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In this paper, we analyze optimal (in space and time) adaptive power transmission policies for fading channels when the channel-state information (CSI) at the transmitter (CSIT) and the receiver (CSIR) is available. The transmitter has a long-term (time) average power constraint. There can be multiple antennas at the transmitter and at the receiver. The channel experiences Rayleigh fading. We consider beamforming and space-time coded systems with perfect/imperfect CSIT and CSIR. The performance measure is the bit error rate (BER). We show that in both coded and uncoded systems, our power allocation policy provides exponential diversity order if perfect CSIT is available. We also show that, if the quality of CSIT degrades then the exponential diversity is retained in the low SNR region but we get only polynomial diversity in the high SNR region. Another interesting conclusion is that in case of imperfect CSIT and CSIR, knowledge of CSIT at the receiver is very important. Finally, for the optimal power control policy of the uncoded system we find the error-exponents which provide the rate versus diversity-order tradeoff for this policy. This tradeoff is of an entirely different nature than the well-known Zheng-Tse tradeoff.

We consider the problem of quickest detection of an intrusion using a sensor network, keeping only a minimal number of sensors active. By using a minimal number of sensor devices, we ensure that the energy expenditure for sensing, computation and communication is minimized (and the lifetime of the network is maximized). We model the intrusion detection (or change detection) problem as a Markov decision process (MDP). Based on the theory of MDP, we develop the following closed loop sleep/wake scheduling algorithms:1) optimal control of M k+1 , the number of sensors in the wake state in time slot k + 1, 2) optimal control of q k+1 , the probability of a sensor in the wake state in time slot k + 1, and an open loop sleep/wake scheduling algorithm which 3) computes q, the optimal probability of a sensor in the wake state (which does not vary with time), based on the sensor observations obtained until time slot k.Our results show that an optimum closed loop control on M k+1 significantly decreases the cost compared to keeping any number of sensors active all the time. Also, among the three algorithms described, we observe that the total cost is minimum for the optimum control on M k+1 and is maximum for the optimum open loop control on q. Summary of contributions:We summarize the main contributions of this paper below.(i) We model the problem of quickest change (intrusion) detection by using a minimal number of observations in the Bayesian framework as a Markov decision process (MDP) that captures 1) the cost due to false alarm, 2) the cost due to the detection delay, and 3) the cost per observation per sensor in the network. (ii) We derive the following closed loop scheduling algorithm This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the IEEE INFOCOM 2008 proceedings. 978-1-4244-2026-1/08/$25.00

[1] Before the onset of the south Asian summer monsoon, sea surface temperature (SST) of the north Indian Ocean warms to 30-32°C. Climatological mean mixed layer depth in spring (March-May) is 10-20 m, and net surface heat flux (Q net ) is 80-100 W m À2 into the ocean. Previous work suggests that observed spring SST warming is small mainly because of (1) penetrative flux of solar radiation through the base of the mixed layer (Q pen ) and (2) advective cooling by upper ocean currents. We estimate the role of these two processes in SST evolution from a two-week Arabian Sea Monsoon Experiment process experiment in April-May 2005 in the southeastern Arabian Sea. The upper ocean is stratified by salinity and temperature, and mixed layer depth is shallow (6 to 12 m). Current speed at 2 m depth is high even under light winds. Currents within the mixed layer are quite distinct from those at 25 m. On subseasonal scales, SST warming is followed by rapid cooling, although the ocean gains heat at the surface: Q net is about 105 W m À2 in the warming phase and 25 W m À2 in the cooling phase; penetrative loss Q pen is 80 W m À2 and 70 W m À2 . In the warming phase, SST rises mainly because of heat absorbed within the mixed layer, i.e., Q net minus Q pen ; Q pen reduces the rate of SST warming by a factor of 3. In the second phase, SST cools rapidly because (1) Q pen is larger than Q net and (2) advective cooling is $85 W m À2 . A calculation using time-averaged heat fluxes and mixed layer depth suggests that diurnal variability of fluxes and upper ocean stratification tends to warm SST on subseasonal timescale. Buoy and satellite data suggest that a typical premonsoon intraseasonal cooling event occurs under clear skies when the ocean is gaining heat through the surface. In this respect, premonsoon SST cooling in the north Indian Ocean is different from that due to the Madden-Julian oscillation or monsoon intraseasonal oscillation.

Abstract-In this paper, we analyze the performance of various layers of the general packet radio service (GPRS) protocol stack, including radio link control/medium-access control (RLC/MAC) layer and logical link-control (LLC) layer on the uplink. In the GPRS MAC protocol, several time-slotted uplink radio-frequency channels are shared by the mobiles on a request-reservation-based multiple-access scheme. Using the theory of Markov chains, we derive expressions for the average throughput and delay performance of the GPRS MAC protocol. We evaluate the performance of the RLC layer (in acknowledged mode) using block-level retransmission (BLR), as defined in the current GPRS standard, and compare it with that of using slot-level retransmission (SLR). We show that SLR at the RLC layer performs significantly better than the BLR, particularly when the channel-error rates are moderate to high. We further investigate the choice of parameters (e.g., number of retransmission attempts) for the automatic repeat request schemes at the RLC and LLC layers. Our results show that it is more beneficial to do error recovery by allowing more retransmission attempts at the RLC layer than at the LLC layer. We also evaluate the performance of transmission-control protocol with BLR and SLR at the RLC layer.Index Terms-Automatic repeat request (ARQ), block-level retransmission (BLR), general packet radio service (GPRS), logical link control (LLC), radio link control/medium-access control (RLC/MAC), slot-level retransmission (SLR), transmission-control protocol (TCP).