This paper presents a hardware design of high throughput, low latency preamble detector for 3GPP LTE physical random access channel (PRACH) receiver. The presented PRACH receiver uses the pipelined structure to improve the throughput of power delay profile (PDP) generation which is executed multiple times during the preamble detection. In addition, to reduce detection latency, we propose an instantaneous preamble detection method for both restricted and unrestricted set. The proposed preamble detection method can detect all existing preambles directly and instantaneously from PDP output while conducting PDP combining for restricted set. The PDP combining enables the PRACH receiver to detect preambles robustly even in severe Doppler effect or frequency error exist. Using proposed method, the worst case preamble detection latency time can be less than 1 ms with 136 MHz clock and the proposed PRACH receiver can be implemented with approximately 237k equivalent ASIC gates count or occupying 30.2% of xc6vlx130t FPGA device.

Existing MANET routing protocols may not be efficient for mobile sensor networks (MSNs) since they generate too much control traffic by relying on flooding or route maintenance messages. Furthermore, peer-to-peer communication patterns assumed in MANET would exacerbate the traffic around sink nodes in MSNs. In this paper we propose traffic adaptive routing (TAR) for MSNs; it can reduce the control packets by analyzing and predicting the source, volume, and the patterns of both traffic and mobility. Through its analysis and the prediction of mobility, TAR also copes with dynamic topology changes by carrying out a fast route recovery process. Our theoretical analysis shows that TAR can effectively reduce unnecessary control packet flooding by 53% on average when compared to AODV. We implement TAR on NS-2. Our experimental evaluation confirms that TAR can not only improve the network and energy performance for MSNs but also can be a practical routing solution for MANET and WSNs compared to the existing ad hoc routing protocols.

Reliable broadcasting in vehicular ad-hoc networks is challenging due to their unique characteristics including intermittent connectivity and various vehicular scenarios. Applications and services in intelligent transportation systems need an efficient, fast and reliable broadcasting protocol especially for safety and emergency applications. In our previous work, we have proposed DECA, a new reliable broadcasting protocol which suits such characteristics. To address the issue of various vehicular scenarios, our protocol performs beaconing to gather local density information of 1-hop neighbors and uses such information to adapt its broadcasting decision dynamically. Specifically, before broadcasting a message, a node selects a neighbor with the highest density and adds the selected neighbor's identifier to the message. Upon receiving of a broadcast message, each node checks whether or not it is the selected neighbor. If so, it is responsible for rebroadcasting the message immediately. This mechanism can raise the data dissemination speed of our protocol so that it is as fast as simple flooding. To address the issue of intermittent connectivity, identifiers of broadcast messages are added into beacons. This helps nodes to check if there are any broadcast messages that have not yet been received. In this paper, we propose DECA with a new beaconing algorithm and a new waiting timeout calculation, so-called DECA-bewa. Our new protocol can reduce redundant retransmissions and overall overhead in high density areas. The protocol performance is evaluated on the network simulator (NS-2). Simulation results show that DECA-bewa outperforms existing protocols in terms of reliability, overhead and speed of data dissemination.

Cardinality estimation schemes of Radio Frequency IDentification (RFID) tags using Framed Slotted ALOHA (FSA) based protocol are studied in this paper. Not as same as previous estimation schemes, we consider tag cardinality estimation problem under not only detection errors but also capture effect, where a tag's IDentity (ID) might not be detected even in a singleton slot, while it might be identified even in a collision slot due to the fading of wireless channels. Maximum Likelihood (ML) approach is utilized for the estimation of the detection error probability, the capture effect probability, and the tag cardinality. The performance of the proposed method is evaluated under different system parameters via computer simulations to show the method's effectiveness comparing to other conventional approaches.

Smart OSPF (S-OSPF), a load balancing, shortest-path-based routing scheme, was introduced to improve the routing performances of networks running on OSPF assuming that exact traffic demands are known. S-OSPF distributes traffic from a source node to neighbor nodes, and after reaching the neighbor nodes, traffic is routed according to the OSPF protocol. However, in practice, exact traffic demands are difficult to obtain, and the distribution of unequal traffic to multiple neighbor nodes requires complex functionalities at the source. This paper investigates non-split S-OSPF with the hose model, in which only the total amount of traffic that each node injects into the network and the total amount of traffic each node receives from the network are known, for the first time, with the goal of minimizing the network congestion ratio (maximum link utilization over all links). In non-split S-OSPF, traffic from a source node to a destination node is not split over multiple routes, in other words, it goes via only one neighbor node to the destination node. The routing decision with the hose model is formulated as an integer linear programming (ILP) problem. Since the ILP problem is difficult to solve in a practical time, this paper proposes a heuristic algorithm. In the routing decision process, the proposed algorithm gives the highest priority to the node pair that has the highest product of the total amount of injected traffic by one node and total amount of received traffic by the other node in the pair, where both traffic volumes are specified in the hose model, and enables a source node to select the neighbor node that minimizes network congestion ratio for the worst case traffic condition specified by the hose model. The non-split S-OSPF scheme's network congestion ratios are compared with those of the split S-OSPF and classical shortest path routing (SPR) schemes. Numerical results show that the non-split S-OSPF scheme offers lower network congestion ratios than the classical SPR scheme, and achieves network congestion ratios comparable to the split S-OSPF scheme for larger networks. To validate the non-split S-OSPF scheme, using a testbed network experimentally, we develop prototypes of the non-split S-OSPF path computation server and the non-split S-OSPF router. The functionalities of these prototypes are demonstrated in a non-split S-OSPF network.

This paper clarifies the effects of metal wires placed around a Multiple-Input-Multiple-Output (MIMO) array with the goal of improving the channel capacity in near-field MIMO systems. Tests are performed on dual-dipole arrays with metal wires placed parallel to the dipoles. If the antenna elements have an appropriate half-power beamwidth (HPBW), there is a clear improvement in the channel capacity of the dual-dipole array. The metal wires are used to increase the multipath richness and the locations of the wires significantly impact the channel capacity. A significant increase in the channel capacity is observed even if only one metal wire is placed in the proper location. We verified the generality of applying a metal wire to improve the channel capacity and that the improvement in the channel capacity is approximately proportional to the number of metal wires.

IEEE802.11 Wireless Local Area Networks (WLANs) are becoming more and more pervasive due to their simple channel access mechanism, Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA), but this mechanism provides all nodes including Access Point and other Stations with the same channel access probability. This characteristic does not suit the infrastructure mode which has so many downlink flows to be transmitted at the Access Point that congestion at the Access Point is more likely to occur. To resolve this asymmetry traffic problem, we develop an Optimal Contention Window Adjustment method assuming the condition of erroneous channels over WLANs. This method can be easily implemented and is compatible with the original CSMA/CA mechanism. It holds the ratio of downlink and uplink flows and at the same time achieves the maximum saturation throughput in the WLANs. We use the Markov Chain analytical model to analyze its performance and validate it through the simulations.

Automatic modulation classification (AMC) is an important function of radio surveillance systems in order to identify unknown signals. Many previous works on AMC have utilized signal cyclostationarity, particularly spectral correlation density (SCD), but many of them fail to address several implementation issues, such as the assumption of perfect knowledge of the symbol rate. In this paper, we discuss several practical issues, e.g. cyclic frequency mismatch, which may affect the SCD, and propose compensation techniques to overcome those issues. We also propose a novel feature extraction technique from the SCD, which utilizes the SCD of not only the original received signal, but also the squared received signal. A symbol rate estimation technique which complements the feature extraction is also proposed. Finally, the classification performance of the system is evaluated through Monte Carlo simulations using a wide variety of modulated signals, and simulation results show that the proposed technique can estimate the symbol rate and classify modulation with a probability of above 0.9 down to SNRs of 5 dB.

In this paper, we study the problem of joint resource allocation in the two-way relay system, where a pair of multi-antenna users wish to exchange information via multi-antenna amplify-and-forward relay under orthogonal frequency-division multiplexing (OFDM) modulation. We formulate a sum-rate maximization problem subject to a limited power constraint for each user and relay. Our resource allocation strategy aims at finding the best pairing scheme and optimal power allocation over subchannels in frequency and space domains. This turns out to be a mixed integer programming problem. We then derive an asymptotically optimal solution though the Lagrange dual decomposition approach. Finally, simulation results are provided to demonstrate the performance gain of the proposed algorithms.

MIMO two-way multi-hop networks are considered in which the radio resource is fully reused in all multi-hop links to increase spectrum efficiency while the adjacent interference signals are cancelled by MIMO processing. In addition, the nodes in the multi-hop network optimize their transmit powers to mitigate the remaining overreach interference. Our main contribution in this paper is to investigate an efficient relay placement method with power allocation in such networks. We present two formulations, namely QoS-constrained optimization and SINR balancing, and solve them using a sequential geometric programming method. The proposed algorithm takes advantage of convex optimization to find an efficient configuration. Simulation results show that relay placement has an important impact on the effectiveness of power allocation to mitigate the interference. Particularly, we found that an uniform relay location is optimal only in power-limited scenarios. With optimal relay locations, significant end-to-end rate gain and power consumption reduction are achieved by SINR balancing and QoS-constrained optimization, respectively. Furthermore, the optimal number of hops is investigated in power or interference-limited scenarios.

A method for the specification of weighting functions for a spaceborne/airborne interferometric synthetic aperture radar (SAR) sensor for Earth observation and environment monitoring is introduced. This method is based on designing an optimum mismatched filter which minimizes the total power in sidelobes located out of a specified range region around the peak value point of the system point-target response, i.e. impulse response function under the constraint imposed on the peak value. It is shown that this method allows achieving appreciable improvement in accuracy performance without degradation in the range resolution.

High-resolution time of arrival (TOA) estimation techniques have great promise for the high range resolution required in recently developed radar systems. A widely known super-resolution TOA estimation algorithm for such applications, the multiple-signal classification (MUSIC) in the frequency domain, has been proposed, which exploits an orthogonal relationship between signal and noise eigenvectors obtained by the correlation matrix of the observed transfer function. However, this method suffers severely from a degraded resolution when a number of highly correlated interference signals are mixed in the same range gate. As a solution for this problem, this paper proposes a novel TOA estimation algorithm by introducing a maximum likelihood independent component analysis (MLICA) approach, in which multiple complex sinusoidal signals are efficiently separated by the likelihood criteria determined by the probability density function (PDF) of a complex sinusoid. This MLICA schemes can decompose highly correlated interference signals, and the proposed method then incorporates the MLICA into the MUSIC method, to enhance the range resolution in richly interfered situations. The results from numerical simulations and experimental investigation demonstrate that our proposed pre-processing method can enhance TOA estimation resolution compared with that obtained by the original MUSIC, particularly for lower signal-to-noise ratios.

An instrumental variable (IV) based linear estimator is proposed for effective target localization in sensor network by using time-difference-of-arrival (TDOA) measurement. Although some linear estimation approaches have been proposed in much literature, the target localization based on TDOA measurement still has a room for improvement. Therefore, we analyze the estimation errors of existing localization estimators such as the well-known quadratic correction least squares (QCLS) and the robust least squares (RoLS), and demonstrate advantages of the proposition by comparing the estimation errors mathematically and showing localization results through simulation. In addition, a recursive form of the proposition is derived to consider a real time application.

A highly parallel turbo decoder for 3GPP LTE/LTE-Advanced systems is presented. It consists of 32 radix-4 soft-in/soft-out (SISO) decoders. Each SISO decoder is based on the proposed full-parallel sliding window (SW) schedule. Implemented in a 0.13 µm CMOS technology, the proposed design occupies 12.96 mm² and achieves 1.5 Gb/s while decoding size-6144 blocks with 5.5 iterations. Compared with conventional SW schedule, the throughput is improved by 30–76% with 19.2% area overhead and negligible energy overhead.

This letter presents an effective direction of arrival (DOA) estimator that is based on the orthogonal projection (OP) technique. When an OP matrix is attained, the proposed estimator, which dispenses with spatial smoothing (SS) preprocessing, can form the maximizing orthogonality for a single snapshot. Since this technique does not need to perform eigen-decomposition while maintaining better DOA estimates, it also has real-time DOA estimation capability. Numerical results are presented to illustrate the efficiency of this method.

Low-complexity joint subcarrier and power allocation is considered. The applied criterion is to minimize the transmission power while satisfying the users' rate requirements. Subcarrier and power allocation are separately applied. Fixed spectrum efficiency is assumed to simplify the subcarrier allocation. We show that under fixed spectrum efficiency, power allocation can be obtained by solving some sets of linear equations. Simulation result shows the effectiveness of the proposed algorithm.

A novel and energy-efficient algorithm with Quality-of-Service (QoS) guarantee is proposed for cooperative spectrum sensing (CSS) with soft information fusion and hard information fusion. By weighting the sensing performance and the consumption of system resources in a utility function that is maximized with respect to the number of secondary users (SUs), it is shown that the optimal number of SUs is related to the price of these QoS requirements.