In LoRa (Long Range), when a collision occurs in the network, each end-device has to retransmit its colliding frame, which reduces the throughput, and increases the energy consumption of the end-devices and the delay of the frames. In this paper, we propose an algorithm to decode colliding synchronized LoRa signals and thus improve the overall performance of the network. Indeed, we use successive transmissions of bitmaps by the end-devices to determine the correct symbols of each colliding frame, instead of retransmitting the whole frames. Simulation results show that our algorithm is able to significantly improve the overall throughput of LoRaWAN, and to decrease the energy consumption and the delay of the transmitters.
In @cite_8 , the authors have proposed two algorithms to decode some cases of collisions of LoRa signals. The first algorithm is used when superposed signals are slightly desynchronized, and the second algorithm is used when superposed signals are completely synchronized. Authors observe that the first algorithm is able to significantly increase the throughput, by decoding many collisions of two signals, and some collisions of three signals. On the other side, the second algorithm has improved the throughput, by decoding both signals when exactly two signals are colliding. The second algorithm requests any of the two colliding transmitters to retransmit its frame. Hence, when one frame is retransmitted, the algorithm is able to decode it, and to deduce the other colliding frame by elimination. The authors have considered the case of only two synchronized signals. In this paper, we are improving this by reducing the amount of data retransmitted, and by considering two or more synchronized signals.
@cite_8
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Long-range low-power wireless communications, such as LoRa, are used in many IoT and environmental monitoring applications. They typically increase the communication range to several kilometers, at the cost of reducing the bitrate to a few bits per seconds. Collisions further reduce the performance of these communications. In this paper, we propose two algorithms to decode colliding signals: one algorithm requires the transmitters to be slightly desynchronized, and the other requires the transmitters to be synchronized. To do so, we use the timing information to match the correct symbols to the correct transmitters. We show that our algorithms are able to significantly improve the overall throughput of LoRa. We address several implementation issues related to multi-user physical layer network coding, in which the symbol-synchronous collision of an arbitrary number of signals is decoded. In particular we study the effect of frequency and phase offsets, the imperfect symbol synchronization of the colliding signals and the estimation of frequency and phase offsets and amplitudes in the presence of more than two colliding signals. This paper presents CRESM, a novel collision resolution method for decoding collided packets in random-access wireless networks. In a collision, overlapping signals from several sources are received simultaneously at a receiver. CRESM exploits symbol misalignment among the overlapping signals to recover the individual packets. CRESM can be adopted in 802.11 networks without modification of the transmitter design; only a simple DSP technique is needed at the receiver to decode the overlapping signals. Our simulations indicate that CRESM has better BER performance than the simplistic Successive Interference Cancellation (SIC) technique that treats interference as noise, for almost all SNR regimes. The implication of CRESM for random-access networking is significant: in general, using CRESM to resolve collisions of up to n packets, network throughput can be boosted by more than n times if the transmitters are allowed to transmit more aggressively in the MAC protocol. Decode-and-forward physical layer network coding is one of the most high-performing ideas for wireless network coding. However, all the present schemes work under rather ideal assumptions, such as synchronous reception of the colliding signals. This paper proposes a simple and practical system which removes many of the assumptions made in the past and also designs a soft-output demodulator for this type of network coding. An asynchronous position measurement system is proposed for indoor localization in this paper. The demonstrated system consists of a UWB transmitter and several energy detection receivers whose positions are known. The position measurement process starts with the locator emitting a UWB pulse. Upon arrival, the pulse is amplified and retransmitted by the target to be located. Signals from both the locator and the target are captured by the receivers. No synchronization mechanism is implemented. Instead, the proposed system measures the differential TOA between the direct coupling signal of the locator and the target signal. Together with the knowledge of the locator transmitter and receiver positions, the absolute range that the pulse travels can be calculated. The sum of transmitter-target range and target-receiver range defines an ellipse and the target resides on the intersections of several such ellipses. It is shown via the Cramer-Rao lower bound that the absolute-range-based elliptical localization is potentially more accurate than the relative-range-based hyperbolic localization. Our proposed system is able to achieve positioning error bound comparable to synchronous absolute-range-based localization systems while eliminating the cost of synchronization. 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. This paper was originally distributed informally as ARPA Satellite System Note 8 on June 26, 1972. The paper is an important one and since its initial limited distribution, the paper has been frequently referenced in the open literature, but the paper itself has been unavailable in the open literature. Publication here is meant to correct the previous gap in the literature. As the paper was originally distributed only to other researchers intimately familiar with the area covered by the paper, the paper makes few concessions to the reader along the lines of introductory or tutorial material. Therefore, a bit of background material follows. ALOHA packet systems were originally described by Abramson ("The ALOHA System--Another Alternative for Computer Communication," Proceedings of the AFIPS Fall Joint Computer Conference, Vol. 37, 1970, pp. 281--285). In an ALOHA a single broadcast channel is shared by a number of communicating devices. In the version originally described by Abramson, every device transmits its packets independent of any other device or any specific time. That is, the device transmits the whole packet at a random point in time; the device then times out for receiving an acknowledgment. If an acknowledgment is not received, it is assumed that a collision occured with a packet transmitted by some other device and the packet is retransmitted after a random additional waiting time (to avoid repeated collisions). Under a certain set of assumptions, Abramson showed that the effective capacity of such a channel is 1 (2e). Roberts in the present paper investigates methods of increasing the effective channel capacity of such a channel. One method he proposes to gain in capacity is to consider the channel to be slotted into segments of time whose duration is equal to the packet transmission time, and to require the devices to begin a packet transmission at the beginning of a time slot. Another method Roberts proposes to gain in capacity is to take advantage of the fact that even though packets from two devices collide in the channel (i.e., they are transmitted so they pass through the channel at overlapping times), it may be possible for the receiver(s) to "capture" the signal of one of the transmitters, and thus correctly receive one of the conflicting packets, if one of the transmitters has a sufficiently greater signal than the other. Roberts considers the cases of both satellite and ground radio channels. Compressive Sensing (CS) allows the highly efficient acquisition of many signals that could be difficult to capture or encode using conventional methods. From a relatively small number of random measurements, a high-dimensional signal can be recovered if it has a sparse or near-sparse representation in a basis known to the decoder. In this paper, we consider the application of CS to video signals in order to lessen the sensing and compression burdens in single- and multi-camera imaging systems. In standard video compression, motion compensation and estimation techniques have led to improved sparse representations that are more easily compressible; we adapt these techniques for the problem of CS recovery. Using a coarse-to-fine reconstruction algorithm, we alternate between the tasks of motion estimation and motion-compensated wavelet-domain signal recovery. We demonstrate that our algorithm allows the recovery of video sequences from fewer measurements than either frame-by-frame or inter-frame difference recovery methods. Time synchronization of video sequences in a multicamera system is necessary for successfully analyzing the acquired visual information. Even if synchronization is established, its quality may deteriorate over time due to a variety of reasons, most notably frame dropping. Consequently, synchronization must be actively maintained. This paper presents a method for online synchronization that relies only on the video sequences. We introduce a novel definition of low level temporal signals computed from epipolar lines. The spatial matching of two such temporal signals is given by the fundamental matrix. Thus, no pixel correspondence is required, bypassing the problem of correspondence changes in the presence of motion. The synchronization is determined from registration of the temporal signals. We consider general video data with substantial movement in the scene, for which high level information may be hard to extract from each individual camera (e.g., computing trajectories in crowded scenes). Furthermore, a trivial correspondence between the sequences is not assumed to exist. The method is online and can be used to resynchronize video sequences every few seconds, with only a small delay. Experiments on indoor and outdoor sequences demonstrate the effectiveness of the method. We address the minimum-energy broadcast problem under the assumption that nodes beyond the nominal range of a transmitter can collect the energy of unreliably received overheard signals. As a message is forwarded through the network, a node will have multiple opportunities to reliably receive the message by collecting energy during each retransmission. We refer to this cooperative strategy as accumulative broadcast. We seek to employ accumulative broadcast in a large scale loosely synchronized, low-power network. Therefore, we focus on distributed network layer approaches for accumulative broadcast in which loosely synchronized nodes use only local information. To further simplify the system architecture, we assume that nodes forward only reliably decoded messages. Under these assumptions, we formulate the minimum-energy accumulative broadcast problem. We present a solution employing two subproblems. First, we identify the ordering in which nodes should transmit. Second, we determine the optimum power levels for that ordering. While the second subproblem can be solved by means of linear programming, the ordering subproblem is found to be NP-complete. We devise a heuristic algorithm to find a good ordering. Simulation results show the performance of the algorithm to be close to optimum and a significant improvement over the well known BIP algorithm for constructing energy-efficient broadcast trees. We then formulate a distributed version of the accumulative broadcast algorithm that uses only local information at the nodes and has performance close to its centralized counterpart. Two new schemes are proposed for collision resolution in slotted ALOHA networks based on multi-user physical-layer network coding (MU PHY NC). In the proposed random access schemes, a collision of a generic number of packets can be recovered decoding the XOR of the original messages, such that the signal resulting from the collision is exploited rather than being discarded. Two different schemes that differ in terms of the amount of control information that needs to be transmitted from the access point, are studied. We investigate strategies for user cooperation in the uplink of a synchronous direct-sequence code-division multiple-access (DS CDMA) network employing nonorthogonal spreading codes and analyze their performance. We consider two repetition-based relay schemes: decode-and-forward (DAF) and amplify-and-forward (AAF). Focusing on the use of linear multiuser detectors, we first present cooperation strategies, i.e., signal processing at both the relay nodes and the base station (BS), under the assumption of perfectly known channel conditions of all links; then, we consider the more practical scenario where relays and BS have only partial information about the system parameters, which requires blind multiuser detection methods. We provide performance analysis of the proposed detection strategies in terms of the (asymptotic) signal-to-(interference plus noise) ratio and the bit error rate, and we show that AAF achieves a full second-order diversity when a minimum mean-square-error detector is employed at both the relay side and the BS. A simple, yet effective, partner selection algorithm is also presented. Finally, a thorough performance assessment is undertaken to study the impact of the multiple-access interference on the proposed cooperative strategies under different scenarios and system assumptions Compressive sensing (CS) is an emerging field based on the revelation that a small collection of linear projections of a sparse signal contains enough information for stable, sub-Nyquist signal acquisition. When a statistical characterization of the signal is available, Bayesian inference can complement conventional CS methods based on linear programming or greedy algorithms. We perform asymptotically optimal Bayesian inference using belief propagation (BP) decoding, which represents the CS encoding matrix as a graphical model. Fast computation is obtained by reducing the size of the graphical model with sparse encoding matrices. To decode a length-N signal containing K large coefficients, our CS-BP decoding algorithm uses O(K log(N)) measurements and O(N log2(N)) computation. Finally, although we focus on a two-state mixture Gaussian model, CS-BP is easily adapted to other signal models. We consider a cooperative wireless network in the presence of one or more eavesdroppers, and exploit node cooperation for achieving physical (PHY) layer based security. Two different cooperation schemes are considered. In the first scheme, cooperating nodes retransmit a weighted version of the source signal in a decode-and-forward (DF) fashion. In the second scheme, referred to as cooperative jamming (CJ), while the source is transmitting, cooperating nodes transmit weighted noise to confound the eavesdropper. We investigate two objectives: i) maximization of the achievable secrecy rate subject to a total power constraint and ii) minimization of the total power transmit power under a secrecy rate constraint. For the first design objective, we obtain the exact solution for the DF scheme for the case of a single or multiple eavasdroppers, while for the CJ scheme with a single eavesdropper we reduce the multivariate problem to a problem of one variable. For the second design objective, existing work introduces additional constraints in order to reduce the degree of difficulty, thus resulting in suboptimal solutions. Our work raises those constraints, and obtains either an analytical solution for the DF scheme with a single eavesdropper, or reduces the multivariate problem to a problem of one variable for the CJ scheme with a single eavesdropper. Numerical results are presented to illustrate the proposed results and compare them to existing work. We study the problem of waking up a collection of @math processors connected by a multihop ad hoc ratio network with unknown topology, no access to a global clock, and no collision detection mechanism available. Each node in the network either wakes up spontaneously or gets activated by receiving a wake-up signal from another node. All active nodes transmit the wake-up signals according to a given protocol @math . The running time of @math is the number of steps counted from the first spontaneous wake-up until all nodes become activated. We provide two protocols for this problem. The first one is a deterministic protocol with running time @math . Our protocol is based on a novel concept of a shift-tolerant selector to which we refer as a (radio) synchronizer. The second protocol is randomized, and its expected running time is @math , where @math is the diameter of the network. Subsequently we show how to employ our wake-up protocols to solve two other communication primitives: leader election and clock synchronization. The physical (or SINR) model of wireless communication is more intricate than radio networks and still not well understood. If two neighbors of a node are transmitting, the node may be able to decode one of the transmissions, depending on the relative nearness of the transmitters. Thus, even the lack of proper reception carries indirect information. We explore here the power of such indirect signaling to infer the approximate topology of the network. In particular, we obtain a polylogarithmic time algorithm to compute a backbone: a set of nodes of constant density that dominates every e-neighborhood. A backbone has wide utility for information dissemination, functioning as a sparse spanner. It also leads to fast broadcast, running in O(Diameter) time after a polylogarithmic precomputation, which previously was only known when additional features such as carrier sense, collision detection, geometric coordinates, or power control were available. A first aspect of the invention is a method of transmitting data packets over a transmission channel shared by a plurality of users, based on the time and or frequency diversity slotted Aloha technique, in which at least two replicas of each packet to be transmitted are sent over said transmission channel, wherein each replica transports signaling information enabling the other replica(s) of the same packet to be located in the time and or frequency domain. A second aspect of the invention is a method of recovering packets in the receiver, the method exploiting said signaling information to execute an interference cancellation algorithm for recovering packets corrupted by collisions caused by access conflicts. Other aspects of the invention are a transmitter equipment and a receiver packet recovery equipment adapted to use said methods. Increased attention has been drawn to machine type communication (MTC) lately, which represents important extension for user functionality in today's technologies, as well as an important potential for marketing expansion. GERAN studies over MTC has mainly focused on applications requiring low throughput and wide coverage such as smart meter, which could cause some impacts over normal data users if operating in a synchronous manner. This paper proposes a new methodology for studying the impact on signaling channels when mixture of synchronous and asynchronous traffic is present in the network. This is based on statistical analysis, considering signaling accessing attempts as driven by a Poisson process. In this approach successive random access attempts by the mobile stations are considered as well as the response on the network side. First implementation is held for GSM GPRS network, although generalization of the method for other technologies is possible. The simulated results show potential problems to be solved when a large number of synchronized users is present. Additionally, an analysis on the effects of the different levels of synchronization and the addition of extra signaling channels is included. Results also point out possible development paths that could be taken when designing new features to make networks more robust to synchronized traffic. We study an interference network where equally-numbered transmitters and receivers lie on two parallel lines, each transmitter opposite its intended receiver. We consider two short-range interference models: the "asymmetric network," where the signal sent by each transmitter is interfered only by the signal sent by its left neighbor (if present), and a "symmetric network," where it is interfered by both its left and its right neighbors. Each transmitter is cognizant of its own message, the messages of the @math transmitters to its left, and the messages of the @math transmitters to its right. Each receiver decodes its message based on the signals received at its own antenna, at the @math receive antennas to its left, and the @math receive antennas to its right. For such networks we provide upper and lower bounds on the multiplexing gain, i.e., on the high-SNR asymptotic logarithmic growth of the sum-rate capacity. In some cases our bounds meet, e.g., for the asymmetric network. Our results exhibit an equivalence between the transmitter side-information parameters @math and the receiver side-information parameters @math in the sense that increasing decreasing @math or @math by a positive integer @math has the same effect on the multiplexing gain as increasing decreasing @math or @math by @math . Moreover---even in asymmetric networks---there is an equivalence between the left side-information parameters @math and the right side-information parameters @math . Most medium access control (MAC) mechanisms discard collided packets and consider interference harmful. Recent work on Analog Network Coding (ANC) suggests a different approach, in which multiple interfering transmissions are strategically scheduled. Receiving nodes collect the results of collisions and then use a decoding process, such as ZigZag decoding, to extract the packets involved in the collisions. In this paper, we present an algebraic representation of collisions and describe a general approach to recovering collisions using ANC. To study the effects of using ANC on the performance of MAC layers, we develop an ANC-based MAC algorithm, CMAC, and analyze its performance in terms of probabilistic latency guarantees for local packet delivery. Specifically, we prove that CMAC implements an abstract MAC layer service, as defined in [14, 13]. This study shows that ANC can significantly improve the performance of the abstract MAC layer service compared to conventional probabilistic transmission approaches. We illustrate how this improvement in the MAC layer can translate into faster higher-level algorithms, by analyzing the time complexity of a multi-message network-wide broadcast algorithm that uses CMAC.