Satellite-terrestrial integrated networks (STINs) are promising architecture for providing global coverage. In STINs, full frequency reuse between a satellite and a terrestrial base station (BS) is encouraged for aggressive spectrum reuse, which induces non-negligible amount of interference. To address the interference management problem in STINs, this paper proposes a novel distributed precoding method. Key features of our method are: i) a rate-splitting (RS) strategy is incorporated for efficient interference management and ii) the precoders are designed in a distributed way without sharing channel state information between a satellite and a terrestrial BS. Specifically, to design the precoders in a distributed fashion, we put forth a spectral efficiency decoupling technique, that disentangles the total spectral efficiency function into two distinct terms, each of which is dependent solely on the satellite’s precoder and the terrestrial BS’s precoder, respectively. Then, to resolve the non-smoothness raised by the RS strategy, we approximate the spectral efficiency expression as a smooth function by using the LogSumExp technique; thereafter we develop a generalized power iteration inspired optimization algorithm built based on the first-order optimality condition. Simulation results demonstrate that the proposed method offers considerable spectral efficiency gains compared to the existing methods.

In this paper, we propose a novel architecture for a lens antenna array (LAA) designed to work with a small number of antennas and enable angle-of-arrival (AoA) estimation for advanced 5G vehicle-to-everything (V2X) use cases that demand wider bandwidths and higher data rates. We derive a received signal in terms of optical analysis to consider the variability of the focal region for different carrier frequencies in a wideband multi-carrier system. By taking full advantage of the beam squint effect for multiple pilot signals with different frequencies, we propose a novel reconfiguration of antenna array (RAA) for the sparse LAA and a max-energy antenna selection (MS) algorithm for the AoA estimation. In addition, this paper presents an analysis of the received power at the single antenna with the maximum energy and compares it to simulation results. In contrast to previous studies on LAA that assumed a large number of antennas, which can require high complexity and hardware costs, the proposed RAA with MS estimation algorithm is shown that meets the requirements of 5G V2X in a vehicular environment while utilizing limited RF hardware and has low complexity.

In this paper, we study a max-min fairness (MMF) beamforming design method in a multiple-user downlink network utilizing rate-splitting multiple access (RSMA). A main objective of the MMF problem is to provide users with uniformly good rates by appropriately adjusting the rates of common and private message, respectively. Since the optimization of the objective function with respect to beamforming vectors and common message rates for each users is intricate and difficult to solve, we divide a whole problem into two stages. In the first stage, we utilize the LogSumExp (LSE) approximation technique and the novel generalized power iteration (GPI) framework to find a beamforming vector given a common message portion. In the second stage, we allocate common message rate for each user for given fixed beamforming vectors. By repeating these two stages, we jointly design the optimal beamforming vectors and common message rates for each users. Through simulation, we show that our method outperforms existing approaches in terms of the worst-case user's rate with extremely low complexity cost.

Positioning accuracy is a critical requirement for vehicle-to-everything (V2X) use cases. Therefore, this paper derives the theoretical limits of estimation for the position and orientation of vehicles in a cooperative vehicle-to-vehicle (V2V) scenario, using a lens-based multiple-input multiple-output (lens-MIMO) system. Following this, we analyze the Cramér-Rao lower bounds (CRLBs) of the position and orientation estimation and explore a received signal model of a lens-MIMO for the particular angle of arrival (AoA) estimation with a V2V geometric model. Further, we propose a lower complexity AoA estimation technique exploiting the unique characteristics of the lens-MIMO for a single target vehicle; as a result, its estimation scheme is effectively extended by the successive interference cancellation (SIC) method for multiple target vehicles. Given these AoAs, we investigate the lens-MIMO estimation capability for the positions and orientations of vehicles. Subsequently, we prove that the lens-MIMO outperforms a conventional uniform linear array (ULA) in a certain configuration of a lens’s structure. Finally, we confirm that the proposed localization algorithm is superior to ULA’s CRLB as the resolution of the lens increases in spite of the lower complexity.

We derive theoretical limits of estimation on the position and orientation of vehicles equipped with lens based arrays in cooperative Vehicle to Vehicle (V2V) scenario. Then, we analyze and compare its performance with conventional linear array. We determine a received signal of a lens-embedded antenna array and V2V geometric model, with which we next derive the Cramér-Rao lower bound (CRLB) on position and orientation estimation. We verify that a lens-based multiple-input multiple-output (MIMO) outperforms a conventional uniform linear array (ULA) in a certain constraint of a lens’s structure.

Physical layer security is a useful tool to prevent illegal wiretapping to confidential information. In this paper, we consider a generalized model of conventional physical layer security, referred as hierarchical information accessibility (HIA). A main feature of the HIA model is that a network has a hierarchy in information access, wherein decoding feasibility is determined by each user’s priority. Under this HIA model, we formulate a sum secrecy rate maximization problem with regard to precoding vectors. This problem is challenging since multiple non-smooth functions are involved into the secrecy rate to fulfill the HIA conditions and also the problem is non-convex. To address the challenges, we approximate the minimum function by using the LogSumExp technique, thereafter obtain the first-order optimality condition. One key observation is that the derived condition is cast as a functional eigenvalue problem, where the eigenvalue is equivalent to the approximated objective function of the formulated problem. Accordingly, we show that finding a principal eigenvector is equivalent to finding a local optimal solution. To this end, we develop a novel method called generalized power iteration for HIA (GPI-HIA). Simulations demonstrate that the GPI-HIA significantly outperforms other baseline methods in terms of the secrecy rate.

In this paper, we consider a hierarchical information accessibility (HIA) model, which generalizes conventional physical layer security. In the considered model, multiple layers with different security priorities are assumed, where only the users in a higher priority layer are permitted to decode the message intended to lower priority layers. To maximize the sum secrecy rate of the considered system, we formulate an optimization problem with regard to precoders. To solve the formulated problem, we first approximate the objective function by using the LogSumExp technique and show that finding a local optimum is equivalent to finding a leading eigenvector of the first-order optimality condition of the reformulated problem. Accordingly, we propose a novel algorithm called generalized power iteration for hierarchical information accessibility (GPI-HIA) to obtain a solution. Via simulations, we demonstrate that the proposed method significantly outperforms other baseline schemes under the considered HIA scenario.

This paper presents novel ultrareliable and low-latency communication (URLLC) techniques for URLLC services, such as Tactile Internet services. Among typical use cases of URLLC services are teleoperation, immersive virtual reality, cooperative automated driving, and so on. In such URLLC services, new kinds of traffic such as haptic information including kinesthetic information and tactile information need to be delivered in addition to high-quality video and audio traffic in traditional multimedia services. Furthermore, such a variety of traffic has various characteristics in terms of packet sizes and data rates with a variety of requirements of latency and reliability. Furthermore, some traffic may occur in a sporadic manner but requires reliable delivery of packets of medium to large sizes within a low latency, which is not supported by current state-of-the-art wireless communication systems and is very challenging for future wireless communication systems. Thus, to meet such a variety of tight traffic requirements in a wireless communication system, novel technologies from the physical layer to the network layer need to be devised. In this paper, some novel physical layer technologies such as waveform multiplexing, multiple-access scheme, channel code design, synchronization, and full-duplex transmission for spectrally efficient URLLC are introduced. In addition, a novel performance evaluation approach, which combines a ray-tracing tool and system-level simulation, is suggested for evaluating the performance of the proposed schemes. Simulation results show the feasibility of the proposed schemes providing realistic URLLC services in realistic geographical environments, which encourages further efforts to substantiate the proposed work.

In this paper, we propose a low complexity direction of arrival (DoA) estimation algorithm that operates in radio frequency (RF) lens-embedded millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems. In mmWave system, to compute the beamforming weighting coefficients in real-time, precise DoA estimation with low complexity is essential. We first investigate the conventional DoA estimation algorithms in mmWave MIMO systems and evaluate its performance. Then we introduce the Power pROfile Based Estimation (PROBE) algorithm for DoA estimation that operates in the RF lens-embedded system. We elaborate on the computational complexity of each algorithm in terms of the number of multiplication operations. We show that the proposed algorithm has a significant performance advantage in terms of estimation accuracy over other conventional algorithms in a complexity-constrained environment.

Summary Distributed compressive sensing (DCS) usually improves the signal recovery performance of multi‐signal ensembles by exploiting both intra‐ and inter‐signal correlation and sparsity structure. However, the existing DCS had proposed for a very limited ensemble of signals that has only single common information. This paper proposes a generalized DCS (GDCS) framework which can improve sparse signal detection performance given arbitrary types of common information, which are classified into full common information and partial common information after overcoming against existing limitation. Specifically, the theoretical bound on the required number of measurements under the GDCS is obtained. We also develop a practical algorithm to obtain benefits using the GDCS. At the end of this paper, it simply summarizes the potential security issues when it gets all sensing information in a sensor network. Finally, numerical results verify that the proposed algorithm reduces the required number of measurements for correlated sparse signal detection compared to the DCS algorithm. This research lays down the basis for efficient distributed signal detection so that it can improve the detection performance or it can detect the signal reliably when the number of signal observations is limited.

Full Duplex(FD) network is considered as efficient scheme which could service both downlink(DL) and uplink(UL) users by same resource while HD can serve only DL or UL user for each resource. By optimized user scheduling with power control, optimal spectral efficiency could be achieved but optimization problem is non-linear and complex thus it is hard to implement. Low complexity relaxed optimization problem is proposed to solve resource allocation to minimize the transmission completion time in FD network. By adopting proposed scheme, suboptimal solution can be found in linear problem with significantly lower complexity.

For multiuser multiple-input and multiple-output (MIMO) wireless communication in orthogonal frequency division multiplexing systems, we propose a MIMO precoding scheme providing a desired peak-to-average power ratio (PAR) at the minimum cost that is defined as received SNR degradation. By taking advantage of the concentration of measure [1], [2], we formulate a convex problem with a constraint on the desired PAR. Consequently, the proposed scheme almost exactly achieves the desired PAR on average, and asymptotically attains the desired PAR at the 10-3point of its complementary cumulative distribution function, as the number of subcarriers increases.

The K-user multiple-input and multiple-output (MIMO) broadcast channel (BC) with no channel state information at the transmitter is considered, where each receiver is assumed to be equipped with either conventional antennas or reconfigurable antennas in which each reconfigurable antenna is capable of choosing a subset of receiving modes from several preset modes. Under general antenna configurations, the sum linear degrees of freedom (DoFs) of the K-user MIMO BC with reconfigurable antennas are completely characterized, which corresponds to the maximum sum DoF achievable by linear coding strategies.

The feasibility conditions of interference alignment (IA) are analyzed for interfering broadcast-multiple-access channels in which one cell operates as downlink but the other cell operates as uplink. Under a general multiple-input and multiple-output antenna configuration, a necessary condition and a sufficient condition for one-shot linear IA are established, i.e., linear IA without symbol or time extension. In various example networks of interest, the optimal sum degrees of freedom (DoFs) are characterized by the derived necessary condition and sufficient condition. For symmetric DoF within each cell, a sufficient condition is established in a more compact expression, which yields the necessary and sufficient condition for a class of symmetric DoFs. An iterative construction of transmit and receive beamforming vectors is further proposed, which provides a specific beamforming design satisfying one-shot IA. Simulation results demonstrate that the proposed IA not only achieves larger DoF, but also significantly improves the sum rate over the single-cell operation in the practical signal-to-noise ratio regime.

Full-duplex (FD) cellular networks are considered in which an FD base station (BS) simultaneously supports a set of half-duplex (HD) downlink (DL) users and a set of HD uplink (UL) users. The transmitter and the receiver of the BS are equipped with reconfigurable antennas, each of which can choose its transmit or receive mode from several preset modes. Under the no self-interference assumption arisen from an FD operation at the BS, the sum degrees of freedom (DoF) of FD cellular networks is investigated for both no channel state information at the transmit side (CSIT) and the partial CSIT. In particular, the sum DoF is completely characterized for the no CSIT model and an achievable sum DoF is established for the partial CSIT model, which improves the sum DoF of the conventional HD cellular networks. For both no CSIT and partial CSIT models, the results show that the FD BS with reconfigurable antennas can double the sum DoF even in the presence of user-to-user interference as both the numbers of DL and UL users and preset modes increase. It is further demonstrated that such DoF improvement indeed yields the sum rate improvement at the finite and operational signal-to-noise ratio regime.

Due to the mobile networks experiencing heterogeneity and intricacy, many studies with efficient data off-loading have been considered. In this paper, we address the benefits of deploying movable caching nodes (e.g. mobile users, vehicles), namely VehiCaching (VC), in cellular networks. We classify the role of VC into two issues: 1) considering multiple access schemes between macrocell and VC for fair and aggressive data off-loading (at the user-side), and 2) developing the file placement strategy with the concept of storage range which relates vehicles' route to embracing user request (at the VC-side). Compared with conventional priority-based caching and non-caching cellular networks, we evaluate the performance gains with respect to the average data throughputs versus storage range, outage probabilities versus target data-rate, and probabilistic distributions of outage probability to capture changed environments by mobility.

Due to the tremendous growth of mobile data traffic, some technologies from small cell deployment are still ongoing as nominated solutions. Without enlarged wired backhaul capacity, however, the performance of small cell techniques are inevitably degraded. The approach employing the storage capacity in order to off-load the backhaul capacity, as known as femto-caching, has been proposed to minimize the delay within downloading data [1]. In this paper, we consider more practical scenario such as distribution of users' position in whole networks and extend the previous researches in the manner of file placement strategies. Simulation results verify that our proposed scheme has better performance gains with respect to increased opportunity to obtain more various downloading data if helpers' coverages are overlapped.

In this paper, an efficient feedback structure is proposed to reduce the feedback overhead of three-user multiple input multiple output interference channels (MIMO-IFC). We present a sequential and iterative feedback structure based on interference cancellation condition. Compared to the previous feedback structure for interference alignment (IA) in K-user MIMO-IFC [1], the proposed method does not need a cooperation between receivers. Even though the proposed scheme inherently requires the infinite number of iterations to remove the residual interference clearly, almost all of the residual interference is eliminated by the low number of iterations enough that its total feedback overhead is dramatically reduced compared to the conventional approach [2]. Furthermore, in order to improve throughput performance, we propose a concatenated receive filter for maximizing the effective SINR.

In this paper, we propose a simple but effective lattice reduction (LR) scheme for an uplink with two antennas at the base station and two-users, each employing the Alamouti space-time block coding (STBC). By exploiting the inherent STBC structure of transmitted symbols from users, the proposed scheme computes the LLL-reduced channel matrix with low complexity. Simulation results reveal that the proposed scheme can achieve the same performance as a conventional lattice reduction schemes while saving about 70% computational complexity in terms of floating-point operations (flops).

Interference alignment (IA) is a joint-transmission technique that achieves the capacity of the interference channel for high signal-to-noise ratios (SNRs). However, most prior works on IA are based on the impractical assumption that perfect and global channel-state information(CSI) is available at all transmitters, resulting in overwhelming feedback overhead. To substantially suppress the feedback overhead, this paper proposes an efficient design of the feedback framework for IA in the K-user multiple-input multiple-output (MIMO) interference channel. The proposed feedback topology supports sequential CSI exchange (feedback and feedforward) between transmitters and receivers and reduces the feedback overhead from a cubic function of K to a linear one, compared to conventional feedback approaches. Given the proposed feedback topology, we consider the limited feedback channel from the receivers to corresponding interferers and analyze the effect of quantization error which generates the residual interference. Also, an efficient feedback-bit allocation algorithm that minimizes the upper-bound of sum residual interference is proposed.

In a densely distributed sensor network, it is known that it is advantageous to exploit both intra- and inter- signal correlation structures during recovery procedure. Based on this observation, the bound of the required number of measurement in distributed compressive sensing (DCS) is shown to be reduced by exploiting this structure[2]. In this paper, we generalize the model for distributed compressive sensing and show that elaborated signal structure can reduce the required number of measurements further. To this end, we introduce a new concept of partial common information which is shared by some parts of signals, but not by every signal. Numerical results show that with the proposed model, more robust signal recovery can be achieved.

In this paper, we analysis the capacity of the clustered network multiple-input multiple-output (MIMO) systems with overlap. We firstly propose a strategy for clustering base stations (BSs) for the analysis tractability. With an assumption of a large number of transmit and receive antennas, an analytical expression of the ergodic capacity using random matrix theorems is derived. In particular, we develop an asymptotic capacity in low signal to noise ratio (SNR) regime. Based on that, we suggest that the number of overlapping degree of freedom (ODOF) is larger than ⌈B/6⌉ for the sake of the capacity increment, where B refers to the total number of BSs in the multicell network. We show through numerical examples that the analytical results match the simulation results even when the number of antennas is small.

In this paper we derive the power loading method for Band Aggregation (BA) Single Carrier-Frequency Division Multiple Access (SC-FDMA) with Zero-Forcing Frequency Domain Equalizer (ZF-FDE). In previous research [6], they derive the optimal power allocation for SC-FDMA with single band, however, this result cannot directly be extended to multiple bands. Thus, we proposed sub-optimal the two stages power loading scheme for SC-FDMA with ZF-FDE in multiple bands. First, we optimize the total powers of each band and then powers of each sub-carrier are optimized by using optimal power in the first step. Simulation results show that the proposed power control is particularly effective in improving the achievable data rate at low Signal to Noise Ratio (SNR).

In this paper, we propose a heterogeneous relaying system which operates multiple amplify-and-forward (AF) and decode-and-forward (DF) relays together. In the proposed system, the heterogeneous relays transmit cooperatively and the receiver at destination exploits received signals of both AF and DF relays. We consider joint encoding (JE) and selective transmission (ST) as cooperative heterogeneous relay transmission schemes. We derive the optimal JE for heterogeneous relays. The extensive simulation results show that the performance of heterogeneous relaying system lies between homogeneous AF and DF relaying system, and follows the performance of homogeneous DF relaying as the number of relays increases.

Transmit beamforming increases throughput and transmission range of a wireless communication system. However, the required feedback of channel state information (CSI) consumes radio resources that otherwise can be used for data transmission. This makes "Feedback or no feedback?" a relevant question to ask. This paper answers this question by proposing intelligent feedback control using a Markov decision process. The feedback controller turns feedback on/off according to the channel state and the criterion of maximum net throughput, namely throughput minus average feedback cost. Assuming channel isotropicity and Markovity, the state of the feedback controller reduces to two channel parameters. This allows the optimal control policy to be efficiently computed using dynamic programming. The optimal control policy is proved to be of the threshold type. Under this policy, feedback is performed whenever a channel parameter indicating the accuracy of transmit CSI is below a threshold, which varies with channel power. The above result holds regardless of whether the controller's state space is discretized or continuous. Simulation shows that feedback control increases net throughput by up to 0.5 bit/s/Hz without requiring additional bandwidth or antennas.

This paper investigates the simulation performances of vehicle-to-anything (V2X) communications based on the IEEE 802.11p wireless access in vehicular environments (WAVE) system in practical small-scale fading models. The main contributions of this paper are as follows. First, we modify the experimental fading models reported by Georgia Institute of Technology to be applied to the computer simulation of V2X communications. Second, an enhanced linear minimum mean square error smoothing-aided decision directed (LSA-DD) channel estimator is proposed to track the time variation of fading channels and mitigate noise enhancement.

Multimode transmission has been studied to improve BER and outage capacity in the point-to-point system. In this paper, we consider the multimode transmission for downlink MIMO based on random beamforming(RBF) with limited feedback. We propose four heuristic mode selection and feedback policies to improve the sum rate and outage performance of downlink RBF system based on two approaches: distributed and centralized. Simulation results show that the centralized mode selection scheme with reasonable feedback amount provides waterfilling effect as well as the multiuser diversity gain, leading to the performance improvement of RBF in terms of sum rate and outage probability.

This paper considers a linear precoding scheme that achieves near optimal sum rate. While the minimum mean square error (MMSE) precoding provides the better MSE performance at all signal-to-noise ratio (SNR) than the zero forcing (ZF) precoding, its sum rate shows superior performance to ZF precoding at low SNR but inferior performance to ZF precoding at high SNR. From this observation, we first develop a near sum rate optimal linear precoding scheme for the case of single receive antenna per user. The resulting precoding scheme regularizes ZF precoding to maximize the sum rate, resulting in better sum rate performance than both ZF precoding and MMSE precoding at all SNR. The proposed scheme is extended to the case of the multiple receive antennas, and it shows the better sum rate performance than the block diagonalization (BD) scheme at all SNR.

The higher data rate of mobile communications has been required for various multimedia services. In DS-CDMA system, one of the solutions to increase the throughput is to use multicode. However, multipath channel destroys the orthogonality of spreading codes, which causes the intercode interference (ICI). ICI gives severe effect on multicode DS-CDMA for BER performance. Conventionally, multicode DS-CDMA system uses the Rake receiver with turbo code, which cannot overcome error floor caused by ICI. In this paper, we propose frequency domain turbo equalization based on minimum mean squared error (FDTE-MMSE) for multicode DS-CDMA in frequency selective channel and evaluate its BER performance by computer simulation. The simulation results show that FDTE-MMSE gives much better performance than the Rake receiver with turbo code in multipath length L > 1.

Time and frequency selective channels or doubly selective channels leads to inter-carrier interference (ICI) in orthogonal frequency division multiplexing (OFDM) systems. We investigate how effectively turbo equalization could reduce the complexity burden of frequency domain equalization in the presence of doubly selective fading channels. We split the frequency domain matrix into several small sub-matrices that contain significant channel information and combine the MMSE equalization and the MAP decoding for iterative structure based on sub-matrices of frequency domain channel matrix. Simulation results show how much complexity reduction the iterative method can offer with better BER performance than that of the non iteration method. The iterative method has 70% computational complexity reduction with achieving 1 dB performance improvement in our simulations.

Antenna selection schemes combined with the scheduler are applied to the uplink multiuser MIMO/FDD system. In this paper, two heuristic Antenna selection based MIMO schedulers are proposed to achieve the optimal performance with affordable complexity, where two search methods are also discussed to set up the antenna channels to be the candidates of the scheduler. Simulation results show that the sum rate and BER performance of the proposed low complexity schemes are about the same to that of the brute-force scheduler which is believed to be the optimal scheme. Moreover, the complexity can be further reduced by the sub-set search method when the number of transmit and receive antennas are 2 which is applicable in the realistic systems.

In this paper, an enhanced time-domain cancellation method is proposed for inter-carrier interference (ICI) reduction in OFDM systems. The conventional time-domain cancellation does not work well in deep fades. In order to supplement the conventional method, the simple repetition (de-)coding and the modulation order increasing are employed in the time-domain cancellation. The approximated repetition decoding provides reliable symbols in the regeneration operation, and the increased modulation order maintains the spectral efficiency. Simulation results indicate that the proposed method using 16QAM significantly improves the BER performance compared to the conventional method using QPSK, while maintains the spectral efficiency. Moreover, the proposed method using 64QAM concurrently improves both the BER performance and the spectral efficiency.

In this paper, we investigate the conventional windowed DFT-based channel estimation for OFDM systems with guard bands. The conventional method suffers from the edge effect and the pilot position mismatch. In order to solve the problems, we propose an enhanced DFT-based channel estimation using virtual interpolation with guard bands prediction, where linear minimum mean square error (LMMSE) smoothing/prediction and circular frequency shifting are employed. This technique can efficiently mitigate the edge effect caused by the DFT of the truncated channel impulse response and compensate the pilot position mismatch that pilot symbols are not allocated at the first and the last subcarriers in a useful band. Simulation results show that the proposed method has about 5 dB SNR gain at BER=10-3compared to the conventional method and is as good as the frequency-domain LMMSE method

The investigation into the effect of various feedback errors on system performance can help the robust feedback channel design and transmission of exact feedback channel information as well. We address the algorithm that determines space combining weight vector maximizing received signal power at the mobile on a frequency flat fading channel and investigate the performance degradation by the feedback channel delay in the FDD/CDMA systems employing transmit beamforming. We observe the effect of feedback channel delay corresponding to the number of transmit antennas and the temporal/spatial correlation of channel. The results show that performance is more sensitive to feedback delay with the larger number of antennas when fading at the transmit antennas are not spatially correlated.

We propose an algorithm for forward link beamforming jointly with power control and RAKE combining, which the total transmit power is minimized and effective signal-to-interference and noise ratio (SINR) at each mobile is grater than the target SINR at the same time. In the algorithm, the beamforming weight vectors are determined by the virtual uplink SINR maximization criterion, and the multipath combining weight vectors are selected by minimum mean squared error (MMSE) criterion. The virtual uplink SINR maximization beamforming schemes can reduce the total transmit power compared to the maximal ratio transmission (MRT) schemes through system level simulation. It is observed that diversity gain is obtained by mobile equipped with the multipath combiner.

Multi-code CDMA (MC-CDMA) can not only be integrated easily with a conventional system, but also achieve good spectral efficiency and high processing gain. However, it suffers from high value of peak-to-average power ratio (PAPR). In this paper, we propose a multi-phase CDMA (MP-CDMA) system that can provide variable rate service and is not susceptible to the nonlinear characteristics of the amplifier. The clipping is introduced at the output of the multi-code modulator and at the input of the MPSK modulator in order to improve the performance of the MPSK chip demodulator and reduce the system complexity. The system performance is compared for the different number of codes and different clipping levels. The optimum clipping level is also evaluated for a different number of codes in both AWGN and frequency flat fading channel.

In this paper, we extend the open-loop and closed-loop diversity schemes for the systems employing multiple antennas at both transmitter and receiver, and analyze the performance of those schemes in the spatially correlated Rayleigh fading channel. The SNR and average symbol error rate of the open-loop diversity are analytically derived, and those of the closed-loop diversity are investigated via Monte-Carlo simulation. The performance of the closed-loop diversity is always better than that of the open-loop diversity over the same diversity order channel. While transmit-only and receive-only diversity schemes can make the full diversity gain, the systems employing multiple antennas at both transmitter and receiver cannot. Therefore it is better to put all the antennas at transmitter or receiver for the closed-loop diversity to obtain the full diversity gain.

A 1/spl times/EV-DO system adopts the dynamic data rate transmission technique to support an efficient data service with proportional fairness scheduler. Proportional fairness guarantees good throughput and channel sharing fairness but it does not address the fair scheduling of delay sensitive packet flows. We propose WFQ-PF which is composed of WFQ (weighted fair queuing) and a wireless fair packet service scheduler based on proportional fairness. Preliminary results on the proposed scheduler are given and we notice that this algorithm is an effective control on packet delay which is caused by location-dependent low throughput of a user.