Transmitter-receiver Pair Research Articles

A Generalized Channel Coding Theory for Distributed Communication

This paper presents generalized channel coding theorems for a time-slotted distributed communication system where a transmitter-receiver pair is communicating in parallel with other transmitters. Assume that the channel code of each transmitter is chosen arbitrarily in each time slot. The coding choice of a transmitter is denoted by a code index parameter, which is known neither to other transmitters nor to the receiver. Fundamental performance limitation of the system is characterized using an achievable region defined in the space of the code index vectors. As the codeword length is taken to infinity, for all code index vectors inside the region, the receiver will decode the message reliably, while for all code index vectors outside the region, the receiver will report a collision reliably. A generalized system error performance measure is defined as the weighted sum of probabilities of different types of communication error events. Assume that the receiver chooses an “operation region” and intends to decode the message if the code index vector is inside the operation region. Achievable bounds on the tradeoff between the operation region and the generalized error performance measure are obtained under the assumption of a finite codeword length.

On the Sum-Rate of the Gaussian MIMO Z Channel and the Gaussian MIMO X Channel

In this paper, we study the Gaussian MIMO Z channel and the Gaussian MIMO X channel. The MIMO X channel (XC) consists of two multiple antenna transmit-receive pairs, where each transmitter communicates with both receivers. The MIMO Z channel (ZC) is obtained from the MIMO X channel by eliminating one of the links and its corresponding message. First, we derive a sum-rate upper bound for the MIMO Z channel and compare it with an existing bound in literature. Next, we consider the MIMO X channel and propose a new sum-rate upper bound by utilizing the sum-rate upper bound for the MIMO ZC. Subsequently, we derive another upper bound for the MIMO XC by assuming receiver cooperation and deriving the worst noise covariance matrix for the resulting two-user MAC. We compare the above two upper bounds for the MIMO XC with the MaddahAli-Motahari-Khandani (MMK) scheme. Then, we consider some consequences of the above results for the MIMO interference channel. Finally, we present some numerical results. The numerical results suggest that the proposed sum-rate capacity upper bounds are tighter than existing bounds.

Distributed Utility Maximization with Backward Physical Signaling in Interference-Limited Wireless Systems

In this paper, we consider a distributed power control scheme that can maximize overall capacity of an interference-limited wireless system in which the same radio resource is spatially reused among different transmitter-receiver pairs. This power control scheme employs a gradient-descent method in each transmitter, which adapts its own transmit power to co-channel interference dynamically to maximize the total weighted sum rate (WSR) of the system over a given interval. The key contribution in this paper is to propose a common feedback channel, over which a backward physical signal is accumulated for computing the gradient of the transmit power in each transmitter, thereby significantly reducing signaling overhead for the distributed power control. We show that the proposed power control scheme can achieve almost 95% of its theoretical upper WSR bound, while outperforming the non-power-controlled system by roughly 63% on average.

Signal‐to‐interference‐plus‐noise ratio‐based multi‐relay beamforming for multi‐user multiple‐input multiple‐output cognitive relay networks with interference from primary network

Cognitive radio is a potential technique to solve the spectrum shortage problem in wireless communications. Integrating wireless relaying into the cognitive radio networks can further improve the spectrum efficiency. In this study, a multiple-input multiple-output cognitive relay network is considered, where the primary network (PN) consists of one transmitter-receiver pair and the secondary network consists of multiple active source-destination pairs and non-regenerative relays. All nodes in the networks are deployed with multiple antennas. How to avoid interference to the PN is an important task in the secondary network design. The precoders of the secondary sources and the receivers of the secondary destinations are designed in a well-known zero-forcing way. The secondary relays forward signals for the secondary source-destination pairs by beamforming. With interference cancellation constraints and individual transmit power constraints, a relay beamforming scheme is proposed to maximise the total signal-to-interference-plus-noise ratio (SINR) at the secondary destinations. Then a maximising minimum SINR relay beamforming scheme is further proposed to provide max–min fairness among the secondary source-destination pairs. The beamforming problems are formulated into the quadratically constrained quadratic fractional programming problems, and are solved by the semi-definite relaxation technique. The performances of these beamforming schemes have been verified by computer simulations.

Hyperbolic Localization in MIMO Radar Systems

This letter addresses an effective algorithm for target localization in multiple-input-multiple-output (MIMO) radar systems with widely separated antennas. The algorithm derived uses time-of-arrival (TOA) measurements from multiple transmitter-receiver pairs and is based on a hyperbolic method suitable for radiation source localization in passive sensor networks. It does not have the local convergence problem as the conventional iterative method. Some combinations of the derived algorithm and the conventional iterative method are presented. In a numerical example, it is shown that the proposed methods can achieve the Cramer-Rao lower bound (CRLB) in the range of moderate processed measurement noise and obtain the better localization performance as the number of transmitters and receivers increases. Furthermore, some remarks are made on the robustness of the proposed methods.

Distributed Channel Assignment in Cognitive Radio Networks: Stable Matching and Walrasian Equilibrium

We consider a set of secondary transmitter-receiver pairs in a cognitive radio setting. Based on channel sensing and access performances, we consider the problem of assigning channels orthogonally to secondary users through distributed coordination and cooperation algorithms. Two economic models are applied for this purpose: matching markets and competitive markets. In the matching market model, secondary users and channels build two agent sets. We implement a stable matching algorithm in which each secondary user, based on his achievable rate, proposes to the coordinator to be matched with desirable channels. The coordinator accepts or rejects the proposals based on the channel preferences which depend on interference from the secondary user. The coordination algorithm is of low complexity and can adapt to network dynamics. In the competitive market model, channels are associated with prices and secondary users are endowed with monetary budget. Each secondary user, based on his utility function and current channel prices, demands a set of channels. A Walrasian equilibrium maximizes the sum utility and equates the channel demand to their supply. We prove the existence of Walrasian equilibrium and propose a cooperative mechanism to reach it. The performance and complexity of the proposed solutions are illustrated by numerical simulations.

Persymmetric adaptive target detection with distributed MIMO radar

Based on persymmetric structures in received signals, we consider the adaptive detection problem in colored Gaussian noise with unknown persymmetric covariance matrix in a multiple-input, multiple-output (MIMO) radar with spatially dispersed antennas. To this end, a set of secondary data for each transmit-receive pair is assumed to be available. A MIMO version of the persymmetric generalized likelihood ratio test (MIMO-PGLRT) detector is proposed. A closed-form expression for the probability of false alarm of this detector is derived. In addition, a MIMO version of the persymmetric sample matrix inversion (MIMO-PSMI) detector is also developed. Compared to the MIMO-PGLRT detector, MIMO-PSMI has a simpler form and is computationally more efficient. Numerical examples are provided to demonstrate that the proposed two detection algorithms can significantly alleviate the requirement of the amount of secondary data and allow for a noticeable improvement in detection performance.

On Primary User Coverage Probabilities and Faulty Cognitive Radios

In a cognitive radio (CR) network, the CR devices opportunistically communicate in the frequency bands occupied by the primary users in order to improve the spectral efficiency in these bands. By sensing the primary users, e.g., the television transmitter-receiver pairs and the wireless microphone systems, each CR device determines whether or not to operate in the band. The CR devices, due to erroneous sensing, either fail to detect the primary user, causing excessive interference at the primary users, or have a false-alarm, causing it to remain silent in a white-space band leading to poor spectrum utility. The impact of these imperfections on the primary user operations in terms of the coverage probability is characterized where the primary users and the CR devices are distributed according to independent homogeneous Poisson point processes on the plane.

Independent Signaling Achieves the Capacity Region of the Gaussian Interference Channel With Common Information to Within One Bit

The interference channel with common information (IC-CI) consists of two transmit-receive pairs that communicate over a common noisy medium. Each transmitter has an individual message for its paired receiver, and additionally, both transmitters have a common message to deliver to both receivers. In this paper, through explicit inner and outer bounds on the capacity region, we establish the capacity region of the Gaussian IC-CI to within a bounded gap of one bit, independently of the values of all channel parameters. Using this constant-gap characterization, the generalized degrees of freedom (GDoF) region is determined. It is shown that the introduction of the common message leads to an increase in the GDoF over that achievable over the Gaussian interference channel without a common message, and hence to an unbounded improvement in the achievable rate. A surprising feature of the capacity-within-one-bit result is that most of the available benefit (i.e., to within one bit of capacity) due to the common message is achieved through a simple and explicit coding scheme that involves independent signaling at the two transmitters so that, in effect, this scheme forgoes the opportunity for transmitter cooperation that is inherently available due to shared knowledge of the common message at both transmitters.

On Queue-Aware Power Control in Interfering Wireless Links: Heavy Traffic Asymptotic Modelling and Application in QoS Provisioning

In this work, we address the problem of power allocation for interfering transmitter-receiver pairs so that the probability that each queue length exceeds a specified threshold is fixed at a desired value. One application is satisfying QoS requirements in a dense cellular network. We deal with this problem using heavy traffic approximation techniques which lead to an asymptotic model of a (controlled) stochastic differential equation. The proposed power control strategy consists of allocating most of the power according to the states of the channel and a smaller fraction according to the queue lengths, for which we find a closed-form expression. We first consider a scenario where all channel realizations and queue lengths are known instantaneously to every transmitter. Then, the algorithm is extended to the case where only local SINR feedback is available and when queue length information is shared with delays among the transmitters. These models and results are also extended to the case where the transmitters are equipped with multiple antennas. Finally, the applicability in practical system settings are discussed and simulation results are provided to illustrate the performance of the proposed method.

Null Space Learning With Interference Feedback for Spatial Division Multiple Access

We propose a learning technique for MIMO communication systems to perform spatial division multiple access with minimal cooperation between users. In the proposed technique, each user (in a two-user receiver-transmitter pair) learns the null space of the interference channel to the other user by transmitting a learning signal and observing an affine function of the other user's interference plus noise power. The only requirement is that each system broadcasts, through a low-rate control channel, a periodic beacon that is a function of its noise plus interference power, which in practice is typically known by each system's receiver and transmitter. Thus, the learning can be made by the two users' transmitters without affecting the communication protocol between each user's receiver and transmitter. The proposed learning scheme is particularly attractive for underlay cognitive radio, where only the secondary user (SU), which must not interfere with the primary user (PU), has to learn the null space. In this case, the PU can broadcast the scheme's beacon without being aware of the SU. Furthermore, if the PU uses a power control mechanism which maintains a constant signal to interference plus noise ratio, the SU can learn the null space even without a beacon, i.e., without any cooperation with the PU.

English

One of the most popular technique to control robotic arm is by making it emulate the movements of the human arm. One of the advantages of the robotic arm is that it simplifies computational complexities. An arrangement of sensors attached to the human arm is used for tracking down hand movement. The arrangement consists of two accelerometers, a potentiometer and an IR receiver-transmitter pair. The Robotic Arm has Five degree of freedom where each joint is controlled by a servo motor that are capable of producing a movement of 180 degrees. In this paper we have proposed an algorithm based on correction and prediction for the purpose of swift synchronization of human hand and Robotic Arm. Successful implementation of the algorithm was achieved on the robotic arm.

Road-RFSense: A Practical RF Sensing--Based Road Traffic Estimation System for Developing Regions

An unprecedented rate of growth in the number of vehicles has resulted in acute road congestion problems worldwide, especially in many developing countries. In this article, we present Road-RFSense, a practical RF sensing--based road traffic estimation system for developing regions. Our first contribution is a new mechanism to sense road occupancy, based on variation in RF link characteristics, when line of sight between a transmitter-receiver pair is obstructed. We design algorithms to classify traffic states into two classes, free-flow versus congested, at timescales of 20 seconds with greater than 90% accuracy. We also present a traffic queue length measurement system, where a network of RF sensors can correlate the traffic state classification decisions of individual sensors and detect traffic queue length in real time. Deployment of our system on a Mumbai road gives correct estimates, validated against 9 hours of image-based ground truth. Our third contribution is a large-scale data-driven study, in collaboration with city traffic authorities, to answer questions regarding road-specific classification model training. Finally, we explore multilevel classification into seven different traffic states using a larger set of RF-based features and careful choice of classification algorithms.

认知无线电系统中的多中继分布式波束成形方法

In this paper, the cognitive scenario where a source-destination pair of secondary users coexists with a licensed transmitter-receiver pair with the help of a group of cognitive relay nodes is considered. To exploit the spatial spectrum holes, we study the distributed beamforming of multiple cognitive relay nodes each equipped with a single antenna for the maximization of signal-to-interference-plus-noise ratio (SINR) at the cognitive destination, while keeping the interference power at the licenced receiver below a certain threshold and satisfying the individual power constraint. Two beamforming schemes are proposed: 1) the optimal scheme maximizing SINR; and 2) a suboptimal zero-forcing scheme. The optimal beamforming problem can be reformulated as a quasi-convex optimization problem using semide nite relaxation (SDR), then the bisection and interior point methods can be used to solve this problem. It can also be proved that SDR yields the optimal solution to the original problem. The suboptimal zero-forcing scheme eliminates the interference at the licensed receiver as well as the signals from the licensed transmitter. It has a low complexity without iterations and simple constraint functions. Numerical results are presented to show the impacts of the number of relay nodes, the maximum transmit power of cognitive nodes, and the threshold of power of interferences at the licenced receiver to the average achievable rates of the two schemes. Furthermore, the performance will be improved if the impact of signals from licenced transmitter is taken into account, which is veri ed through simulation experiments.

Vertical Soil Profiling Using a Galvanic Contact Resistivity Scanning Approach

Proximal sensing of soil electromagnetic properties is widely used to map spatial land heterogeneity. The mapping instruments use galvanic contact, capacitive coupling or electromagnetic induction. Regardless of the type of instrument, the geometrical configuration between signal transmitting and receiving elements typically defines the shape of the depth response function. To assess vertical soil profiles, many modern instruments use multiple transmitter-receiver pairs. Alternatively, vertical electrical sounding can be used to measure changes in apparent soil electrical conductivity with depth at a specific location. This paper examines the possibility for the assessment of soil profiles using a dynamic surface galvanic contact resistivity scanning approach, with transmitting and receiving electrodes configured in an equatorial dipole-dipole array. An automated scanner system was developed and tested in agricultural fields with different soil profiles. While operating in the field, the distance between current injecting and measuring pairs of rolling electrodes was varied continuously from 40 to 190 cm. The preliminary evaluation included a comparison of scan results from 20 locations to shallow (less than 1.2 m deep) soil profiles and to a two-layer soil profile model defined using an electromagnetic induction instrument.

3D finite-element forward modeling of electromagnetic data using vector and scalar potentials and unstructured grids

We present a finite-element solution to the 3D electromagnetic forward-modeling problem in the frequency domain. The method is based on decomposing the electric field into vector and scalar potentials in the Helmholtz equation and in the equation of conservation of charge. Edge element and nodal element basis functions were used, respectively, for the vector and scalar potentials. This decomposition was performed with the intention of satisfying the continuity of the tangential component of the electric field and the normal component of the current density across the interelement boundaries, therefore finding an efficient solution to the problem. The computational domain was subdivided into unstructured tetrahedral elements. The system of equations was discretized using the Galerkin variant of the weighted residuals method, with the approximated vector and scalar potentials as the unknowns of a sparse linear system. A generalized minimum residual solver with an incomplete LU preconditioner was used to iteratively solve the system. The solution method was validated using five examples. In the first and second examples, the fields generated by small dipoles on the surface of a homogeneous half-space were compared against their corresponding analytic solutions. The third example provided a comparison with the results from an integral equation method for a long grounded wire source on a model with a conductive block buried in a less conductive half-space. The fourth example concerned verifying the method for a large conductivity contrast where a magnetic dipole transmitter-receiver pair moves over a graphite cube immersed in brine. Solutions from the numerical approach were in good agreement with the data from physical scale modeling of this scenario. The last example verified the solution for a resistive disk model buried in marine conductive sediments. For all examples, convergence of the solution that used potentials were significantly quicker than that using the electric field.

Modular Robot with Self-Reconfigurable Capabilities

The paper presents a modular robot, designed for reconfiguring, in order to achieve both walking and crawling motion. Each module has 2 DOFs (rotations). Six modules can be connected to form a four-legged structure or an open chain. The robot has self-reconfiguring skills and is able to perform creeping/walking motion. A distributed control is accomplished, each module having its own controller and RF transmitter-receiver pair, for communication with the host computer.

Approximation Algorithm for Joint Node Placement and Frequency Selection in Bistatic Radar Sensor Networks

We consider a bistatic radar sensor network that consists of multiple separated radar transmitters and radar receivers, which are deployed to detect targets among a set of points of interest. Any transmitter-receiver pair with the same frequency forms a bistatic radar. In contrast to the disk-based sensing model in a traditional sensor network, the detection probability of a bistatic radar depends on both locations of the transmitter and receiver. Given the radar transmitters' locations and illuminating frequencies, we study the problem of joint radar receiver placement and frequency selection to maximize the target detection probability. We first study the case where there is a set of candidate locations to place the radar receivers, and propose a simple algorithm with approximation ratio at least 0.63. We then consider the case where there is no constraint for radar receivers' locations, and develop an approximation algorithm which is provably close to optimal. Finally, the numerical results are presented to show the efficacy of our algorithms.

Decentralized Wireless Networks: Spread Spectrum Communications Revisited

This paper addresses a decentralized wireless networks of K separate transmitter-receiver pairs. Users treat each other as noise and there is no central controller to assign the resources to the users. Each user randomly spreads the symbols in its Gaussian codewords by the so-called signatures of spreading gain N. Any receiver is aware of the signatures of its affiliated transmitter, however, it is unaware of the signatures of other users. This makes the interference plus noise at each receiver be mixed Gaussian, and hence, there is no closed expression for the achievable rates of users. Invoking conditional entropy power inequality and a key upper bound on the differential entropy of a mixed Gaussian random vector, we develop a lower bound on the achievable rates of users. This lower bound has the same signal-to-noise ratio (SNR) scaling as that of the exact achievable rate. It is shown that the sum multiplexing gain (SMG) in the network can be made arbitrarily close to (K/N) for any finite values of K and N where K ≤ N. The effect of matched filtering is studied in the particular case where the signatures are constructed over a binary alphabet. It is established that the SMG of the network is larger than (1/2e) regardless of the value of K as long as N = 2 and the signatures are generated according to a proper nonuniform distribution. This paper is concluded by a section on signature design in the finite SNR regime. The main observation is that for any two different methods A and B of designing the signatures, if method A results in a larger achievable rate per user for sufficiently large SNR values, then construction B is likely to yield larger achievable rates for sufficiently small values of SNR. This behavior is attributed to the interplay between two critical factors, namely, the multiplexing gain per user and what we refer to as the interference entropy factor.

Outage performance of relay-assisted primary and secondary transmissions in cognitive relay networks

Abstract In this paper, a two-phase protocol for relay-assisted spectrum sharing in cognitive relay network is proposed. The primary system comprises a transmitter-receiver pair (PT-PR) and a decode-and-forward relay (Relay), while the secondary system comprises a transmitter-receiver pair (ST-SR). In the proposed protocol, the Relay assists the transmissions of the primary users as well as the secondary users where there is no direct link between the ST and the SR. Outage probabilities of the primary system and the secondary system are derived and verified through simulations. Compared with the protocol without cooperation, better outage performance of the primary system is achieved. Meanwhile, though the ST causes interference to the PR, the interference is compensated by the cooperation of the Relay. Moreover, the proposed protocol realizes the communications of the secondary users on the condition that the secondary transmission link is not ideal.