In this paper, we focus on the performance imimprovement of the network coding (NC) based hybrid automatic repeat request chase combining (HARQ-CC) scheme. First, considering the joint detection method with the conventional log- likelihood ratio (LLR) calculation, we design the optimal pair of constellation mappings for bit error rate (BER) minimization. Furthermore, we propose a novel remapping-based joint detection algorithm: threshold- based optimal accumulation order selection (TH-OAOS) algorithm for LLR maximization to improve the system performance. The simulation results show that the proposed optimal constellation mappings significantly outperforms the conventional original mappings in terms of error performance. Moreover, the error performance of the proposed TH-OAOS algorithm for LLR maximization is far better than the case of the conventional LLR calculation.

Orthogonal frequency division multiplexing (OFDM) combined with the coordinated multi-point (CoMP) transmission technique has been proposed to improve performance of the receivers located at the cell border. However, the inevitable carrier frequency offset (CFO) will destroy the orthogonality between subcarriers and induce strong inter-carrier interference (ICI) in OFDM systems. In a CoMP-OFDM system, the impact of CFO is more severe because of the mismatch in carrier frequencies among multiple transmitters. To reduce performance degradation, CFO estimation and compensation is essential. For simultaneous estimation of multiple CFOs, the performance of conventional CFO estimation schemes is significantly degraded by the mutual interference among the signals from different transmitters. In this work, our goal is to propose an effective approach that can simultaneously estimate multiple CFOs in the downlink by using the composite signal coming from multiple base stations corresponding to CoMP transmission. Based on the Zadoff-Chu sequences, we design an optimal set of training sequences, which minimizes the mutual interference and is robust to the variations in multiple CFOs. Then, we propose a maximum likelihood (ML)-based estimator, the robust multi-CFO estimation (RMCE) scheme, for simultaneous estimation of multiple CFOs. In addition, by incorporating iterative interference cancellation into the RMCE scheme, we propose an iterative scheme to further improve the estimation performance. According to the simulations, our scheme can eliminate the mutual interference effectively, approaching the Cramer-Rao bound performance.

In cognitive radio (CR) networks, to avoid collision with the primary users, the secondary users (SUs) must sense the existence of the primary signals in each fixed time period, before transmitting their signals. For a multiple primary channels (PCs) scenario, the SUs are generally allowed to utilize all the idle PCs in order to maximize the system throughput. In the conventional approach, the SUs sense all the PCs to maximize the number of channels available for data transmission. However, the increase in the number of PCs sensed by the CR network will increase the time consumption in the sensing phase, and thus degrades the time available for data transmission. The goal of this work is to find the pre-determined optimal number of channels utilized for data transmission to maximize the system throughput. Compared to the real-time adaptation approach, our proposed scheme can be easily applied to practical systems and achieve a throughput very close to the ultimate system throughput, but without the need of real-time computation burden.

In time-varying flat-fading environments, time domain channel correlations are required for accurate channel estimation and interpolation. However, the correlation property, which depends on the Doppler spread, is hard to be extracted from corrupted channel responses within a short channel estimation interval. In this work, based on an approximate channel model via the Taylor expansion, we propose a joint channel and Doppler spread estimation scheme over time-varying flat-fading channels. It employs the expectation-maximization (EM) algorithm to iteratively attain the maximum-likelihood (ML) channel and Doppler spread estimates. Simulation results show that the proposed scheme achieves accurate performance of both channel estimation and Doppler spread estimation within a short estimation interval.

Orthogonal frequency division multiplexing (OFDM) combining with the coordinated multi-point (CoMP) transmission technique has been proposed to improve performance of the receivers located at the cell border. However, the inevitable carrier frequency offset (CFO) will destroy the orthogonality between subcarriers and induce strong inter-carrier interference (ICI) in OFDM systems. In a multi-point transmission system, the impact of CFO is more severe because of the mismatch of carrier frequencies among multiple transmitters. To relieve the performance degradation, CFO estimation and compensation is essential. For simultaneous estimation of multiple CFOs, the performance of conventional CFO estimation schemes is significantly degraded by the mutual interference among the signals coming from multiple transmitters. In this work, we propose a maximum likelihood (ML)-based estimator for simultaneous estimation of multiple CFOs, and design the training sequences that are robust to the variation in CFOs. According to the simulations, our scheme can eliminate the mutual interference effectively, approaching the mutual interference-free performance.

The cooperative information aggregation (CIA) scheme for distributed estimation was proposed in our past research considering the realistic wireless sensor network (WSN) environments. In the existing CIA scheme, a multi-bit quantizer is applied at all nodes, however, each node only transmits one predetermined bit of its quantized observation to the fusion center (FC) to economize the energy expense and the communication bandwidth. In this work, the CIA based distributed sequential estimation (CIAS) scheme is proposed. In the proposed CIAS scheme, an instruction message is designed to be sent from the FC to the nodes sequentially to guide each node's transmitted bit selection. By sequentially polling the information bits from the nodes, the vote processes performed at the FC for the data fusion may be early terminated depending on the accumulative received information bits, and thereby numerous resource bits can be conserved in the estimation procedure. We design two algorithms for the CIAS scheme as well to pursue the promotion of energy conservation and estimation achievement. In the simulation results, considerable energy saving and estimation performance improvement in the proposed CIAS scheme are demonstrated, in comparison with the existing CIA scheme.

In orthogonal frequency division multiplexing (OFDM) systems, high peak-to-average power ratio (PAPR) is one of the major technical challenges, which brings serious impact on the hardware implementation. In literature, many schemes have been proposed for PAPR reduction, wherein the selective mapping (SLM) scheme is the most popular and widely discussed approach. However, SLM suffers from very high computational complexity because of the requirement of a large number of inverse fast Fourier transformation (IFFT) operations. In this work, we propose a modified SLM approach based on time-domain sub-block conversion matrices to reduce the computational complexity due to multiple IFFTs. This scheme is modified from the conversion matrix scheme. By dividing the frequency-domain signals into multiple sub-blocks, the number of the valid conversion matrices can be increased, and thus more candidate signals are available for PAPR reduction. By applying our scheme, the number of candidate signals can be increased from 12 in the original conversion matrix scheme to 28 and 128 for the two-subblock and four-subblock cases, respectively. According to the simulations, the PAPR reduction performance can be improved by 0.2 dB - 0.9 dB.

The time domain maximum likelihood (ML) Doppler spread estimation for OFDM systems provides an accurate estimation performance; however, it results in a much higher computation cost. We propose a low-complexity ML Doppler estimator based on a well-designed preamble sequence along with a suboptimal ML (SML) method to reduce the computational complexity of the optimal ML scheme. Because of the proposed preamble sequence, the received samples are able to be partitioned into uncorrelated subsets, yielding a substantial complexity reduction for the SML scheme. The simulation results show that the proposed estimator provides accurate and efficient Doppler spread estimation.

Wireless sensor networks have been used recently to obtain forensic evidence. One of the basic principles of obtaining forensic evidence is to maintain the integrity of the evidence. To increase the probability of retaining data integrity, the data replication strategy was proposed for unattended wireless sensor networks (UWSN), wherein the data integrity was quantified by data survival rate. However, the distribution of multiple data replicas may expose the location information of some critical nodes, thereby resulting in a high possibility of being attacked by the adversary. In this paper, we study the trade-off between the data survival rate and the location privacy of a critical node in an UWSN. Obviously, the increase in the number of data replicas can improve the data survival rate, but could severely degrade the location privacy of a critical node. Based on the captured data replicas, we propose three location estimation algorithms, the coordinate median, average of overlapping area and expectation-maximization approaches. The location estimation performance of the proposed schemes is evaluated and the trade-off between the data survival rate are investigated. According to the simulation results, the location privacy degrades severely with the increase in the number of data replicas.

To meet the growing demand for multimedia services, Multimedia Broadcast/Multicast Service (MBMS) was proposed to enhance bandwidth efficiency in wireless communication systems. Although MBMS supports multimedia streams with several resolutions, streams with different resolutions are treated as separate services and transmitted upon independent radio resources, resulting in inefficient resource utilization. At the receiver, some valuable information embedded in the higher-resolution channels is not utilized to enhance the reception of the data stream in a lower resolution channel. In this work, we propose a multilevel coupling modulation (MCM) scheme aimed to improve the overall system throughput and to extend the service coverage of the multi-resolution MBMS in orthogonal frequency division multiplexing (OFDM) systems. The proposed MCM scheme can fully utilize all the usable information conveyed in different channels, thereby improving the receiving performance. In addition, we derive the symbol error rates of the proposed MCM scheme, in the AWGN and frequency-selective fading channels, for performance evaluation. The analytical and simulation results demonstrate that the proposed MCM scheme can substantially enhance the receiving performance, service accessibility and overall system throughput of multi-resolution MBMS in OFDM systems.

In OFDM systems, carrier frequency offset (CFO) between the transmitter and the receiver destroys the orthogonality among subcarriers and induces strong inter-carrier interference (ICI). For the CFO estimation schemes based on frequency-domain pilot signals, the estimation performance is degraded and bounded by the ICI. In this work we propose a novel CFO estimation scheme - PTA-based with ICI elimination (PTA-IE), to improve the CFO estimation performance. By applying an iterative process, the CFO estimation performance can be progressively enhanced, attaining the best achievable performance without ICI. Our proposed scheme can benefit not only the CFO estimation performance but also the demodulation performance on data subcarriers. Moreover, the proposed scheme has low computational complexity without the need of matrix inversion.

In this work, we propose a sequential fusion scheme for distributed detection in an inhomogeneous sensing environment. More specifically, the transmissions of sensors are ordered according to the observation quality and the communication channel quality to reduce energy consumption in wireless sensor networks. We devise the corresponding stopping and decision rules, as well as two transmission ordering rules, based on the log-likelihood ratio and mutual information, respectively. The simulation results demonstrate that the proposed scheme can reduce the required number of transmissions substantially, while achieving the same detection performance as the conventional maximum a posteriori probability fusion scheme.

In this work, we analyze the throughput, delay, and energy efficiency of random access sensor networks that employ Slepian-Wolf distributed source coding (DSC) and study the impact of MAC protocol design on these performances. Suppose that N sensors observe correlated information from the environment and that their local data are sent to a sink node through direct transmission links. To eliminate data redundancy, we allow sensors to encode their local messages using the Slepian-Wolf DSC method. We assume that sensors are ordered sequentially and that each sensor's message is compressed by exploiting the joint data statistics between itself and the sensors earlier in the sequence. Due to properties of DSC, a message can be decoded only if all messages transmitted by sensors earlier in the sequence are successfully decoded. The loss of one message may cause failure in decoding many other messages. Hence, the sensors' messages are not of equal importance and should be given different transmission priorities by the MAC. Based on the properties of DSC, we provide analytical tools to study the throughput, delay, and energy efficiency of slotted ALOHA random access protocols. Utilizing these tools, we compare between the performance of different transmission probability assignments and study the impact of MAC protocol design on the performance of these systems. Furthermore, an adaptive MAC protocol is also proposed to improve upon the throughput and delay of the original system.

In recent years, the ubiquity of communication networks speed up the development of wireless network and the Internet applications. In addition to the common service provided by the telecommunication enterprise, how to connect some distinct users to form a network which allow them to deal with their own works is a popular topic that many scholars engage in. When constructing the network, the key management is the most important problem that each system has to solve. There are many key agreement protocols which are non-hierarchical. However, the hierarchy is ubiquitous in our real life. In this paper, we have achieved a verifiable hierarchical key derivation scheme using the elliptic curve cryptography and the bilinear mapping function which can achieve the same security level but use less bit number when comparing to the RSA system.

PAPR is one of the major drawbacks for the widely adopted communication technique, OFDM (orthogonal frequency dividing multiplexing). There are a lot of researches proposed to reduce the PAPR at the cost of either performance degradation or bandwidth inefficiency. In this paper, a cross-layer design for joint PAPR reduction and multi-resolution resource allocation is introduced, which has neither performance degradation nor side information. The variability of multi-resolution data in both envelopes and phases can help the PAPR reduction via resource allocations. And the number of searches of candidate signals with different resource allocations is analyzed. The simulation results show that the PAPR is substantially reduced by the proposed scheme without any side information and modification in receivers.

The multi-resolution multicast service is an emerging service for future generation communication systems, supporting different service qualities for receivers with different capabilities. Under such a scenario, the radio resource arrangement becomes very complex but is important in order to enhance the overall system throughput. For multi-resolution multicast OFDM systems, we proposed an adaptive scheme for radio resource allocation combined with the diversity mechanism. Moreover, considering the feasibility for real-time applications, the proposed scheme is simplified into a two-stage algorithm. The simulation results show that the proposed algorithm achieves significant performance improvement not only in terms of the total system throughput but also for the fairness issues.

For distributed estimation in wireless sensor networks (WSNs), the estimation performance suffers from the presence of observation and communication noise, as well as the limited communication bandwidth between the sensor nodes (SNs) and the fusion center (FC). In this work, we propose an efficient distributed estimation scheme for WSNs, improving both the bandwidth and energy efficiency. In the proposed scheme, a multi-bit uniform quantizer with Gray codeword mapping is applied at each node. For each node, however, only one bit is chosen for transmission to the FC, in order to save the energy consumption and bandwidth utilization. By carefully pre-arranging the transmitted bits among all nodes, the information bits received at the FC can be successfully aggregated and fused to obtain the estimated signal and to overcome the impairment caused by the communication channel. The transmitted bits arrangement is formulated as a constrained optimization problem for resource allocation, with the object of minimizing the estimation mean square error (MSE) at the FC.

In this work, the sequential fusion scheme is used to save the energy consumption for events detection in wireless sensor networks (WSNs). The fusion center (FC) sequentially accumulates the information forwarded by nodes, and broadcasts a termination message to stop the transmission of nodes when the accumulated information is enough for decision-making. Thus the average number of forwarded messages, as well as the average energy consumption, can be significantly reduced. Since the number of sensor nodes is generally limited, the truncated sequential probability ratio test (TSPRT) is applied at the FC. The main goal of this paper is to propose analytical approaches, for both centralized and decentralized detection, to determine the thresholds for TSPRT. According to the simulation results, with little performance degradation, the average number of transmissions can be greatly reduced compared with the nonsequential fusion scheme.

Proper Power allocation can improve energy efficiency in wireless sensor networks (WSNs). Previous works considered only the channel statistics and did not take the instantaneous observations into consideration. Applying the instantaneous quality of an observation to the transmission power control of a node can improve the overall energy efficiency. In this work, we proposed nearly optimal power allocation schemes based on the instantaneous observation quality in each node for distributed detection in WSNs. The instantaneous quality of an observation is related to the log-likelihood ratio (LLR) of the signal observed by a node. According to the simulation results, at least 20 % of energy can be saved when compared to the equal power allocation scheme.

Mobile location tracking based on the received signal strength (RSS) is known to be easily influenced by the shadowing effects in wireless propagation channels. In this paper, we exploit the correlation among shadowing losses at adjacent locations to improve the performance of location tracking. A location tracking algorithm consisting of a maximum likelihood estimator and a Kalman filter is proposed to jointly track the mobile location and the shadowing losses via the RSS. Under a shadowed propagation environment, the simulation shows that, without knowing the underlying mobility model but only the target's speed information, the shadowing tracking furnishes worthful information for the location tracking algorithm, and the proposed method thus provides acceptable performance both for the location and shadowing tracking.

The maximum likelihood (ML) Doppler spread estimator provides an accurate estimation performance; however, it results in a much higher computation cost. In this work, we propose a time-domain approximate-ML estimator that significantly reduces the computational complexity of the ML estimator over a flat Rayleigh fading channel. Simulation results show that the proposed method nearly achieves the exact ML performance. Moreover, by using a small number of observation samples, our proposed method gives almost unbiased Doppler spread estimation for low to medium user mobility.

Code shift keying (CSK) was proposed to increase the transmission efficiency of DSSS systems, and to overcome the spreading gain versus data rate limitation. However, CSK modulation provides no multi-access capability, and degrades the flexibility of a spread spectrum system. In this work, a generalized M-ary DSSS modulation scheme, spreading code phase shift keying (SCPSK), is proposed to improve the system flexibility, and to provide the multi-access capability. This scheme involves switching the spreading code phase in accordance with the incoming data. The union bound of the symbol error probability, in an AWGN channel exposed to multi-user interference, are derived for performance evaluation. Furthermore, the performance of M-SCPSK in a multipath fading channel is investigated via simulation and compared with the conventional DSSS-BPSK scheme.

Network sensing coverage and network lifetime are the two major performance metrics for WSNs. Different data forwarding/routing mechanisms lead to different amounts and different distributions of energy consumption in a network. Moreover, nodes at different locations will suffer from different message forwarding burdens, either due to the amounts of forwarding messages or due to the required transmission power. In this work, we focus on the node deployment problem for large-scale randomly distributed WSNs, and proposed a non-uniform node deployment strategy, the IFA-based deployment strategy, for the multi-hop routing scenario. The sensing coverage, message forwarding and energy consumption issues are well examined and taken into consideration in our proposed deployment strategy. The iterative algorithm that figures out the optimal node density distribution fitting to the energy consumption distribution has been devised. Simulation results show that the proposed IFA-based deployment strategy can significantly improve the sensing coverage performance of a WSN.

In order to prevent inter-carrier interference (ICI), carrier frequency offset (CFO) estimation is essential and crucial for OFDM systems. Conventional fractional CFO estimation can be classified into two categories: the pilot tone-aided (PTA) schemes and the cyclic prefix-based schemes (CPB). In addition to the subcarriers dedicated for channel/frequency estimation, data subcarriers are also candidates that may be potentially used to improve the CFO estimation. In this work, we propose novel data-subcarrier aided CFO estimation algorithms, without the need of demodulating the data in advance, for M-PSK data modulated OFDM systems. According to the simulation results, it is found that the proposed algorithms can significantly improve the CFO estimation performance at the cost of an increase in computational complexity.

In mobile radio environments, the shadowing effects corresponding to a mobile station (MS) vary with time and the received carrier-to-interference power ratio (CIR) changes accordingly. From the service quality prediction viewpoint, it is worthwhile to investigate the spatial correlation property of the received CIR. This paper focuses on investigating the spatial correlation property of the CIR for the down-link of CDMA systems. The probability density function and the outage probability of the predicted CIR, conditioning on the current received CIR, have been derived for performance evaluation and prediction. According to the simulation results, our proposed model can precisely characterize the spatial correlation property of the CIR.

Channel estimation using preamble symbols is very important for demodulation and dynamic resource allocation in OFDM systems. However, if there is an interference source present, the preamble symbols may be corrupted by the interference. This will spoil the accuracy of channel estimation, and will result in severe degradation in the performance of the entire data frame. This work exploits the feasibility of introducing time- domain redundancy into preamble symbols to improve the estimation performance in multi-access interfering environments. Based on this time-domain redundancy property we propose an adaptive select and replace (ASR) scheme to either partially or completely eliminate the interference in the time-domain. By applying the proposed methods, multi-access interference can be efficiently eliminated. Even when there is no interference present, the proposed methods can still improve the estimation performance in a low frequency-selective channel.

Multi-band OFDM (MB-OFDM) UWB system was proposed for the applications of wireless personal area networks (WPANs). If the user mobility is concerned, handoff from a piconet to neighboring piconets is unavoidable. There are only few works considering soft handoff in OFDM systems. In this work, a novel soft handoff strategy for the MB-OFDM system is proposed. The system performance is analyzed and simulations are performed. Two receiving schemes, FixedFilter and DynamicFilter, are considered. Both FixedFilter and DynamicFilter improve the system performance. DynamicFilter is a little more complicated, but it provides larger performance gain. Finally, soft handoff can be achieved in the MB-OFDM system.

The reliability and delay of Slepian-Wolf distributed source coding (DSC) in sensor networks is analyzed under the random access setting. Consider a network of N sensors that observes correlated information from the environment and sends the local data to a central processor through direct transmission links. Due to the low message rate in sensor networks, we adopt the slotted ALOHA random access protocol where the time is divided into synchronized time slots and each sensor is allowed to access the time slots with independent probabilities. To eliminate the redundancy in the transmitted data, the sensors encode the local messages based on the Slepian-Wolf DSC method. Specifically, we assume that the sensors' message are encoded with a sequential dependency among each other and, thus, must be decoded one after the other such that the decoding of a particular message is reliant on the successful decoding of all the messages encoded earlier in the sequence. In this case, the loss of one message may result in the failure of other messages and the delay in the successful decoding of a particular message also varies from sensor to sensor. In this work, we analyze the performance of Slepian-Wolf DSC in random access networks in terms of the rate of successful decoding and the average delay of each message. Specifically, we propose and compare different transmission probability assignments for DSC in the ALOHA network and emphasize the importance of the MAC design.

Ultra-wideband (UWB) communication systems are generally applied to short-range wireless communications. In order to achieve higher rates or to support multiple access capabilities, direct sequence spread spectrum (DSSS) techniques have been introduced to UWB systems, and multiple pulses corresponding to a certain pseudo-noise (PN) code are transmitted to represent a symbol. In addition, the concept of M-ary code shift keying (M-CSK) was introduced into DSSS systems to achieve higher rates. In this work, we propose an M-CSK modulation technique based on the large set of Kasami sequences since it possesses good code properties, including a large code set size and low cross correlations. The modulation and demodulation schemes are developed, and the system performance in additive white Gaussian noise (AWGN) and UWB channels exposed to multiple user interference is investigated thoroughly. It was found that the Kasami M-CSK modulation is superior to other M-CSK modulation schemes in the bandwidth efficiency, and therefore a higher data rate can be achieved. Furthermore, based on our proposed demodulation scheme, the hardware complexity of receivers can be greatly reduced to O(M1/3), and the implementation of receivers for a very large M becomes feasible.

Sensing coverage is an important issue for sensor networks, since it is viewed as one of the critical measures of performance offered by a sensor network. The design of a routing protocol is generally independent of the sensing coverage issue. Since some nodes may become invalid after they have used up their own energy resource, the achievable sensing coverage will gradually degrade as time passes. Different routing protocols may motivate different distributions of energy dissipation among nodes, and thus induce different changes in the network topology after some nodes have died out. This implies that different routing protocols will lead to different sensing coverage when some nodes are no longer available. Considering the impact on the sensing coverage of a network, we have proposed coverage-preserving routing protocols which are modified from the LEACH and virtual grid routing protocols. These proposed protocols can substantially improve the performance of sensing coverage. According to the simulation results, the sensing coverage degradation of the coverage-preserving protocols is slower than that of the other baseline protocols. For the time duration maintaining the network coverage over 50%, a gain of 20% in overall sensing coverage can be obtained by using the coverage-preserving protocols.

Sensing coverage is one of the most important issues for sensor networks. Since some nodes may become invalid after they have used up their own energy resource, the achievable sensing coverage will gradually degrade as time passes. Different routing protocols may motivate different distributions of energy dissipation among nodes, and thus induce different changes in the network topology after some nodes have died out. This implies that different routing protocols will lead to different sensing coverage when some nodes are no longer available. Considering the impact on the sensing coverage of a network, we have proposed coverage-preserving routing protocols modified from the LEACH and virtual grid routing protocols. These proposed protocols can substantially improve the performance of sensing coverage. According to the simulation results, a gain of 20% in overall sensing coverage can be obtained for the time duration maintaining the network coverage over 50%.

Link stability is an important metric for the routing issue in mobile ad hoc networks (MANETs). In order to establish and maintain a reliable route for multi-hop routing in MANETs, the prediction of the link stability in future states is essential and advantageous. In this paper, we propose a new link stability prediction method based on current link-related or user-related information in shadowed environments. A more realistic user mobility model and a realistic propagation model are taken into consideration. According to the numerical and simulation results, it is found that the proposed method can accurately predict the link stability for different environment and mobility conditions. The prediction results can be regarded as a measure of the link stability, and can be applied to the applications, such as link performance prediction, system performance analysis, service quality prediction and route search. Furthermore, the impact of different mobility information on the accuracy of link stability prediction is also evaluated to assess the importance of the knowledge of mobility information.

Code phase shift keying (CPSK), an M-ary direct sequence spread spectrum (DSSS) modulation scheme, was proposed to increase the transmission efficiency of DSSS systems. Moreover, the M-SCPSK modulation scheme was proposed to provide multi-access capability and to increase the system flexibility. In this work, the correlative M-SCPSK modulation scheme, a type of memory modulation, is proposed to improve the system performance, and the performance in an AWGN channel exposed to multi-user interference is investigated. Based upon this correlative attribute, the Viterbi decision algorithm is applied to the demodulation, thereby greatly improving the system performance. According to the simulation results, the improvement is at least 2.7 dB in Eb/N0with one symbol memory.

Shadow fading, an inevitable phenomenon caused by obstructions in the propagation path, will cause large variations in the received signal strength for mobile radio environments. The spatial correlation of the shadowing effects is exponentially decayed by the increase in distance between any two separate positions. Variations in the shadowing effects are generally modeled as a Gaussian-Markov stochastic process. In this work, two Gaussian-Markov stochastic models have been proposed to characterize the spatial correlation properties and the variations in the total co-channel interference (CCI) as well as in the carrier-to-interference ratio (CIR) for downlink channels in mobile cellular systems. The numerical and simulation results show that these two models precisely characterize the spatial correlation properties of total CCI and CIR; good accuracy is guaranteed for different propagation environments, and the estimation errors for the standard deviations of the variations are limited to about 0.2 dB. The proposed models can be applied to the applications, such as the design of handoff schemes, link performance prediction, link adaptation control, and performance simulations

Shadowing fading, an inevitable phenomenon caused by obstructions in the propagation path, causes large variation in the received signal strength for mobile radio environments. The spatial correlation of the shadowing effects is exponentially decayed with the increase of distance between any two separate positions. The variation of the shadowing effects is generally modeled as a Gaussian-Markov stochastic process. In this work, two Gaussian-Markov stochastic models are proposed to characterize the spatial correlation properties and the variations of the total co-channel interference (CCI) and the carrier-to-interference ratio (CIR) for mobile cellular systems. The numerical and simulation results show that these two models can characterize the spatial correlation properties of the total CCI and the CIR very well. These models can be applied to applications such as handoff scheme design, link performance prediction, link adaptation control, and performance simulations.

This paper examines the feasibility of adding a personal communication network (PCN) to a frequency band which is already allocated to fixed-service microwave systems. To achieve this goal, spread spectrum techniques are used to spread narrowband PCN signals into wideband. The forward and reverse link performance of PCN users under the influence of the microwave system and the influence of PCN users on the microwave system are both examined. It is proven that spectrum sharing between the PCN network and microwave systems is indeed feasible. Although our analysis is done based upon the consideration of only one microwave system, it can be easily extended to allow the appearance of two or more microwave systems.

A study on the use of direct sequence spread spectrum techniques to reduce the damage caused by multipath interference in random accessed mobile packet radio networks is conducted. Basically the reception of a packet is affected by three types of interference: channel noise, multipath interference, and multiuser interference. To reflect reality, signal capture due to near-far field effect shall be incorporated in the analysis. Two types of capture effect are considered. Our results show that spread spectrum greatly reduces the multipath and multiuser interference at the expense of channel bandwidth. Furthermore, the two types of capture effect behave quite differently. One of them seems too optimistic and behaves counter-intuitively.>