sharing technique, whereby the transmitter power is appropriately allocated between pure information transmission and state amplification.

Admission control algorithms for cellular systems

This paper evaluates call admission control algorithms for a cellular or microcellular system. Algorithms are evaluated based on two Quality of Service (QoS) metrics: the new call blocking probability, which is the probability that a new call is denied access to the system, and the forced-termination probability, which is the probability that a call that has been admitted will be terminated prior to the calls completion. Three novel algorithms are presented: the Weighted Sum Scheme, the Probability Index Scheme, and the Hybrid Control Scheme. The weighted sum scheme uses the weighted sum of the number of calls underway in various cells when making the admission decision. The probability index scheme computes a probability index, which reflects the forced-termination probability of a new call arrival, and admits those calls with low probability indexes. The hybrid control scheme combines these two approaches. These novel algorithms are compared with three known algorithms: the Reservation Scheme in which a specific number of channels are reserved in each cell for handoffs, the Linear Weighting Scheme in which the admission decision depends on the total number of calls underway in a group of cells, and the Distributed Admission Control Scheme in which the admission decision depends on the projected overload probabilities in the cell at which the new call arrives and adjacent cells. We show that the Hybrid Control Scheme yields the best performance, particularly during periods when load differs from the expected level. We also show that the simple Reservation Scheme performs remarkably well, often superior to more complex schemes that have been proposed.

Approaching the MIMO capacity with a low-rate feedback channel in V-BLAST

This paper presents an extension of the vertical Bell Laboratories Layered Space-Time (V-BLAST) architecture in which the closed-loop multiple-input multiple-output (MIMO) capacity can be approached with conventional scalar coding, optimum successive decoding (OSD), and independent rate assignments for each transmit antenna. This theoretical framework is used as a basis for the proposed algorithms whereby rate and power information for each transmit antenna is acquired via a low-rate feedback channel. We propose the successive quantization with power control (SQPC) and successive rate and power quantization (SRPQ) algorithms. In SQPC, rate quantization is performed with continuous power control. This performs better than simply quantizing the rates without power control. A more practical implementation of SQPC is SRPQ, in which both rate and power levels are quantized. The performance loss due to power quantization is insignificant when 4–5 bits are used per antenna. Both SQPC and SRPQ show an average total rate close to the closed-loop MIMO capacity if a capacity-approaching scalar code is used per antenna.

Novel heuristics for call admission control in cellular systems

This paper proposes three new heuristic call admission control algorithms for a cellular system that carries a single class of homogeneous traffic and uses fixed channel assignment; the weighted sum scheme, the probability index scheme, and the hybrid control scheme. The weighted sum scheme uses the weighted sum of the number of calls underway in various cells when making the admission decision. The probability index scheme computes a probability index, which reflects the forced-termination probability of a new call arrival, and admits those calls with low probability indices. The hybrid control scheme combines the weighted sum scheme and the probability index scheme. These novel algorithms are compared with three known algorithms: the reservation scheme, the linear weighting scheme, and the distributed admission control scheme. Each of the algorithms attempts to optimize two quality of service (QoS) metrics: the new call blocking probability, which is the probability that a new call is denied access to the system, and the forced-termination probability, which is the probability that a call is terminated prematurely (i.e., prior to call completion). Based on our simulation results, the hybrid control scheme yields the best performance and the weighted sum scheme is second. The reservation scheme does relatively well considering its simplicity.

Rate vs. distortion trade-off for channels with state information

We consider a channel where the sender has access to channel state information and wishes to send both the pure information and a description of the channel state to the receiver. An achievable tradeoff region between pure information rate and state estimation error is proposed for a discrete memoryless channel with an arbitrary state distortion measure.

Simultaneous Communication of Data and State

We consider the problem of transmitting data at rate R over a state dependent channel p(y\x,s) with the state information available at the sender and at the same time conveying the information about the channel state itself to the receiver. The amount of state information that can be learned at the receiver is captured by the mutual information I(Sn;Yn) between the state sequence Sn and the channel output Yn. The optimal tradeoff is characterized between the information transmission rate R and the state uncertainty reduction rate Delta, when the state information is either causally or noncausally available at the sender. This result is closely related and in a sense dual to a recent study by Merhav and Shamai, which solves the problem of masking the state information from the receiver rather than conveying it.

Efficient nonlinear optimizations of queuing systems

We present a systematic treatment of efficient nonlinear optimizations of queuing systems. The suite of formulations uses the computational tool of convex optimization, with fast polynomial time algorithms to obtain the global optimum for these nonlinear problems under various constraints. We first show convexity structures of several queuing systems, including some surprising transition patterns, followed by formulating and showing numerical examples of several convex performance optimizations for both single queues and queuing networks. Blocking probability minimization and service rate allocation through the effective bandwidth approach is also presented.

Tradeoff between message and state information rates

We consider a communication problem where the sender has access to the channel state information and wishes to send both the message information and the state information across the channel. The novelty in characterizing the tradeoff between the message information rate and state estimation error arises primarily because of the instability of encoding and decoding the state information. The tradeoff region is typically difficult to obtain even for a simple channel. We characterize the optimal trade-off for the binary channel Y/sup n/=X/sup n//spl oplus/S/sup n//spl oplus/Z/sup n/, where S/sup n/ is available at the transmitter. We also prove the optimality of the extreme points of the conjectured tradeoff region for the additive Gaussian channel Y/sup n/=X/sup n/+S/sup n/+Z/sup n/, with S/sup n/ i.i.d./spl sim/N(0,Q) known at the encoder and unknown noise Z/sup n/ i.i.d./spl sim/N(0,N).