Xiaotian Zhou

Bipartite Matching Based User Grouping for Grouped OFDM-IDMA

In this paper, we present a novel user grouping method for grouped OFDM-IDMA systems. Aiming at maximizing the system capacity, we adaptively distribute users among the pre-allocated subcarrier groups according to their respective channel conditions. Using the notion of SNR evolution function, we first analyze the achievable capacity of the system and formulate the optimization problem as a weighted bipartite matching problem. Due to the analytically intractability of the SNR evolution function, we opt to use either the worst case or best case of the achievable capacity to approximate the original problem. Then Kuhn-Munkres method is employed to solve the approximated problems. The performance of the proposed scheme is evaluated by both theoretical analyses and simulations. Results show that with our proposed algorithm, the system capacity is markedly improved and is very close to the theoretical capacity upper bound.

SCM-SM: Superposition Coded Modulation-Aided Spatial Modulation With a Low-Complexity Detector

Spatial modulation (SM) is a spatial multiplexing scheme that utilizes both the signal constellation and antenna index to convey information. In the original SM, traditional modulation schemes such as quadrature amplitude modulation (QAM) are employed for constellation mapping. In this paper, we propose a novel scheme where superposition coded modulation (SCM) is employed to modulate the information onto the constellation points. We also develop a low-complexity iterative detector for our proposed SCM-SM system. Analysis and simulations demonstrate that SCM-SM significantly outperforms the original SM system with the same data rate while maintaining the relatively low complexity, particularly in the high data rate scenario.

Linear Programming Based Pilot Allocation in TDD Massive Multiple-Input Multiple-Output Systems

By providing substantial gains in terms of both spectral and energy-efficiency, Massive MIMO is expected to be the promising enabler for the fifth generation (5G) communications. However the performance of massive MIMO is greatly affected by pilot contamination due to the insufficiency of pilot sequences. To overcome this, we propose a linear programming based pilot allocation with the purpose of alleviating the effect of pilot contamination and maximizing the system throughput. We first formulate the pilot allocation as a user clustering problem, which can be converted to a linear programming one by introducing the integer factor and constraint relaxation. An efficient linear programming algorithm is proposed to solve the problem. Simulation results demonstrate that the proposed scheme outperforms the other candidates in the presence of pilot contamination.

Interference Alignment Transceiver Design by Minimizing the Maximum Mean Square Error for MIMO Interfering Broadcast Channel

An interference alignment (IA) transceiver design scheme for multiple-input-multiple-output (MIMO) multicell multiuser wireless communication systems is proposed by minimizing the maximum mean square error (MSE) of the received symbols to improve fairness among users. The formulated Min-Max MSE optimization problem is not jointly convex on the transmit precoders and receive filters and, thus, is very difficult to solve directly. An iterative method is proposed to solve the optimization problem to get a suboptimal solution instead. Considering that if the receive filters are fixed, the Min-Max MSE problem can be reformulated as a second-order cone programming problem, and if the transmit precoders are fixed, the closed-form receive filters minimizing the receive MSE can be easily obtained, and the formulated Min-Max MSE problem is solved by alternatively optimizing the transmit precoders and the receive filters. The convergence of the proposed algorithm is proved, which shows its feasibility. Furthermore, a robust Min-Max MSE algorithm is proposed to counter the channel uncertainty. Simulation results show that the proposed Min-Max MSE algorithm can achieve IA when the antennas are configured to be strong IA proper and when the users in the network are of the same signal-to-noise ratio (SNR). Analysis indicates that the proposed Min-Max IA transceiver design scheme can significantly improve user fairness with a possible cost of sum-rate reduction. Results also show that the proposed robust design algorithm provides better performance when lacking perfect channel state information (CSI).

Quadrature index modulated OFDM for vehicular communications

High reliability and spectral/power efficiency are key metrics for vehicular communications. The former is due to the requirements for the safety and route related information transmitted; while the latter owns to the conflict between the communication demands of user and limited capacity of vehicular batteries. Bearing these in mind, in this paper we propose a novel quadrature index modulated OFDM system by independently performing the index modulation in both in-phase and quadrature domain. We give the detailed transceiver design of the proposed system and evaluate the performance through theoretical analysis and simulations. Results demonstrate that the proposed scheme outperforms the traditional OFDM-IM with the same spectral efficiency in various mobile scenario.

A bipartite matching based user grouping method for grouped OFDM-IDMA systems

In this paper, we present a novel user grouping method for grouped OFDM-IDMA systems. Aiming at maximizing the system capacity, we adaptively distribute the users among the pre-allocated subcarrier groups according to their respective channel conditions. We analyze the achievable capacity of the system and formulate the optimization problem as a weighted bipartite matching problem. Kuhn-Munkres method is employed to solve the problem. The performance of the proposed scheme is evaluated through both theoretical analysis and simulation. It shows that with our proposed algorithm, the system throughput is greatly improved and is very close to the theoretical upper bound.

On Analytical Achievable Rate for MIMO Linear Interference Alignment with Imperfect CSI

This paper studies the impact of channel error on the achievable rate of symmetrical K-user multiple-input multiple-output linear interference alignment (IA) networks. The upper and lower bounds of the achievable sum rate are derived analytically with the assumption of orthonormal transmit precoders and receive filters designed from imperfect channel state information (CSI) over both the uncorrelated and correlated channels. For uncorrelated channels, quite tight lower and upper bounds are obtained. The impact of channel error on the degrees of freedom (DoF) and the DoF persistence conditions are also investigated. Results show that the DoF of IA networks persists only if the channel error decreases in an order higher than the signal-to-noise ratio. For correlated channel, the lower and upper bounds for one realization of IA are derived. The derived upper bound can be used to characterize the achievable rate approximately. Simulation results indicate that the achievable rate of IA network is influenced significantly by CSI uncertainty. The obtained analytical bounds provide an intuitive way to show the impact of channel error on the achievable rate and thus can help practical systems deign.

A Scalable and Cooperative MAC Protocol for Control Channel Access in VANETs

In this paper, a scalable and cooperative medium access control (MAC) protocol (SCMAC) is proposed to support the periodic beaconing over the control channel in vehicular ad hoc networks. The main concerned aspects in SCMAC are communication reliability and protocol scalability. The communication reliability is guaranteed by cooperative beaconing. When broadcasting a beacon, the node embeds the slot state information into the beacon so that surrounding nodes can determine the availability of each slot. Together with the contention window, collisions can be alleviated. The protocol scalability is achieved by the slot access method and the proactive slot reservation. On one hand, the slot access method reduces the average delay by using the smaller beaconing period as the node density is decreasing. On the other hand, the proactive slot reservation always keeps enough idle slots so that more nodes can quickly join the network. Correspondingly, the beaconing period will increase and all nodes can gain chances to broadcast beacons. The simulation results show that SCMAC can achieve the reliable and scalable periodic beaconing in vehicular environments.