In this paper we review the most peculiar and interesting information-theoretic and communications features of fading channels. We first describe the statistical models of fading channels which are frequently used in the analysis and design of communication systems. Next, we focus on the information theory of fading channels, by emphasizing capacity as the most important performance measure. Both single-user and multiuser transmission are examined. Further, we describe how the structure of fading channels impacts code design, and finally overview equalization of fading multipath channels.

How much information can be carried over a wireless network with a multiplicity of nodes? What are the optimal strategies for information transmission and cooperation among the nodes? We obtain sharp information theoretic scaling laws under some conditions.

We present a capacity-approaching coding scheme for unicast or multicast over lossy packet networks. In the scheme, all nodes perform coding, but do not wait for a full block of packets to be received before sending out coded packets. Rather, whenever they have a transmission opportunity, they form coded packets with random linear combinations of previously received packets. All coding and decoding operations in the scheme have polynomial complexity. Our analysis of the scheme shows that it is not only capacity-approaching, but that the propagation of packets carrying “innovative ” information follows that of a queueing network where every node acts as a stable M/M/1 queue. We consider networks with both lossy point-to-point and broadcast links, allowing us to model both wireline and wireless packet networks. 1

In wireless data networks the optimal routing of data depends on the link capacities which, in turn, are determined by the allocation of communications resources (such as transmit powers and bandwidths) to the links. The optimal performance of the network can only be achieved by simultaneous optimization of routing and resource allocation. In this paper, we formulate the simultaneous routing and resource allocation problem and exploit problem structure to derive ef£cient solution methods. We use a capacitated multicommodity flow model to describe the data ¤ows in the network. We assume that the capacity of a wireless link is a concave and increasing function of the communications resources allocated to the link, and the communications resources for groups of links are limited. These assumptions allow us to formulate the simultaneous routing and resource allocation problem as a convex optimization problem over the network flow variables and the communications variables. These two sets of variables are coupled only through the link capacity constraints. We exploit this separable structure by dual decomposition. The resulting solution method attains the optimal coordination of data routing in the network layer and resource allocation in the radio control layer via pricing on the link capacities.

We establish an O(n log² n) upper bound on the time for deterministic distributed broadcasting in multi-hop radio networks with unknown topology. This nearly matches the known lower bound of n log n). The fastest previously known algorithm for this problem works in time O(n 3=2 ). Using our broadcasting algorithm, we develop an O(n 3=2 log 2 n) algorithm for gossiping in the same network model.

A new modeling framework is introduced for the analytical study of medium access control (MAC) protocols operating in multihop ad hoc networks. The model takes into account the e#ect of physical-layer parameters on the success of transmissions, the MAC protocol on the likelihood that nodes can access the channnel, and the connectivity of nodes in the network. A key feature of the model is that nodes can be modeled individually, i.e., it allows a per-node setup of many layer-specific parameters. Moreover, no spatial probability distribution or a particular arrangement of nodes is assumed; the model allows the computation of individual (per-node) performance metrics for any given network topology and radio channel model. To show the applicability of the modeling framework, we model multihop ad hoc networks using the IEEE 802.11 distributed coordination function and validate the results from the model with discreteevent simulations in Qualnet. The results show that our model predicts results that are very close to those attained by simulations, and requires seconds to complete compared to several hours of simulation time.

We study the use of channel state information 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 his channel state information (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 CSL The function is called the transmission control scheme. 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 where the transmission control is a function of the size of the network. We obtain expressions for the AST achievable with PITC. For population dependent transmission control, 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 CDMA networks with Linear Minimum Mean Square Error (LMMSE) receivers and Matched Filters (MF) to illustrate the effectiveness of utilizing channel state. It is shown that through the use of channel state, with an...

Consider the following network communication setup, originating in a sensor networking application we refer to as the “sensor reachback ” problem. We have a directed graph G = (V, E), where V = {v0v1...vn} and E ⊆ V × V. If (vi, vj) ∈ E, then node i can send messages to node j over a discrete memoryless channel (Xij, pij(y|x), Yij), of capacity Cij. The channels are independent. Each node vi gets to observe a source of information Ui (i = 0...M), with joint distribution p(U0U1...UM). Our goal is to solve an incast problem in G: nodes exchange messages with their neighbors, and after a finite number of communication rounds, one of the M + 1 nodes (v0 by convention) must have received enough information to reproduce the entire field of observations (U0U1...UM), with arbitrarily small probability of error. In this paper, we prove that such perfect reconstruction is possible if and only if H(US|USc) < i∈S,j∈Sc Cij, for all S ⊆ {0...M}, S � = ∅, 0 ∈ S c. Close examination of our achievability proof reveals that in this setup, Shannon information behaves as a classical network flow, identical in nature to the flow of water in pipes. This “information as flow ” view provides an algorithmic interpretation for our results, among which we

Abstract — In this paper, we study minimal power transmission of bursty sources over wireless channels with constraints on mean queuing delay. The power minimizing schedulers adapt power and rate of transmission based on the queue and channel state. We show that packet scheduling based on queue state can be used to trade queuing delay with transmission power, even on additive white Gaussian noise channels. Our extensive simulations show that small increases in average delay can lead to substantial savings in transmission power, thereby providing another avenue for mobile devices to save on battery power. We propose a lowcomplexity scheduler that has near optimal performance. We also construct a variable rate QAM based transmission scheme to show the benefits of the proposed formulation in a practical communication system. Power optimal schedulers with absolute packet delay constraints are also studied and their performance is evaluated via simulations. Index Terms — Packet scheduling, power control, queuing delay, traffic regulation, wireless channels. I.

The effect of Multipacket Reception (MPR) on stability and delay of slotted ALOHA based random access systems is considered. A general asymmetric MPR model is introduced and the MAC capacity region is specified. An explicit characterization of the ALOHA stability region for the two user system is given. It is shown that the stability region undergoes a phase transition from a concave region to a convex region bounded by lines as the MPR capability improves. It is also shown that after this phase transition, slotted ALOHA is optimal i.e., the ALOHA stability region coincides with the MAC capacity region. Further, it is observed that there is no need for transmission control when ALOHA is optimal i.e., ALOHA with transmission probability one is optimal. These results are extended to a symmetric N > 2 user ALOHA system, where it is shown that for a large class of symmetric MPR channels no transmission control is optimal from a stability viewpoint. This finding suggests that if the physical layer is even reasonably good, there is no need for sophisticated Medium Access Control protocols.