Search

We evaluate the end-to-end delay of a multihop transmission scheme that includes a source, a number of relays, and a destination, in the presence of interferers located according to a Poisson point process. The medium access control (MAC) protocol considered is a combination of TDMA and ALOHA, according to which nodes located a certain number of hops apart are allowed to transmit with a certain probability. Based on an independent transmissions assumption, which decouples the queue evolutions, our analysis provides explicit expressions for the mean end-to-end delay and throughput, as well as scaling laws when the interferer density grows to infinity. If the source always has packets to transmit, we find that full spatial reuse, i.e., ALOHA, is asymptotically delay-optimal, but requires more hops than a TDMA-ALOHA protocol. The results of our analysis have applications in delay-minimizing joint MAC/routing algorithms for networks with randomly located nodes.We simulate a network where sources and relays form a Poisson point process, and each source assembles a route to its destination by selecting the relays closest to the optimal locations. We assess both theoretically and via simulation the sensitivity of the end-to-end delay with respect to imperfect relay placements and route crossings.

From being a scientific curiosity only a few years ago, energy harvesting (EH) is well on its way to becoming a game-changing technology in the field of autonomous wireless networked systems. The promise of long-term, uninterrupted and self-sustainable operation in a diverse array of applications has captured the interest of academia and industry alike. Yet the road to the ultimate network of perpetual communicating devices is plagued with potholes: ambient energy is intermittent and scarce, energy storage capacity is limited, and devices are constrained in size and complexity. In dealing with these challenges, this article will cover recent developments in the design of intelligent energy management policies for EH wireless devices and discuss pressing research questions in this rapidly growing field.

This paper considers a wireless sensor powered by an energy harvesting device, which reports data of varying importance to its receiver. Modeling the ambient energy supply by a two-state Markov chain ("GOOD" and "BAD"), assuming a finite battery capacity constraint, and associating data transmission with a given energy cost, we propose low-complexity transmission policies, that achieve near-optimal performance in terms of the average long-term importance of the reported data. In particular, we derive the performance of the Balanced Policy (BP), which adapts the transmission probability to the harvesting state, such that energy harvesting and consumption are balanced. Our analysis demonstrates that the performance of the BP largely depends on the power-to-depletion, defined as the power that a fully charged battery can supply on average over a BAD period. Numerical results show that the optimal BP achieves near-optimal performance and that a BP which avoids energy overflow further reduces the gap with respect to the globally optimal policy. A heuristic BP, based on the analysis of a system with a deterministic and periodic energy supply, is also proposed, and the parallels between the deterministic system and its stochastic counterpart are discussed.

We design and implement a software-radio system for Superposition Coding (SC), a multiuser transmission scheme that deliberately introduces interference among user signals at the transmitter, using a library of off-the-shelf point-to-point channel codes. We experimentally determine the set of rate-pairs achieved by this transmission scheme under a packet-error constraint. Our results suggest that SC can provide substantial gains in spectral efficiencies over those achieved by orthogonal schemes such as Time Division Multiplexing. Our findings also question the practical utility of the Gaussian approximation for the inter-user interference in Superposition-Coded systems.

The goal of this paper is to explore the benefits of channel diversity in wireless ad hoc networks. Our model is that of a Poisson point process of transmitters, each with a receiver at a given distance. A packet is divided in blocks which are transmitted over different subbands determined by random frequency hopping. At the receiver, a maximum-likelihood decoder is employed to estimate the transmitted packet/codeword. We show that, if L is the Hamming distance of the error correction code and e is a constraint on the packet error probability, the transmission capacity of the network is proportional to e1/L, when e → 0. The proportionality constant depends on the code selection, the packet length, the geometry of the symbol constellation and the number of receive antennas. This result implies that, at the cost of a moderate decoding complexity, large gains can be achieved by a simple interference randomization scheme during packet transmission. We also address practical issues such as channel estimation and power control. We find that reliable channel information can be obtained at the receiver without significant rate loss and demonstrate that channel-inversion power control can increase the transmission capacity.

This article provides an overview on the topic of ad hoc network performance analysis, mainly from a physical layer standpoint. The emphasis of the paper is on how the individual link and network performance can be evaluated in an analytically tractable manner, such that design insights can be obtained and optimization over key parameters is possible. Our model is that of a large random network, where the wireless channel comprises path-loss and fading. Various physical layer factors are taken into account: the multiple-access (MA) scheme, such as direct-sequence (DS) CDMA and frequency-hopping (FH) CDMA; error correction coding such as Reed-Solomon (RS) or convolutional coding; coherent or noncoherent detection; the use of multiple-input, multiple-output (MIMO) techniques to enhance error protection or to increase the transmission rate. The performance of the network is evaluated and optimized in terms of useful metrics such as the network throughput, the information efficiency and the transmission capacity.

Frequency hopping (FH) combined with coding is a popular technique in wireless communication applications. Motivated by the commercial system outlined in [1], this paper investigates the performance of a coherent FH multiple access (FH-MA) cellular system, where hopping patterns are constructed from latin squares. Some of the patterns carry pilot symbols, which the users track to estimate the channel on the data patterns and perform coherent detection. The latin squares construction enables us to analytically evaluate the bit error probability (BEP) over each data pattern, when convolutional codes are employed for error protection. The focus of our work is to precisely determine the effect that frequency and interference diversity, ensuing from FH, have on the coded performance. Regarding frequency diversity, it is shown that the performance can vary widely for different latin squares. Moreover, under pilot-assisted channel estimation, a performance tradeoff is observed, as an increasing frequency selectivity results in more diversity, but also more inaccurate channel state information. With respect to interference diversity, we analyze the performance when the interference power variations are perfectly known or ignored by the receiver. Our results confirm that interference tracking is important in harnessing the error correcting power of convolutional coding.

We propose a theoretical framework to evaluate the expected throughput of underwater networks over an ensemble of node topologies and propagation environments. The analysis is based on the assumptions that the transmitters are spatially distributed according to a Poisson point process, and that the channel follows a Rayleigh fading distribution, with a mean that is determined by spreading loss and frequency-dependent absorption. We evaluate the probability of a successful transmission, i.e., the probability that the signal-to-interference-and-noise ratio at the typical receiver is greater than a given threshold, and determine the maximum network throughput density over the transmitter density and the operating frequency. The theoretical results are validated using a realistic underwater channel simulator based on ray tracing. It is demonstrated that, for a number of practical scenarios, the theoretical and simulated throughput match provided that the spreading-loss exponent is appropriately fitted to the simulation scenario. Overall, the proposed framework provides easy-to-obtain network throughput results, which can be used as a complement or an alternative to time-costly, deployment-dependent network simulations.

We analyze the performance of an interference-aware opportunistic relay selection protocol for multi-hop line networks which is based on the following simple rule: a node always transmits if it has a packet, except when its successive node on the line is transmitting. We derive analytically the saturation throughput and the end-to-end delay for two and three hop networks, and present simulation results for higher numbers of hops. In the case of three hops, we determine the throughput-optimal relay positions.