This study studies the joint antenna selection and transmit beamforming optimisation in the downlink of a single‐cell multi‐user distributed antenna system, assuming that all users are delay sensitive and only partial channel state information is available at the transmitter side. Under the constraint of the maximum transmit power of each distributed antenna unit, the authors formulate an optimisation problem to minimise the total power consumption while maintaining the rate outage ratio of each user below a threshold. To mitigate the signalling overhead, they firstly propose an adaptive antenna selection strategy based on the received pilot signal power strength. Then, considering that the remaining transmit beamforming problem may be infeasible and non‐convex, a series of relaxation and convex approximation are applied. Finally, they propose a transmit beamforming algorithm based on successive convex approximation and user admission control. Simulation results show that the authors proposed algorithm can achieve a near optimal system performance in both the satisfied user ratio and total power consumption.

In this study, the authors study the downlink joint user scheduling and power allocation in a single‐cell distributed antennas system. Considering that all users are delay sensitive and without any assumption on the feasibility of the system, they formulate an optimisation problem to minimise the total power consumption while maximising the number of satisfied users. Given a user scheduling result, a deflation‐based joint user removal and power allocation algorithm and a conservative power allocation algorithm are proposed. Owing to the complexity in full enumeration of all user scheduling results, they further propose a joint heuristic user scheduling and power allocation algorithm, in which a priority parameter is defined to determine the user scheduling order and the conservative power allocation algorithm is applied to execute the power allocation. The user with the worst quality of experience is iteratively removed away from the active user set until all the remaining users are guaranteed with their quality of service requirements. Simulation results show that the authors proposed heuristic algorithm obtains a near optimal system performance in both user outage ratio and total power consumption.

Efficient spectrum resource allocation in wireless networks is important for improving the system throughput and guaranteeing the user-percieved Quality-of-Service (QoS). In this paper, we propose an enhanced algorithm for spectrum resource allocation in femtocells. First, the bandwidth of each user is determined by the user's demand and the channel state. Second, graph theory is enhanced and used to improve spectrum efficiency. Our simulation results show that the proposed algorithm improves the system throughput significantly and also guarantees the fairness toward the users.

This paper proposes a joint transmit-receive spectrum sharing method based on space division multiplexing (SDM) in cognitive radio networks (CRN). By exploiting spatial correlation features between cognitive transmission and interference from cognitive base station (CBS) to primary user (PU) as well as interference from primary base station (PBS) to cognitive user (CU), appropriate primary system and its channel are selected. Consequently spectrum sharing is carried out employing the proposed SDM based strategy. The method is a good complement for conventional cognitive radio (CR) which adopts opportunistic spectrum access. Analysis and simulation results show that compared with the method implemented only at CBS and exhaustive searching, the proposed scheme could achieve near-optimal throughput performance with reduced complexity.

Emergence of various radio access networks enables users to communicate with each other anytime and anywhere. Handover management strategy directly influences the user's service continuity performance and quality of service. In this paper, we propose a handover trigger time selection strategy based on the prediction of received signal strength. With auto-regression model, the mobile terminal predicts both the earliest and the latest handover trigger time threshold, and then determines the optimal trigger time. Simulation results show that our proposed method can almost eliminate handover failure and has a good adaptability to the varying network overlapping environment.

By maximizing a derived lower bound on the ergodic capacity, the optimal design of training length is given for Multiple-Input Multiple-Output (MIMO) systems. The channel is assumed to be flat fading in presence of spatial fading correlation only at the transmitter, which is known a priori by both ends. Different from the case of independent and identically distributed channel, the optimal training length no longer equals the number of transmit antennas but is just the same as the rank of transmit correlation matrix. The stronger the channel correlation is, the less the optimal training length is. This coincides with the fact that the accuracy of channel estimation is being improved when the channel correlation increases under equal training intervals.

Optimal design of training sequences for multiple-input multiple-output (MIMO) channel estimation is considered. The channel is assumed to be frequency-selective and obey block-fading law with both spatial fading correlation and multipath tap gain correlation known at both the transmitter and receiver. To minimize the channel estimation error, optimal training sequences are designed to exploit full information of channel correlation under the criterion of minimum mean square error (MMSE). It is investigated that channel correlation is helpful to decrease the estimation error and the proposed training sequences have good performance via simulations.

The paper deals with the problem of the carrier frequency-offset (CFO) estimation for wireless communications. Since the well-known maximum-likelihood (ML) CFO estimator is rather complex, many complexity-reduced CFO estimators have so far been proposed. However, most of them are based on periodic training sequences and have limited estimation range. We propose a general framework called composite frequency- offset estimator (CFE), which can extend the estimation range of any range-limited correlation-based CFO estimator up to the full transmission spectrum. We first formulate the CFO estimation as a problem of composite hypothesis testing, and then solve the problem by the composite hypothesis testing approaches. We show that the composite frequency-offset estimate is the ML estimate as long as the original range-limited estimator is unbiased and attains the Cramer-Rao Lower Bound. The CFE also allows a flexible tradeoff between the estimation range and computational complexity. Finally, numerical results show the efficiency of the proposed method.

Optimal design of training sequences is considered for multiple-input multiple-output (MIMO) systems in the presence of spatial fading correlation. By the method of minimum mean square error (MMSE) channel estimation, we first evaluate the estimation accuracy and the training sequence length under correlated fading, based on which we then design optimal training sequences that have controllable length to make effective use of the correlation properties. It is investigated that the impacts of spatial correlation are helpful not only to improve channel estimation but also to decrease the training length, moreover, that the proposed training sequences have good performance via simulations.

We address the problem of frequency offset and channel estimation in multi-input multi-output (MIMO) flat-fading channels. By considering MIMO system as equivalent single-input single-output (SISO) sub-systems with multi-antenna interference, a novel iterative parameter estimation method with interference cancellation is proposed. Numerical results show that this iterative method achieves a satisfactory performance.

Carrier frequency offsets (CFOs) in orthogonal frequency division multiplexing access (OFDMA) system will introduce intercarrier interference (ICI) and consequently degrade the system performance. A new frequency offsets estimation algorithm based on the combination of ESPRIT (estimation of signal parameters by rotational invariance techniques) and the maximum likelihood (ML) estimation methods for OFDMA system is proposed. The subset of the frequency offsets is first estimated by ESPRIT then the frequency offset of each user is identified in the subset by ML estimation method. The complexity of the combination algorithm is significantly decreased compared with the ML estimator. The algorithm efficiently solves the problem of multi-frequency offsets estimation.

In this paper, a new maximum likelihood (ML) estimator for the integer frequency offset estimation of OFDM systems is proposed and compared with the conventional SC estimator. Both estimators exploit the differential information between two consecutive blocks of OFDM data symbols in the frequency domain. The reason why the proposed ML estimator has better performance than the conventional SC method is analyzed. The mean and variance of the proposed and conventional estimators are discussed, and the estimation error probability is given. The computer simulation results are in good agreement with the analytical study.

An efficient estimator for integer frequency offset estimation of OFDM systems is derived, which is based on maximum likelihood (ML) technique and exploits the differential information between two consecutive blocks of OFDM data symbols in frequency domain. The reason why the proposed ML estimator has better performance than the conventional method is analyzed. How to select the differential sequence is also studied. By computer simulations, the effects of the various parameters such as length of cyclic prefix, value of integer frequency offset and differential PN sequence on the performances of the two estimators are evaluated, and the performance of the ML estimator is compared with that of the conventional method for the additive white Gaussian noise (AWGN) channel and a multipath fading channel. The simulation results are in good agreement with the analytical study.