Vignesh Sethuraman

Capacity per unit energy of fading channels with a peak constraint

A discrete-time single-user scalar channel with temporally correlated Rayleigh fading is analyzed. There is no side information at the transmitter or the receiver. A simple expression is given for the capacity per unit energy, in the presence of a peak constraint. The simple formula of Verdu/spl acute/ for capacity per unit cost is adapted to a channel with memory, and is used in the proof. In addition to bounding the capacity of a channel with correlated fading, the result gives some insight into the relationship between the correlation in the fading process and the channel capacity. The results are extended to a channel with side information, showing that the capacity per unit energy is one nat per joule, independently of the peak power constraint. A continuous-time version of the model is also considered. The capacity per unit energy subject to a peak constraint (but no bandwidth constraint) is given by an expression similar to that for discrete time, and is evaluated for Gauss-Markov and Clarke fading channels.

Low-SNR Capacity of Noncoherent Fading Channels

Discrete-time Rayleigh-fading single-input single-output (SISO) and multiple-input multiple-output (MIMO) channels are considered, with no channel state information at the transmitter or the receiver. The fading is assumed to be stationary and correlated in time, but independent from antenna to antenna. Peak-power and average-power constraints are imposed on the transmit antennas. For MIMO channels, these constraints are either imposed on the sum over antennas, or on each individual antenna. For SISO channels and MIMO channels with sum power constraints, the asymptotic capacity as the peak signal-to-noise ratio (SNR) goes to zero is identified; for MIMO channels with individual power constraints, this asymptotic capacity is obtained for a class of channels called transmit separable channels. The results for MIMO channels with individual power constraints are carried over to SISO channels with delay spread (i.e., frequency-selective fading).

Comments on "Bit-interleaved coded modulation"

Caire, Taricco, and Biglieri presented a detailed analysis of bit-interleaved coded modulation (BICM), a simple and popular technique used to improve system performance, especially in the context of fading channels. They derived an upper bound to the probability of error, called the expurgated bound. In this correspondence, the proof of the expurgated bound is shown to be flawed. A new upper bound is also derived. It is not known whether the original expurgated bound is valid for the important special case of square QAM with Gray labeling, but the new bound is very close to, and slightly tighter than, the original bound for a numerical example.

Low SNR Capacity of Fading Channels with Peak and Average Power Constraints

Flat-fading channels that are correlated in time are considered under peak and average power constraints. For discrete-time channels, a new upper bound on the capacity per unit time is derived. A low SNR analysis of a full-scattering vector channel is used to derive a complimentary lower bound. Together, these bounds allow us to identify the exact scaling of channel capacity for a fixed peak to average ratio, as the average power converges to zero. The upper bound is also asymptotically tight as the average power converges to zero for a fixed peak power. For a continuous time infinite bandwidth channel, Viterbi identified the capacity for M-FSK modulation. Recently, Zhang and Laneman showed that the capacity can be achieved with non-bursty signaling (QPSK). An additional contribution of this paper is to obtain similar results under peak and average power constraints

Capacity bounds for noncoherent fading channels with a peak constraint

A discrete-time single-user channel with temporally correlated Rayleigh fading is considered. Neither the transmitter nor the receiver has channel side information (CSI), and both peak and average power constraints are placed on the inputs. Two lower bounds to the capacity are presented. One is motivated by the technique of decision feedback decoding. The other is related to the information rate with side information present, minus a penalty term to account for the information about the channel that is learned at the receiver. The second lower bound is a slight variation of a bound of Shamai and Marzetta. The bounds are compared numerically to two upper bounds for a channel with Gauss Markov Rayleigh fading. One upper bound is the capacity for complete CSI, with the peak constraint ignored, and the other is based on the capacity per unit energy. In general, the gap between the upper and lower bounds depends on the channel memory, but is quite small for low SNR

First Order Adaptive IIR Filter for CQI Prediction in HSDPA

In this work, we consider channel quality indicator (CQI) prediction for High Speed Downlink Packet Access (HSDPA). In HSDPA systems, there is a delay of about 3 subframe associated with the application of CQI feedback. Traditional FIR filter based predictors such as Least-Mean-Squares (LMS) and Recursive-Least-Squares (RLS) typically come with high computational complexity. We consider a first order adaptive IIR alternative with substantially lower complexity while attaining the same level of accuracy. By minimizing the mean squared error (MSE), we derive an exact gradient descent algorithm as well as two pseudolinear regression algorithms. The convergence rates and the convergence conditions are then established. Simulation results show that the proposed adaptive IIR filters combat both feedback delay as well as estimation error and provide up to 25\% HSDPA throughput improvement.

Low SNR Capacity of Fading Channels -MIMO and Delay Spread

Discrete-time Rayleigh fading multiple-input multiple-output (MIMO) channels are considered, with no channel state information at the transmitter and receiver. The fading is assumed to be correlated in time and independent from antenna to antenna. Peak and average transmit power constraints are imposed, either on the sum over antennas, or on each individual antenna. In both cases, an upper bound and an asymptotic lower bound, as the signal-to-noise ratio approaches zero, on the channel capacity are presented. The limit of normalized capacity is identified under the sum power constraints, and, for a subclass of channels, for individual power constraints. These results carry over to a SISO channel with delay spread (i.e. frequency selective fading).

Throughput Optimization in High Speed Downlink Packet Access (HSDPA)

In this paper, we investigate throughput optimization in High Speed Downlink Packet Access (HSDPA). Specifically, we propose offline and online algorithms for adjusting the Channel Quality Indicator (CQI) used by the network to schedule data transmission. In the offline algorithm, a given target BLER is achieved by adjusting CQI based on ACK/NAK history. By sweeping through different target BLERs, we can find the throughput optimal BLER offline. This algorithm could be used not only to optimize throughput but also to enable fair resource allocation among mobile users in HSDPA. In the online algorithm, the CQI offset is adapted using an estimated short term throughput gradient without specifying a target BLER. An adaptive stepsize mechanism is proposed to track temporal variation of the environment. We investigate convergence behavior of both algorithms. Simulation results show that the proposed offline algorithm can achieve the given target BLER with good accuracy. Both algorithms yield up to 30% HSDPA throughput improvement over that with 10% target BLER.