A novel low-complexity wireless neighbor discovery scheme, referred to as sparse orthogonal frequency division multiplexing (sparse-OFDM) is proposed. One area of application is the "Internet of Things" (IoT). The number of devices is very large while every device accesses the network with a small probability, so the number of active devices in a frame is much smaller than the total local device population. Sparse OFDM is a one-shot transmission scheme with low complexity, which exploits both the parallel channel access offered by OFDM and the bursty nature of transmissions. When the transmission delay of each device is an integer number of symbol intervals, analysis and simulation show that sparse OFDM enables successful asynchronous neighbor discovery using a much smaller code length than random access schemes.
Neighbor discovery can be formulated as multiuser detection from the perspective of physical layer processing @cite_14 . Due to the bursty traffic patterns, the number of active devices is typically orders of magnitude smaller than the total local device population. Based on this crucial observation, low-complexity neighbor discovery algorithms inspired by compressed sensing were proposed @cite_19 @cite_3 @cite_11 @cite_9 @cite_20 . These algorithms can reduce the code length by over 50 Noncoherent neighbor discovery based on energy detection can be formulated as the classical group testing problem @cite_24 . By utilizing the sparsity nature, neighbor discovery can be achieved efficiently using a low transmission overhead. A related study applies sparse graph codes to asynchronous group testing @cite_4 , where the required code length is larger than that for our proposed scheme.
@cite_14 @cite_4 @cite_9 @cite_3 @cite_24 @cite_19 @cite_20 @cite_11
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Fast and efficient discovery of all neighboring nodes by a node new to a neighborhood is critical to the deployment of wireless ad hoc networks. Different than the conventional ALOHA-type random access discovery schemes, this paper assumes that all nodes in the neighborhood simultaneously send their unique on-off signatures known to the receive node. In particular, a transmitter does not transmit any energy during an ldquooffrdquo mini-slot in its signature sequence. The received signal can be viewed as the outcome of a sequence of tests over the mini-slots, where the outcome of a test is positive if there is energy at the corresponding mini-slot from at least one neighbor, and negative if none of the neighboring nodes transmits energy during the mini-slot. The neighbor discovery problem is thus equivalent to a classical group testing problem. Two practical and scalable detection algorithms are developed from the group testing viewpoint. Unlike some previous neighbor discovery schemes using coherent multiuser detection, which are difficult to implement due to lack of training, the proposed scheme requires only non-coherent energy detection. The proposed algorithms are shown to achieve faster and more reliable discovery than existing random access schemes. As a supporting primitive of many mobile device applications, neighbor discovery identifies nearby devices so that they can exchange information and collaborate in a peer-to-peer manner. To date, discovery schemes trade a long latency for energy efficiency and require a collaborative duty cycle pattern, and thus they are not suitable for interactive mobile applications where a user is unable to configure others' devices. In this paper, we propose Acc, which serves as an on-demand generic discovery accelerating middleware for many existing neighbor discovery schemes. Acc leverages the discovery capabilities of neighbor devices, supporting both direct and indirect neighbor discoveries. Our evaluations show that Acc-assisted discovery schemes reduce latency by a maximum of 51.8 , compared with the schemes consuming the same amount of energy. We further present and evaluate a Crowd-Alert application where Acc can be employed by taxi drivers to accelerate selection of a direction with fewer competing taxis and more potential passengers, based on a 10 GB dataset of more than 15,000 taxis in a metropolitan area. Abstract This paper studies the problem of neighbor discovery in wireless networks, namely, each node wishes to discover and identify the network interface addresses (NIAs) of those nodes within a single hop. A novel paradigm, called compressed neighbor discovery is proposed, which enables all nodes to simultaneously discover their respective neighborhoods with a single frame of transmission, which is typically of a few thousand symbol epochs. The key technique is to assign each node a unique on–off signature and let all nodes simultaneously transmit their signatures. Despite that the radios are half-duplex, each node observes a superposition of its neighbors’ signatures (partially) through its own off-slots. To identify its neighbors out of a large network address space, each node solves a compressed sensing (or sparse recovery ) problem. Two practical schemes are studied. The first employs random on–off signatures, and each node discovers its neighbors using a noncoherent detection algorithm based on group testing. The second scheme uses on–off signatures based on a deterministic second-order Reed–Muller code, and applies a chirp decoding algorithm. The second scheme needs much lower signal-to-noise ratio (SNR) to achieve the same error performance. The complexity of the chirp decoding algorithm is sub-linear, so that it is in principle scalable to networks with billions of nodes with 48-bit IEEE 802.11 MAC addresses. The compressed neighbor discovery schemes are much more efficient than conventional random-access discovery, where nodes have to retransmit over many frames with random delays to be successfully discovered. Due to slow advance in battery technology, power remains a bottleneck to limit wide applications of mobile ad hoc and wireless sensor networks. Among all extensive studies on minimizing power consumption, neighbor discovery is one of the fundamental components focusing on communication and access. This work surveys research literature on neighbor discovery protocols (NDPs). In general, they can be roughly classified by four underlying principles: randomness, over-half occupation, rotation-resistant intersection, and coprime cycles. The Birthday protocols act as representatives of NDPs using randomness, in which a node decides to listen, transmit, or sleep with probabilities. The original idea of over-half occupation is to be active over at least half of each period, though several refinements have been proposed to decrease its high duty cycle. Methods of rotation-resistant intersection formulate the problem of discovery using combinatorial characteristics of discrete time slots, and guarantee discovery at least once per period. Moreover, neighbor discovery can also be guaranteed within a worst-case bound, as shown by methods adopting coprime cycles. In this paper, we elaborate on these ideas and present several representative protocols, respectively. In particular, we give an integrative analysis of deterministic protocols via a generic framework. A qualitative comparison incorporating multiple criteria and a quantitative evaluation on energy efficiency are also included. Finally, we point out promising research directions towards energy-efficient neighbor discovery. Neighbor discovery plays a crucial role in the formation of wireless sensor networks and mobile networks where the power of sensors (or mobile devices) is constrained. Due to the difficulty of clock synchronization, many asynchronous protocols based on wake-up scheduling have been developed over the years in order to enable timely neighbor discovery between neighboring sensors while saving energy. However, existing protocols are not fine-grained enough to support all heterogeneous battery duty cycles, which can lead to a more rapid deterioration of long-term battery health for those without support. Existing research can be broadly divided into two categories according to their neighbor-discovery techniques — the quorum based protocols and the co-primality based protocols. In this paper, we propose two neighbor discovery protocols, called Hedis and Todis, that optimize the duty cycle granularity of quorum and co-primality based protocols respectively, by enabling the finest-grained control of heterogeneous duty cycles. We compare the two optimal protocols via analytical and simulation results, which show that although the optimal co-primality based protocol (Todis) is simpler in its design, the optimal quorum based protocol (Hedis) has a better performance since it has a lower relative error rate and smaller discovery delay, while still allowing the sensor nodes to wake up at a more infrequent rate. Neighbor discovery is crucial for both wireless sensor networks and mobile computing applications. The crux of the problem is to achieve energy efficiency, which has been demonstrated to be difficult by prior work. In this paper we propose Hello, a generic flexible protocol for neighbor discovery. With an unrestricted parameter, it serves as a generic framework that incorporates existing deterministic protocols. Under the framework, we expose optimal parameters for either symmetric or asymmetric duty cycles, which is the first to our knowledge. As a result, it exhibits great flexibility by adjusting itself to any configuration that best meets application demands. Besides, several techniques are applied to removing redundant discoveries without sacrificing the worst-case latency. We evaluate Hello through extensive simulation and real-world sensor experiments. The results show that Hello is highly energy-efficient under symmetric and asymmetric duty cycles. In particular, it is two times better than the state of the art in terms of the worst-case latency under asymmetric duty cycles. Neighbor discovery is a fundamental problem in wireless networks. In this paper, we study asynchronous neighbor discovery between duty-cycled mobile devices. Each node is duty-cycled, i.e., its radio may only be active for a small fraction of the time. The duty cycles of the nodes can be the same or different, leading to symmetric or asymmetric cases of the neighbor discovery problem. In addition, the setting is asynchronous, i.e., clocks of different nodes may not be synchronized. Most existing studies assume an integer model (where time proceeds in discrete steps); two recent studies break away from this assumption, which allows them to develop significantly more efficient schemes. Our study improves the state-of-the-art in three main fronts. Firstly, we develop a generalized non-integer model (where time is continuous) that permits unified treatment of the assumptions in existing studies. We also provide a reduction that transforms any schedule in the basic integer model to a corresponding schedule in the generalized non-integer model while improving the performance by a factor of two. Applying this reduction, an optimal schedule in the integer model becomes an optimal schedule in the non-integer model. Thirdly, we establish a new family of lower bounds for the best achievable latency guarantee in the non-integer model. They are applicable to both symmetric and asymmetric settings, and encompass the lower bounds for the integer model as special cases. Finally, we develop a novel optimal construction based on Sidon sets for the symmetric setting. Our approach differs from the approaches taken by all existing studies, and provides a new direction for constructing neighbor discovery schedules. In this paper, we design a fast and efficient energy-based and asynchronous neighbor discovery protocol for the Internet of Things (IoT). In our solution, we relax the assumption of frame-level synchronization. We formulate a novel asynchronous group testing scheme and apply it to the neighbor discovery problem. We then show that our proposed scheme is able to detect the set of K active neighbors1 among a network of n nodes with codeword length and decoding complexity of Θ(K log (K) log (n)). Finally, we provide extensive simulation results to verify our theoretical guarantees.