Indoor positioning plays an important role in a variety of applications under Internet of Things (IoT). Conventional WiFi fingerprinting-based indoor positioning systems (IPSs) usually require extensive manual calibrations to construct radio maps. This process severely limits the system scalability and adaptiveness. Pedestrian dead reckoning (PDR) is a popular method that can avoid the calibration process. However, PDR-based IPSs typically suffer from accumulated errors. To tackle this problem, many refinement methods require map information or floorplans which may not be available or up-to-date in practice. With the development of IoT, various types of crowdsourced data become available. In this work, we propose GraphIPS, a calibration-free and map-free IPS which dynamically generates accurate radio maps by utilizing smartphone crowdsourced WiFi and inertial measurement unit (IMU) data. GraphIPS fuses the crowdsourced data into a graph-based formulation and applies the multidimensional scaling (MDS) algorithm to compute the positions of the user's steps. The experimental results show that GraphIPS achieves comparable accuracy to the calibration-based method in a significantly shorter run time than optimization-based methods. In addition to smartphones, GraphIPS is also potentially applicable for the smart wearables with embedded WiFi modules and IMUs.

With the development of Internet of Things (IoT), a variety of crowdsourced data becomes available. In this article, we propose to utilize the crowdsourced WiFi received signal strength (RSS) data to perform indoor positioning. In many instances, the size of crowdsourced WiFi RSS data is potentially large, and the ground truths of the corresponding RSS fingerprints are unavailable. Therefore, it is challenging to construct the associated radio map. In the proposed method, a heuristic geometrical algorithm is developed to convert the RSS data into pairwise distances among the fingerprints. Based on these pairwise distances, multidimensional scaling (MDS) is then applied to compute the positions of all the fingerprints, thereby building a radio map. We show that the accuracy of the proposed method is only reasonably lower than a state-of-the-art calibration-based method. Further, we present a k -means clustering-based region partitioning method that partitions the large crowdsourced data set effectively. The parallel processing on the partitioned data and computational simplicity of MDS result in significantly shorter runtime for the proposed method than the previous optimization-based methods.

Indoor positioning plays an important role in various location-based services (LBSs). In conventional systems, the process of constructing radio maps for positioning usually involves labor-intensive manual calibrations, which seriously limits the system's scalability and adaptiveness. In this paper, we propose an efficient calibration-free method by leveraging on crowdsourced WiFi signal data that are captured passively through a WiFi sensing testbed. Since the ground truths of the crowdsourced data are unavailable, the radio maps cannot be directly constructed. In the proposed method, we adopt the multidimensional scaling (MDS) technique to compute the positions of the unlabeled data thereby generating radio maps. In order to enable MDS, we estimate the pairwise distances among the unlabeled data by using an improved trilateration method and a law of cosine (LoC)-based geometrical algorithm without online pairwise measurements. Experimental results show that the accuracy of the proposed method is higher than trilateration-based method and reasonably lower than that of calibration-based method. Meanwhile, the run time of the proposed method is shorter than previous optimization-based methods. The short run time allows the radio maps to be dynamically updated against the environmental variations.

Indoor position information plays an important role in a wide variety of Internet of Things (IoT) applications. In recent studies, Wi-Fi channel state information (CSI) is becoming a popular tool for indoor positioning and environmental sensing due to the richer information it contains in multiple subcarriers. Deep neural networks (DNNs) and convolutional neural networks (CNNs) have been applied in training CSI data for indoor positioning and are shown to have fine performances. However, the potential sequential correlations among the subcarriers and consecutive CSI packets are yet to be exploited in those networks. In this study, we propose a two-level nested long short-term memory (LSTM) network named IPRIC to recognize the indoor positions and classify the type of interferences of Wi-Fi CSI data by analyzing the sequential correlations among the subcarriers and consecutive packets. We apply the discrete wavelet transform (DWT) for data preprocessing to minimize noise and improve classification. As evaluated in an office environment, IPRIC achieves higher classification accuracy than the DNN and CNN-based methods.

Pedestrian dead reckoning (PDR) is a popular localization approach. However, PDR is error prone at turning points. During a turn, a small error in heading estimation can cause severe accumulated positioning errors thereafter. In this paper, we propose a turn-based correction approach which aims to reduce the potential accumulated errors caused by inaccurate heading estimations during turns. We consider a crowdsourcing environment in which previous users' data can help in the positioning of current users. For previous and current users moving in reverse directions and turn at the same position, we match the previous user's turning position with the current user's using Kullback-Leibler (KL) divergence based on the received signal strength (RSS) scans collected. Upon a match, the previous user's pre-turn positions can be used to improve the post-turn positions of the current user. Tests are done for different types of paths and the results show that the proposed approach can effectively reduce the PDR errors caused by inaccurate heading estimations at turning points.

We derive a new computational algorithm for Barrett technique for modular polynomial multiplication, termed BA-P. Residue arithmetic is applied to BA-P to obtain a new Barrett algorithm for modular polynomial multiplication (BA-MPM). The work is focused on an algorithm that carries out computation using modular arithmetic without conversion to large degree polynomials. There are several parts to this work. First, we set up a new BA-P using polynomials other than uα. Second, residue arithmetic based BA-MPM is described. A complete mathematical framework is described including proofs for the results. Third, we present a computational procedure for BA-MPM. Fourth, the BA-MPM is used as a basis for algorithms for modular polynomial exponentiation (MPE). Applications are in areas of signal security and cryptography.

To avoid substantial manual calibration effort, some WiFi-based indoor localization methods attempt to achieve calibration-free feature. However, many of these methods have additional requirements which limit their practical applicabilities, e.g. lateration-based methods require the target locations to be covered by at least three APs, some methods require specific relationships between the training locations and APs. In this paper, we propose an indoor localization system named SimpLoc, which does not require any manual calibration effort nor any strict condition of use. The system applies the multi-dimensional scaling technique by converting the crowd-sourced RSS data to pseudo pairwise distances between the unknown locations. In a 36 × 23m2area, SimpLoc achieves a mean distance error of 1.93m. Experimental results show that the error can still be maintained at 2.14m when only 10 percent of the training data are used.

Directional Medium Access Control protocols (DMACs) have been studied for decades. Since most existing DMACs assume an ideal antenna model which does not consider the minor-lobe interference, their performance cannot be guaranteed in practice. Other approaches assuming non-ideal antenna require either extra equipment or clock synchronization, making the system more complicated. It is also observed that directional transmission is rarely discussed in multi-channel scenarios. In this paper, a Cooperative Multi-channel Directional Medium Access Control protocol (CMDMAC) is proposed, incorporating directional transmission and multi-channel transmission to enhance system performance. Without making the terminals more complex or requiring clock synchronization, CMDMAC uses cooperative methods to solve the hidden terminal and deafness problems, taking into account minor-lobe interference effects of the directional antennas. Protocol performance is studied via simulation in NS2, showing that CMDMAC has good performance in terms of throughput and data packet transmission ratio.

This paper investigates the impact of using outdated channel estimates for relay selection and signal amplification on the performance of amplify-and-forward (AF) relays under partial relay selection (PRS) and opportunistic relay selection (ORS). In practice, outdated channel state information (CSI) can occur due to feedback or scheduling delay. Both variable gain (VG) AF and fixed gain AF schemes are considered. Outage probability, the average bit error rate (BER) and simplified high signal-to-noise ratio approximations are derived. The effect of parameters such as the number of relays, the rank of chosen relay, and the correlation between the delayed and current channel state information are analyzed. Outdated CSI for computing relay gains in PRS causes about 2 dB loss. In ORS, a 3% reduction in correlation causes up to an order of magnitude increase in the outage probability.

We present a downlink opportunistic scheduling algorithm when there are user equipments (UEs) served by multiple mobile terminals (MTs) in a time- slotted cellular system. We study two scenarios, namely Scenario (i) when the scheduler knows the presence of such UEs; and Scenario (ii) when the scheduler has no knowledge of the presence of such UEs. We establish the optimality and present the main properties of our scheduling scheme. Simulations under High-Speed Down-link Packet Access (HSDPA) model are implemented which show that our algorithm works well and provides an approximately 20% performance improvement for the UEs served by multiple MTs as compared to previous opportunistic scheduling schemes. Furthermore, our algorithm is able to provide better overall performance even in the worst case. The objective behind this research work is to establish the performance of cellular systems that provides differentiated quality of service (QoS).

In this paper, we investigate the distributed power allocation strategies for a spectrum-sharing femtocell network, where a central macrocell underlaid with several femtocells. Assuming that the macrocell protects itself by pricing the interference from the femtocells, a Stackelberg game is formulated to jointly consider the utility maximization of the macrocell and the femtocells. Then, the Stackelberg equilibrium for the proposed game is studied, and an effective distributed interference price bargaining algorithm with guaranteed convergency is proposed to achieve the equilibrium. Numerical examples are then presented to verify the proposed studies. It is shown that the algorithm is effective in distributed power allocation and macrocell protection requiring minimal network overhead for spectrum-sharing-based two-tier femtocell networks.

This paper evaluates the impact of using outdated channel estimates due to feedback delay for relay selection and signal amplification on the performance of partial relay selection with amplify-and-forward (AF) relays. Both variable and fixed gain AF schemes are considered. Expressions for the system's outage probability and the average bit error rate, and their high signal-to-noise ratio (SNR) approximations are derived. The effect of parameters such as the rank of relay chosen, SNR imbalance and the correlation between the delayed and current channel state information are studied and verified through simulations.

This paper evaluates the impact of using outdated channel estimates in a multiuser Amplify-and-Forward (AF) relay network, under Nakagami-m fading. Both variable gain AF and fixed gain AF schemes are considered. Expressions for the system's outage probability and the average bit error rate (BER) are derived. Since the expressions are barely tractable, we also present approximations for the high signal-to-noise ratio (SNR) regime. By doing so we characterize the impact of network parameters such as the number of relays, correlation between the delayed and current channel state information, chosen user rank and SNR imbalance on the performance degradation.

In this paper, we consider a cognitive radio (CR) network where a secondary (cognitive) user shares the spectrum for transmission with a primary (non-cognitive) user over block-fading (BF) channels. It is assumed that the primary user has a constant-rate, constant-power transmission, while the secondary user is able to adapt transmit power and rate allocation over different fading states based on the channel state information (CSI) of the CR network. We study a new type of constraint imposed over the secondary transmission to protect the primary user by limiting the maximum transmission outage probability of the primary user to be below a desired target. We derive the optimal power allocation strategies for the secondary user to maximize its ergodic/outage capacity, under the average/peak transmit power constraint along with the proposed primary user outage probability constraint. It is shown by simulations that the derived new power allocation strategies can achieve substantial capacity gains for the secondary user over the conventional methods based on the interference temperature (IT) constraint to protect the primary transmission, with the same resultant primary user outage probability.

In this paper, we consider multi-input multi-output (MIMO) two-way relay networks with orthogonal frequency-division multiplexing (OFDM) modulation scheme. The networks consist of two end users exchanging their information via a relay. One information exchange between two end users is divided into two Phases. In Phase 1, two users send their information to the relay. The relay then amplifies and broadcasts its received signals to the two users in Phase 2, i.e., the relay works in the amplify-and-forward (AF) mode. By doing so, two-way relay networks require half as many time slots to accomplish one information exchange as the traditional one-way relay networks. We propose at each end user an iterative algorithm to jointly estimate the channel information and detect the data transmitted from the other user. The channel information consists of the \textit{composite} channels which are the combinations of individual channels in the networks and noise covariance matrices resulting from the AF working mode of the networks. We apply the Expectation Conditional Maximization (ECM) algorithm to estimate the necessary channel information for detection. Simulation results show that the performance of our proposed iterative algorithm is close to that given by the perfect channel information.

The impact of antenna correlation on the performance of beamforming in a dual-hop fixed gain amplify-and-forward (AF) relay network is analyzed. The source and destination nodes are equipped with multiple antennas correlated in space, whereas the relay has a single antenna. Closed-form expressions for the system's outage probability and the average bit error rate (BER) are derived. We have also presented simple asymptotic outage probability and average BER expressions. When the second link is much stronger than the first link, it is shown that the system's performance at high SNR is only governed by the spatial correlation and number of antennas at the source and the diversity order is equal to the number of antennas at the source. Our analytical results have been verified through comparison with Monte Carlo simulations.

This paper is concerned with a spectrum sharing cognitive radio network. In particular, the individual outage capacity region for a M-user fading cognitive multiple access network sharing the same spectrum with an existing primary network is first characterized. The primary network's transmission is assumed to be protected by the interference power constraint. Then, under the interference power constraint and the individual transmit power constraint of each user, the individual outage capacity region is implicitly obtained by characterizing the boundary points on the individual usage probability region for a given rate vector. The optimal power allocation and decoding strategy is then derived by the Lagrange dual decomposition method. It is proved that the optimal decoding strategy is the successive decoding strategy, and the decoding order is determined by dual variables together with the channel fading gains of the primary and secondary links. Finally, several numerical examples are given to validate the proposed studies.

In this paper we consider a Multi-Input Multi-Output (MIMO) wireless relay network which comprises of a source terminal, a destination terminal and a relay. The transmission from the source terminal to the destination is divided into two phases. During Phase I, the source terminal sends its signals to the relay. The relay only amplifies and forwards its received signals to the destination terminal during Phase II, i.e., the network works in the Amplify-and-Forward (AF) mode. In this mode, the noise elements at the relay at Phase I are also amplified and forwarded through a link (from the relay to the destination terminal). It makes the overall noises across antennas of the destination terminal correlated. This correlation is characterized by a noise covariance matrix. Hence, for the purpose of data detection at the destination terminal, we need to estimate channel coefficients as well as the noise covariance matrix. In the considered network, an error correcting code (ECC) is used. We propose a doubly iterative receiver to estimate channel information and decode transmitted signals. The estimation part is an application of the Expectation Conditional Maximization (ECM) algorithm. Turbo-equalization is used to provide soft information of transmitted signals to the ECM-based algorithm. Simulation results show that our doubly iterative receiver provides an excellent BER performance.

In this paper, the performance of a dual-hop Amplify-and-Forward (AF) multi-antenna relay network, with end-to-end (e2e) best antenna selection, is investigated. To investigate the performance of this system, we first derive the exact outage probability in closed-form. It is then used to obtain expressions for e2e SNR moments and the average symbol/bit error rate (SER/BER) valid for a large class of practical modulation schemes. A simple and accurate BER approximation is also derived to quantify the performance at high SNR. Our analytical results, show that the e2e antenna pair selection scheme achieves the same diversity order as for the case where all antennas are used. To further confirm the validity of our analysis, Monte Carlo simulation results are also presented.

We analyze the impact of outdated channel state information due to feedback delay on the performance of amplify-and-forward relays with the$k$th worst partial relay selection scheme. In our analysis, new expressions for the system's outage probability and the average bit error rate are derived. The effects of the rank of the relay chosen, the average SNR imbalance, and the correlation between the delayed and current signal-to-noise ratio (SNR) on the system performance are investigated. Additionally, simple and accurate outage and average BER approximations are also derived to quantify the performance at high SNR. We also give simulation results to support the theoretical study.

In this letter, we consider a bi-directional relay network in which two users, U1and U2, exchange their information via a relay station, RS. Multiple antennas are deployed at both users and at RS. Single carrier cyclic prefix (SCCP) is used to combat intersymbol interference (ISI) in frequency-selective fading channels. The transmission process is divided into two time slots. At the first time slot, both users send their information to RS concurrently. RS then amplifies and broadcasts its received signals at the second time slot. We propose an algorithm to estimate the channel information at end users based on the least square (LS) principle. To further minimize the mean square error (MSE) of the estimate, a method to design the optimal training sequences is also proposed. Simulation results show that the performance achieved by our optimal design is close to that with perfect channel information.

This paper considers a spectrum underlay network, where an OFDM-based cognitive radio (CR) system is allowed to share the subcarriers of an OFDMA-based primary system for simultaneous transmission. Instead of using the conventional interference power constraint (IPC) to protect the primary users (PUs) in the primary system, a new criterion referred to as rate loss constraint (RLC), in the form of an upper bound on the maximum rate loss of each PU due to the CR transmission, is proposed for primary transmission protection. Assuming the channel state information (CSI) of the PU link, the CR link, and their mutual interference links is available to the CR, the optimal power allocation strategy to maximize the achievable rate of the CR system is derived under RLC together with CR¿s transmit power constraint. It is shown that the CR system can achieve a significant rate gain under RLC as compared to IPC. Furthermore, the relationship between RLC and IPC is investigated, and it is shown that the rate gain is obtained by exploiting the additional CSI of the PU link. A more general case referred to as hybrid protection to PUs is then studied, by taking into account that some PU links¿ CSI is not available at CR.

This paper considers a spectrum sharing based cognitive radio network where a M-user fading multiple access network shares the same spectrum with an existing primary network. The primary network's transmission is assumed to be protected by the interference power constraint. Under this interference power constraint together with the individual transmit power constraint of each user, the outage capacity regions for the fading cognitive multiple access channel (C-MAC) are defined for two different scenarios, i.e., an outage must be declared simultaneously for all users (common outage) and outages are declared individually for each user (individual outage). Then, optimal power allocation strategies to achieve the boundary points of these outage capacity regions are derived by considering their equivalent problems, i.e., the common/individual usage probability maximization for given rate vectors. It is rigorously proved that the optimal decoding strategy is the successive decoding strategy, and the decoding order is determined by the dual variables and the channel power gains of the involved channels. Then, a modified ellipsoid method is proposed to obtain the optimal dual variables. Finally, several numerical examples are given to validate the proposed studies.

This paper considers a spectrum sharing wireless environment, where an OFDM-based cognitive radio system is allowed to access the spectrum originally licensed to an OFDMA primary system. A new criterion referred to as the rate loss constraint, in the form of an upper bound on the maximum rate loss of the primary user due to the secondary transmission, is proposed for primary transmission protection. In addition, assuming that some PUs are protected by the rate loss constraint, and some PUs are protected by the interference power constraint, the optimal power allocation strategy to maximize the rate of the cognitive radio system under such a hybrid protection to PUs together with a transmit power constraint is derived. Then, the relationship between the rate loss constraint and the interference power constraint is investigated, and it is shown by simulation that the cognitive radio system can achieve a significant rate gain under the proposed constraint compared with that under the conventional interference power constraint.

This paper considers a cognitive radio network where a secondary user shares the same narrow band with a primary user for transmission. Instead of adopting the conventional interference-power/interference-temperature constraint, this paper proposes a new type of constraint for the secondary user to protect the primary transmission, which limits the maximum outage probability of the primary transmission subject to the secondary user's interference to be below a prescribed target. Under this newly proposed constraint along with the average/peak transmit power constraint, the paper derives the optimal power allocation strategies over block-fading channels for the secondary user to achieve its outage capacity. It is shown by simulations that the derived power allocation strategies achieve substantial outage capacity gains for the secondary user over the conventional power control policies based upon the interference-temperature constraint, given the same primary user's outage probability constraint.

A novel signal structure is designed for a high data rate (HDR) Prerake UWB system, which uses orthogonal codes and chip-interleaving to suppress the inter-chip interference (ICI). On one hand, high data rate is achieved via superposition of symbols. On the other hand, the symbols are coded using the Walsh-Hadamard codes and interleaved on the chip level, which largely eliminates the ICI. The BER performance of the system is analyzed under imperfect channel estimation. Numerical results show that the HDR Prerake UWB system using the Walsh-Hadamard codes and chip-interleaving outperforms the conventional HDR Prerake UWB system using the random DS codes without ICI suppression under both perfect and imperfect channel estimation. Effect of the length of Walsh-Hadamard codes on the system performance is also discussed in detail.

In this paper, we consider a secondary link sharing the spectrum with a primary link in a fading cognitive radio (CR) network. Instead of applying the conventional interference power constraint at the primary user (PU) receiver for the secondary user (SU) to protect the primary transmission, we propose a new constraint on the maximum tolerable outage probability for the PU due to the SU transmission. Under the assumption that perfect instantaneous channel state information (CSI) on the SU channel, the channel from the SU transmitter to PU receiver, and the PU channel is available at the SU transmitter, we derive the optimal power allocation strategies to achieve the ergodic capacity of the SU fading channel. It is shown by simulations that the proposed power allocation strategies can achieve substantial capacity gain for the SU over that based on the conventional interference power constraint, for the same PU outage probability loss.

In this paper, we propose an iterative receiver for a multi-input multi-output (MIMO) two-way wireless relay system. The two-way relay system requires two time slots to accomplish one information exchange. Compared to the traditional one-way relay system, which demands four time slots to complete one information exchange, our system only uses half as many time slots. Our proposed iterative receiver consists of two loops. One is the minimum mean square error (MMSE)-based iterative soft interference cancellation (SIC) algorithm which is extended from the algorithm in to cover correlated noise environment incurred from the nature of signalling. The other is the Expectation Conditional Maximization (ECM)-based estimation algorithm. The MMSE-SIC algorithm provides the soft information of the transmitted signals and this information is transferred to the ECM-based estimation algorithm to update the channel information. Simulation results show that the performance of the iterative receiver proposed here is close to that given by perfect channel information with small number of iterations.

In this letter, the problem of training sequence design in a bi-directional relay network is investigated. The two nodes, Tx1 and Tx2, communicate with each other via a relay (RL). The RL receives the signals that are transmitted simultaneously from both nodes and then broadcasts the superposition back to the two nodes. Single carrier cyclic prefix (SCCP) is deployed in the transmission from the two nodes and the RL as well for combating intersymbol interference (ISI). We are interested in the channel estimation problem in this scenario. We propose a design of training sequences from two nodes to minimize the mean-square error (MSE) of the channel estimation according to zero forcing (ZF) criterion. We do not separate the links between each node to RL but incorporate them into the composite channels. Simulation results show that our design performance suffers only 1-dB loss in terms of bit-error rate (BER) as compared to the case with perfect channel information.

A cognitive radio network (CRN) is formed by either allowing the secondary users (SUs) in a secondary communication network (SCN) to opportunistically operate in the frequency bands originally allocated to a primary communication network (PCN) or by allowing SCN to coexist with the primary users (PUs) in PCN as long as the interference caused by SCN to each PU is properly regulated. In this paper, we consider the latter case, known as spectrum sharing, and study the optimal power allocation strategies to achieve the ergodic capacity and the outage capacity of the SU fading channel under different types of power constraints and fading channel models. In particular, besides the interference power constraint at PU, the transmit power constraint of SU is also considered. Since the transmit power and the interference power can be limited either by a peak or an average constraint, various combinations of power constraints are studied. It is shown that there is a capacity gain for SU under the average over the peak transmit/interference power constraint. It is also shown that fading for the channel between SU transmitter and PU receiver is usually a beneficial factor for enhancing the SU channel capacities.

The differentially-encoded, di-symbol time-division multiuser impulse radio (d2TD-IR) with delay-sum autocorrelation receivers is a low complexity, high efficiency short range wireless communication technology for infrastructure networks. The d2TD-IR system is designed with the assumption that the users are perfectly synchronized. In this letter, we propose a recursive algorithm of combined synchronization and power control. Computer simulation results show that the proposed algorithm has significant performance improvement over the algorithm, in which synchronization and power control are performed separately.

Transmitted-reference impulse radio (TR-IR) is a low complexity UWB system which is suitable for highly dispersive multipath channel. However, TR-IR requires a wideband analog delay line which has high complexity and high energy consumption. In this letter, we propose a digital eigen-based (EB) receiver which first converts the analog signal to digital signal and then demodulates the received signal in digital domain. Computer simulation results show that the proposed receiver can outperform the conventional autocorrelation receiver. We also proposed a monobit digital EB (MEB) receiver as a low complexity alternative to the EB receiver. The bit-error-rate performance of MEB receiver have also been studied theoretically to show the quantization effect in this letter.

In this paper, a new spectrum sharing model called sensing-based spectrum sharing is proposed for cognitive radio networks. This model consists of two phases: in the first phase, the secondary user (SU) listens to the spectrum allocated to primary user (PU) to detect the state of PU; in the second phase, SU adapts its transit power based on the sensing results. If the PU is inactive, the SU allocates the transmission power based on its own benefit. However, if the PU is active, interference power constraint is imposed in order to protect the PU. By studying the ergodic capacity of SU, we show that this spectrum sharing model can achieve a higher capacity of SU link and improve the spectrum utilization compared to conventional opportunistic spectrum access or simple spectrum sharing. Using the dual decomposition method, we find the optimal power allocation policies and the optimal sensing time for fading channels to achieve the ergodic capacity of the SU link considering both transmit and interference power constraints. Finally, the numerical results are presented to validate the analytical results.

In this correspondence, we derive a simplified description of the Han–Kobayashi rate region for the general interference channel. Using this result, we establish that the recently discovered Chong–Motani–Garg rate region is a new representation of the Han–Kobayashi region. Moreover, a tighter bound for the cardinality of the time-sharing auxiliary random variable emerges from our simplified description.

In this paper, the interference channel with common information (ICC), in which two senders need deliver not only private messages but also certain common messages to theircorrespondingreceivers, is investigated. An achievable rate region for such a channel is obtained by applying a superposition coding scheme that consists of successive encoding and simultaneous decoding. It is shown that the derived achievable rate region includes or extends several existing results for the interference channels with or without common information. The rate region is then specialized to a class of ICCs in which one sender has no private information to transmit, and a class of deterministic interference channels with common information (DICCs). In particular, the derived rate region is found to be the capacity region for this class of DICCs. Last, the achievable rate region derived for the discrete memoryless ICC is extended to the Gaussian case, in which a numerical example is provided to illustrate the improvement of our rate region over an existing result.

In this paper, we establish the capacity region of a class of deterministic interference channels with common information. For such a class of channels, each sender needs to transmit not only the private information but also certain common information to the corresponding receiver. Moreover, the channel outputs are deterministic with respect to given channel inputs.

New automatic classification algorithms are proposed for the imperfect rectangular QAM constellation with phase rotation. Our proposed algorithms are developed based on the two-dimensional Radon transform, and can effectively estimate the phase rotation and classify the modulation type of the received signals. Simulation experiments are performed and the results show that our proposed algorithms are successful even when the incoming signals are corrupted by additive white Gaussian noise (AWGN). As compared with the existing classification algorithm, our proposed algorithms can achieve satisfied performance in terms of probability of correct classification (PCC), and are more feasible to be adopted in practice.

The capacity region of a class of discrete memoryless interference channels is established. The setup is similar to the class of deterministic interference channels studied by El Gamal and Costa. However, we relax certain conditions that were imposed by El Gamal and Costa. The capacity region of this class of interference channels also includes the capacity region of the discrete memoryless interference channels with strong interference. Finally, we extend the result to the case where both transmitters have a common message to transmit.

The Cramer-Rao bounds (CRBs) of near field electromagnetic ranging (NFER) are derived for the cases of ranging and 2-D localization. From the derived CRBs, it is shown that the accuracies are dependent on the true location and frequency used, in addition to the signal-to-noise ratio. Ulitizing the derived bound for 2-D localization, the selection of frequency can be made to achieve the best average accuracy in different area sizes.

This correspondence studies coding strategies for a three-node relay channel. We start with the basic coding strategies of Cover and El Gamal: the relay decodes the source message and forward it to the destination (cooperation); the relay transmits its compressed channel outputs to the destination (facilitation); or the relay superimposes both cooperation and facilitation (generalized). In this paper, two new generalized strategies superimposing cooperation and facilitation are introduced and investigated on the general relay channel. The first strategy makes use of sequential backward (SeqBack) decoding while the second strategy makes use of simultaneous backward (SimBack) decoding. The achievable rate for the second strategy is shown to include that of the generalized strategy of Cover and El Gamal. Assuming zero-mean, jointly Gaussian random variables, the two new strategies give higher achievable rates than the generalized strategy of Cover and El Gamal for certain parameters on the Gaussian relay channel

We consider the two-user Z channel (ZC), where there are two senders and two receivers. One of the senders transmits information to its intended receiver (without interfering with the unintended receiver), while the other sender transmits information to both receivers. The complete characterization of the discrete memoryless ZC remains unknown to date. For the Gaussian ZC, the capacity has only been established for a crossover link gain of $1$. In this work, we study both the discrete memoryless ZC and the Gaussian ZC. We first establish achievable rates for the general discrete memoryless ZC. The coding strategy uses rate-splitting and superposition coding at the sender with information for both receivers. At the receivers, we use joint decoding. We then specialize the rates obtained to two different types of degraded discrete memoryless ZCs and also derive respective outer bounds to their capacity regions. We show that as long as a certain condition is satisfied, the achievable rate region is the capacity region for one type of degraded discrete memoryless ZC. The results are then extended to the two-user Gaussian ZC with different crossover link gains. We determine an outer bound to the capacity region of the Gaussian ZC with strong crossover link gain and establish the capacity region for moderately strong crossover link gain.

A new space-time block coded transmit antenna selection scheme over spatially correlated fading channels is presented. This scheme allows two or more transmit antennas to simultaneously use one radio frequency frontend. A system with four transmit antennas is considered in particular. The four antennas are selectively grouped into two subsets. Alamouti code is then applied on top of the subsets as if each was a single antenna. This scheme is shown to be more efficient than the conventional transmit antenna selection combined with Alamouti code in correlated channels. Moreover, it lowers the bitrate of the feedback channel.

We consider the two-user Gaussian zigzag channel, where there are two senders and two receivers. One of the senders transmits information to its intended receiver (without interfering with the unintended receiver) while the other sender transmits information to both receivers. We first establish achievable rates for the discrete memoryless zigzag channel under strong interference which can be extended to the Gaussian zigzag channel with strong and very strong crossover link gain (a2ges 1). We also determine an outer bound for the Gaussian zigzag channel under strong and very strong crossover link gain (a2ges 1). Moreover, we establish the capacity of the Gaussian zigzag channel under (strictly) strong crossover link gain (1 les a2les 1 + P1)

Near field electromagnetic ranging (NFER) can offer high localization accuracy from moderate precision measurements with inherent immunity against non-line-of-sight and multipath problems. This paper explores the factors affecting accuracy in ranging and 2-D localization using NFER by deriving the Cramer Rao bounds (CRBs). From the CRBs, it can be seen that besides the signal-noise ratio, the accuracy is dependent on the true location and the frequency used. Exploiting this property, ranging and maximum likelihood estimation (MEE) localization algorithms are developed for application of multiple frequencies to NFER to improve accuracy. Simulation results show that substantial improvement in accuracy is achieved for the algorithms over using a single frequency for NFER

This paper studies coding strategies for a three-node relay channel. We first review the basic coding strategies of Cover and El Gamal for the relay channel. Next, two new coding strategies superimposing cooperation and facilitation are developed. One of the coding strategies is shown to include the generalized strategy of Cover and El Gamal. For certain parameters of the Gaussian relay channel, the two new strategies give higher achievable rates than the generalized strategy of Cover and El Gamal

We present a statistical model for the characterization of ultra-wideband (UWB) channels for the outdoor office environment. The bandwidth is from 3-6 GHz and measurements are done for the line-of-sight (LOS) and non-line-of-sight (NLOS) cases. Small scale effects are modeled by the Saleh-Valenzuela (S-V) model with modifications on the ray arrival times and amplitude statistics to fit the empirical data. The ray arrival times are described by a mixture of Poisson processes while the amplitude statistics are follow a Nakagami distribution with the m parameter following a lognormal distribution. The parameters for the cluster and ray power-decay time constants, cluster and ray arrival times, mean excess delay and RMS excess delay are also extracted to define the channel model completely.

Digital image watermarks can be detected in the transform domain using maximum-likelihood detection, whereby the decision threshold is obtained using the Neyman-Pearson criterion. A probability distribution function is required to correctly model the statistical behavior of the transform coefficients. Earlier work has considered modeling the discrete wavelet transform coefficients using a Gaussian distribution. Here, we introduce a Laplacian model and establish via simulation that it can result in a better performance than the Gaussian model.

Operating in the 2.4 GHz unlicensed ISM band, a Bluetooth piconet inevitably encounters interference from other Bluetooth piconets. In the literature, the focus has been mainly on the analysis of the collision probability ( P/sub c/) of a Bluetooth packet. The destructive effect of packet collisions could be mitigated by the attenuation introduced by the propagation distance. We present a method to compute the packet error rate (PER) over distance in the presence of multiple Bluetooth piconets. The numerical results give insights on how to choose the optimum packet type in a multi-Bluetooth interference environment.

This paper analyses the feasibility of an enhanced EGPRS system allowing better integration of high QoS users (high data rate and time-sensitive applications) in the downlink. With the coming deployment of QoS guarantee in GPRS cellular networks, such users are expected to cause a significant capacity problem. Here we propose to distribute when possible the capacity needed for each high QoS user over several base-stations in order to minimize QoS degradation for other users within the network. The performance of such a scheme depends on the possibility for a mobile to be served jointly by several base-stations. Therefore feasibility is established through multiple base-stations joint coverage statistics: probability for a mobile user to be served simultaneously at a given location by several base-stations, and normalized joint coverage area are evaluated. Statistics of joint coverage are investigated for typical sectorized EGPRS layouts under lognormal shadowing. Influence of shadowing, network load and sectorization on the joint coverage statistics are presented. It is shown that under quite general circumstances and assumptions for system configuration and channel conditions high QoS is achieved when a mobile is served by multiple base-stations.

In this paper, we provide a new scheme for transmission of video information over wireless channels. This scheme is constructed by combining the prioritized discrete cosine transform (DCT) for video compression with multiple description codes based on forward error correction (FEC) codes. Reed-Solomon codes with different error correction abilities are applied to different parts of the progressive source bitstream, and finally these blocks are split into several equal descriptions for transmission. The prioritized DCT coder gives a wonderful progressive feature with less complexity and can be easily combined with the FEC based multiple description generation. We demonstrate via simulation that this scheme can improve the robustness of video transmission over wireless channels and allow video quality to degrade gracefully as channel conditions worsen.

This paper presents the error performance of turbo coded TCM (TTCM) when applied to wideband code division multiple access (WCDMA) vehicular channels. The IMT2000 standard for third generation (3G) mobile systems proposes rate 1/3 turbo coding for data rates above 32 kb/s. Data rates up to 384 kb/s in vehicular environments and up to 2 Mb/s in indoor environments can be achieved either by reducing the spreading factor (SF) or by multicode operation (or by a combination of both). Multicode operation, however, increases the cochannel interference, which necessitates the use of complex multiuser interference cancellers in 3G systems. In this paper, we examine a turbo TCM scheme, which has the potential to offer much higher spectral efficiency when used in WCDMA systems. The proposed scheme is based on a punctured turbo TCM mapped to 8 PSK constellation. The error performance of such a scheme is examined in WCDMA channels using appropriate channel impulse response models for vehicular environments and the simulation results reported. Results show that the error performance of the scheme considered by us is 1.8-2.1 dB inferior to that of the rate-1/3 turbo coding scheme, however, the spectral efficiency is increased threefold, which is quite attractive for transmission at higher data rates.

This paper presents the error performance of turbo coded TCM (TTCM) in WCDMA channels. Turbo coding has been proposed as one of the coding options, for high data rates above 32 kb/s, in the IMT2000 standard. High data rates up to 2 Mb/s are proposed to be achieved using a combination of spreading factor and multicode operation that uses multiple channels with additional spreading codes. This increases the cochannel interference, which necessitates the use of complex multiuser interference cancellers in 3G systems. We examine a turbo TCM scheme, which has potential to offer much higher spectral efficiency when used in WCDMA system thereby reducing the need for multicode operation and hence results in reduced cochannel interference. The proposed system utilizes a turbo TCM mapped to 8-PSK constellation that offers a spectral efficiency of 2 b/s/Hz which is thrice that of a rate-1/3 turbo coded QPSK scheme, albeit an E/sub b//N/sub 0/ degradation of 1.8 dB. The three times gain in the spectral efficiency when traded with this degradation is quite significant and attractive for transmission at higher data rates.

In this paper, we propose and investigate a new signature sequence scheme for asynchronous direct-sequence code-division multiple-access (DS-CDMA) communication systems. The new sequence set offers good mean-square cross-correlation (MSCC) properties in both even and odd correlation functions, which are important for system capacity, acquisition and demodulation performance in DS-CDMA systems. A new asynchronous phase-coded DS-CDMA system model is proposed. An analysis of the new system model is presented, and a new aperiodic cross correlation function is derived. The correlation properties of the new sequence set are presented and compared with those of the conventional PN sequence sets. Emphasis is placed on the average rather than the worst case performance. Numerical results show that MSCC value of the new sequence set is only about half of those of the conventional PN sequence sets. This may result in an improvement of 3 dB in the multiple access interference (MAI) performance.

The factorization properties of polynomials defined over finite integer rings and the associated direct sums are analyzed. The objective is to describe new computationally efficient algorithms for computing one and two dimensional convolution of data sequences defined over finite integer rings. The number theoretic transforms (NTTs) are a special case of the general theory presented.