Srihari Adireddy

Sensor networks with mobile agents

Architecture for large scale low power sensor network is proposed. Referred to as sensor networks with mobile agents (SENMA), SENMA exploit node redundancies by introducing mobile agents that communicate opportunistically with a large field of sensors. The addition of mobile agents shifts computationally intensive tasks away from primitive sensors to more powerful mobile agents, which enables energy efficient operations under severely limited power constraints. An opportunistic ALOHA random access coupled with a direct sequence spread spectrum physical layer is proposed. A comparison of SENMA with a flat ad hoc sensor network shows a substantial gain in energy efficiency.

Optimal placement of training for frequency-selective block-fading channels

The problem of placing training symbols optimally for orthogonal frequency-division multiplexing (OFDM) and single-carrier systems is considered. The channel is assumed to be quasi-static with a finite impulse response of length (L + 1) samples. Under the assumptions that neither the transmitter nor the receiver knows the channel, and that the receiver forms a minimum mean square error (MMSE) channel estimate based on training symbols only, training is optimized by maximizing a tight lower bound on the ergodic training-based independent and identically distributed (i.i.d.) capacity. For OFDM systems, it is shown that the lower bound is maximized by placing the known symbols periodically in frequency. For single-carrier systems, under the assumption that the training symbols are placed in clusters of length /spl alpha/ /spl ges/ (2L + 1), it is shown that the lower bound is maximized by a family of placement schemes called QPP-/spl alpha/, where QPP stands for quasi-periodic placement. These placement schemes are formed by grouping the known symbols into as many clusters as possible and then placing these clusters periodically in the packet. For both OFDM and single-carrier systems, the optimum energy tradeoff between training and data is also obtained.

Exploiting decentralized channel state information for random access

We study the use of channel state information (CSI) for random access in fading channels. Traditionally, random access protocols have been designed by assuming simple models for the physical layer where all users are symmetric, and there is no notion of channel state. We introduce a reception model that takes into account the channel states of various users. Under the assumption that each user has access to its CSI, we propose a variant of Slotted ALOHA protocol for medium access control, where the transmission probability is allowed to be a function of the CSI. The function is called the transmission control. Assuming the finite user infinite buffer model we derive expressions for the maximum stable throughput of the system. We introduce the notion of asymptotic stable throughput (AST) that is the maximum stable throughput as the number of users goes to infinity. We consider two types of transmission control, namely, population-independent transmission control (PITC), where the transmission control is not a function of the size of the network and population-dependent transmission control (PDTC), where the transmission control is a function of the size of the network. We obtain expressions for the AST achievable with PITC. For PDTC, we introduce a particular transmission control that can potentially lead to significant gains in AST. For both PITC and PDTC, we show that the effect of transmission control is equivalent to changing the probability distribution of the channel state. The theory is then applied to code-division multiple-access (CDMA) networks with linear minimum mean-square error (LMMSE) receivers and matched filters (MF) to illustrate the effectiveness of using channel state. It is shown that through the use of channel state, with arbitrarily small power, it is possible to achieve an AST that is lower-bounded by the spreading gain of the network. This result has implications for the reachback problem in large sensor networks.

Sensor networks with mobile access: optimal random access and coding

We consider random access and coding schemes for sensor networks with mobile access (SENMA). Using an orthogonal code-division multiple access (CDMA) as the physical layer, an opportunistic ALOHA (O-ALOHA) protocol that utilizes channel state information is proposed. Under the packet capture model and using the asymptotic throughput as the performance metric, we show that O-ALOHA approaches the throughput equal to the spreading gain with an arbitrarily small power at each sensor. This result implies that O-ALOHA is close to the optimal centralized scheduling scheme for the orthogonal CDMA networks. When side information such as location is available, the transmission control is modified to incorporate either the distribution or the actual realization of the side information. Convergence of the throughput with respect to the size of the network is analyzed. For networks allowing sensor collaborations, we combine coding with random access by proposing two coded random access schemes: spreading code dependent and independent transmissions. In the low rate regime, the spreading code independent transmission has a larger random coding exponent (therefore, faster decay of error probability) than that of the spreading code dependent transmission. On the other hand, the spreading code dependent transmission gives higher achievable rate.

Opportunistic ALOHA and cross layer design for sensor networks

We propose a novel distributed medium access control scheme called opportunistic ALOHA for reachback in sensor networks with mobile agents. Each sensor transmits its information with a probability that is a function of its channel state (propagation channel gain). This function called transmission control is then designed under the assumption that orthogonal CDMA is employed to transmit information. The gains achieved in the throughput by use of transmission control are analyzed and evaluated numerically. The variation of the average number of transmitting users with distance from the collecting agent is analyzed. The proposed reachback protocol can be used in a variety of sensor network applications. We end by giving two examples of how the reachback protocol can be used by the sensor network to transmit information reliably to the collecting agent. The maximum rate at which the information can be reliably transmitted with the proposed schemes is evaluated as a function of the performance parameters of the reachback protocol.

Detection with embedded known symbols: optimal symbol placement and equalization

The detection of a data sequence with embedded known symbols is considered. For a class of symbol-by-symbol decision feedback receivers, known symbol distributions optimal with respect to the criterion of average mean square error (A-MSE) are presented. Optimal design of the decision feedback receiver is also obtained. Simulation results show that, compared to the performance with conventional symbol placement strategy, considerable gain can be obtained by the joint optimization of symbol placement and equalizer.

Optimal embedding of known symbols for OFDM

The problem of placing known symbols optimally for OFDM is considered. The channel is assumed to be quasi-static with a finite impulse response. Under the assumption that neither the transmitter and receiver know the channel, we optimize the training by maximizing a lower bound of the mutual information. It is shown that the lower bound is maximized by placing the known symbols periodically. Optimum energy trade-off between the training and the data is also obtained and illustrated through simulation.

Optimal placement of known symbols for slowly varying frequency-selective channels

The problem of placing known symbols in a data stream for a slowly varying frequency-selective channel is considered from an information-theoretic perspective. Given the amount of redundancy associated with known symbols, placement schemes that minimize the outage probability are derived by assuming that the transmitted codewords consist of packets that are constrained to have the same known symbol placement. Under the assumption that each known symbol cluster is at least as large as /spl alpha/ /spl ges/ 2L + 1 (where L is the channel order), we show that the optimal placement is obtained by arranging the known symbols into as many clusters as possible and placing them such that the unknown symbol blocks are as equal as possible. It is shown that the optimal placement of known symbol clusters does not depend on the probability density of the channel. Numerical examples are used to illustrate the ideas and potential gains of using optimal known symbol placement.

Medium access control with channel state information for large sensor networks

Traditionally, random access protocols have been designed and studied by assuming simple models for the physical layer. We introduce a reception model that incorporates the channel states of the transmitting users and allows for multiple simultaneous successes. We assume that each user has access to his channel state and propose a variant of the Slotted ALOHA protocol for medium access where the transmit probability is chosen as a function of the channel state. We introduce the notion of asymptotic stable throughput and characterize the achievable asymptotic stable throughput through the use of channel state information. As an example, we consider the application of the results to sensor networks.

Sensitivity and Coding of Opportunistic ALOHA in Sensor Networks with Mobile Access

We consider a distributed medium access protocol, Opportunistic ALOHA, for reachback in sensor networks with mobile access points (AP). We briefly discuss some properties of the protocol, like throughput and transmission control for an orthogonal CDMA physical layer. We then consider the incorporation of necessary side information like location into the transmission control and numerically demonstrate the loss in throughput in the absence of such information. Through simulations, we discuss the robustness and sensitivity of the protocol under various modeling errors and propose strategies to allow for errors in estimation of some parameters without reduction in the throughput. For networks, where the sensors are allowed to collaborate, we consider three coding schemes for reliable transmission: spreading code independent, spreading code dependent transmission and coding across sensors. These schemes are compared in terms of achievable rates and random coding error exponents. The coding across sensors scheme has comparable achievable rates to the spreading code dependent scheme, but requires the additional transmission of sensor ID. However, the scheme does not require the mobile AP to send data through the beacon unlike the other two schemes. The use of these coding schemes to overcome sensitivity is demonstrated through simulations.