To achieve more high speed and high quality systems of wireless communications, orthogonal frequency division multiple access (OFDMA) has been proposed. Moreover, OFDMA considering the multiuser diversity (MUDiv) has been also proposed to achieve more high system performance. On the other hand, the conventional MUDiv/OFDMA requires large complexity to select the subcarrier of each user. To solve this problem, we have proposed a MUDiv/OFDMA based on the low granularity block (LGB). However, it degrades the system performance in the environment which contains many deep faded subcarrier channels. Therefore, in this paper, we propose a cooperative LGB-MUDiv/OFDMA to mitigate the influence due to the deep faded subcarrier channel.

The important issue of an adaptive scheduling scheme is to maximize throughput while providing fair services to all users, especially under strict quality of service requirements. To achieve this goal, we consider the problem of multiuser scheduling under a given fairness constraint. A novel Adaptive Fairness and Throughput Control (AFTC) approach is proposed to maximize the network throughput while attaining a given min-max fairness index. Simulation results reveal that comparing to straightforward methods, the proposed AFTC approach can achieve the desired fairness while maximizing the throughput with short convergence time, and is stable in dynamic scenarios. The trade-off between fairness and throughput can be accurately controlled by adjusting the scheduler's parameters.

In multiple-input multiple-output (MIMO) systems, the multiuser MIMO (MU-MIMO) systems have the potential to provide higher channel capacity owing to multiuser and spatial diversity. Block diagonalization (BD) is one of the techniques to realize MU-MIMO systems, where multiuser interference can be completely cancelled and therefore several users can be supported simultaneously. When the number of multiantenna users is larger than the number of simultaneously receiving users, it is necessary to select the users that maximize the system capacity. However, computation complexity becomes prohibitive, especially when the number of multiantenna users is large. Thus simplified user scheduling algorithms are necessary for reducing the complexity of computation. This paper proposes a simplified capacity-based user scheduling algorithm, based on analysis of the capacity-based user selection criterion. We find a new criterion that is simplified by using the properties of Gram-Schmidt orthogonalization (GSO). In simulation results, the proposed algorithm provides higher sum rate capacity than the conventional simplified norm-based algorithm; and when signal-to-noise power ratio (SNR) is high, it provides performance similar to that of the conventional simplified capacity-based algorithm, which still requires high complexity. Fairness of the users is also taken into account. With the proportionally fair (PF) criterion, the proposed algorithm provides better performance (sum rate capacity or fairness of the users) than the conventional algorithms. Simulation results also shows that the proposed algorithm has lower complexity of computation than the conventional algorithms.

In this letter, a multiuser cooperative network with multiple relays is introduced, and two decode-and-forward (DF) cooperation schemes are proposed aiming at outage-optimal and fair user scheduling, respectively. The outage probability and asymptotic expressions of symbol error probability (SEP) are derived to evaluate these two schemes. Analysis and simulations show that both schemes can achieve full diversity order, which is the combination of cooperative diversity and multiuser diversity.

This letter investigates the effects of spatial correlation on several multiple antenna schemes in multiuser environments. Using an order statistics upper bound on achievable capacity, we quantify the interaction among spatial correlation, spatial diversity, spatial multiplexing and multiuser diversity. Also, it is verified that the upper bound is tighter than asymptotic capacity when the number of users is relatively small.

This letter presents an optimal user selection algorithm that provides a maximum sum-rate in a zero-forcing based Multiuser MIMO system for downlink. The proposed technique forms a primary group of users whose channel power exceeds a predetermined threshold. Through computer simulations, we have found that the proposed method outperforms the conventional technique yielding a sum rate that is 0.33 bps/Hz higher when the transmit SNR is 10 dB and the total number of users and transmit antennas in the cell is 100 and 4, respectively.

We have developed a novel downlink packet scheduling scheme for a multiuser OFDMA system in which a subchannel can be time-multiplexed among multiple users. This scheme which is called Matrixed-based Proportional Fairness can provide a high system throughput while ensuring fairness. The scheme is based on a Proportional Fairness (PF) utility function and can be applied to any of the PF-based schedulers. Our scheduler explores multichannel multiuser diversity by using a two-dimensional matrix combining user selection, subchannel assignment, and time slot allocation. Furthermore, unlike other PF-based schemes, our scheme considers finitely backlogged queues during the time slot allocation. By doing so, it can exploit multichannel multiuser diversity to utilize bandwidth efficiently and with throughput fairness. Additionally, fairness in the time domain is enhanced by limiting the number of allocated time slots. Intensive simulations considering finitely backlogged queues and user mobility prove the scheme's effectiveness.

In multiuser MIMO-BC (Multiple-Input Multiple-Output Broadcasting) systems, user selection is important to achieve multiuser diversity. The optimal user selection algorithm is to try all the combinations of users to find the user group that can achieve the multiuser diversity. Unfortunately, the high calculation cost of the optimal algorithm prevents its implementation. Thus, instead of the optimal algorithm, some suboptimal user selection algorithms were proposed based on semiorthogonality of user channel vectors. The purpose of this paper is to achieve multiuser diversity with a small amount of calculation. For this purpose, we propose a user selection algorithm that can improve the orthogonality of a selected user group. We also apply a channel prediction technique to a MIMO-BC system to get more accurate channel information at the transmitter. Simulation results show that the channel prediction can improve the accuracy of channel information for user selections, and the proposed user selection algorithm achieves higher sum rate capacity than the SUS (Semiorthogonal User Selection) algorithm. Also we discuss the setting of the algorithm threshold. As the result of a discussion on the calculation complexity, which uses the number of complex multiplications as the parameter, the proposed algorithm is shown to have a calculation complexity almost equal to that of the SUS algorithm, and they are much lower than that of the optimal user selection algorithm.

In this letter, we propose a new power allocation scheme for random unitary beamforming assuming a discrete transmission rate with a small amount of feedback information and low latency. Simulation results show that the proposed scheme can improve throughput compared to the conventional power allocation scheme.

In this letter, we propose a novel singular value decomposition zero-forcing beamforming (SVD-ZFBF) relaying scheme in the multiuser downlink MIMO broadcasting channel with fixed relays. Based on the processing scheme, we apply SUS [5] to select users at the relay station (RS) and develop a joint power allocation strategy at the base station (BS) and RS. By increasing the power at RS or selecting active users to obtain more multiuser diversity, SVD-ZFBF can approach an upper bound and outperform SVD-ZFDPC [1] with much lower complexity. Moreover, we show that the noise power ratio of RS to users significantly impacts the performance.

Sum power iterative water-filling (SPIWF) algorithm provides sum-rate-optimal transmission scheme for wireless multiple-input multiple-output (MIMO) broadcast channels (BC), whereas it suffers from its high complexity. In this paper, we propose a new transmission scheme based on a novel block zero-forcing dirty paper coding (Block ZF-DPC) strategy and multiuser-diversity-achieving user selection procedure. The Block ZF-DPC can be considered as an extension of existing ZF-DPC into MIMO BCs. Two user selection algorithms having linear increasing complexity with the number of users have been proposed. One aims at maximizing the achievable sum rate directly and the other is based on Gram-Schmidt Orthogonalization (GSO) and Frobenius norm. The proposed scheme is shown to achieve a sum rate close to the sum capacity of MIMO BC and obtain optimal multiplexing and multiuser diversity gain. In addition, we also show that both selection algorithms achieve a significant part of the sum rate of the optimal greedy selection algorithm at low computation expenditure.

Dirty paper coding (DPC) is a strategy to achieve the region capacity of multiple input multiple output (MIMO) downlink channels and a DPC scheduler is throughput optimal if users are selected according to their queue states and current rates. However, DPC is difficult to implement in practical systems. One solution, zero-forcing beamforming (ZFBF) strategy has been proposed to achieve the same asymptotic sum rate capacity as that of DPC with an exhaustive search over the entire user set. Some suboptimal user group selection schedulers with reduced complexity based on ZFBF strategy (ZFBF-SUS) and proportional fair (PF) scheduling algorithm (PF-ZFBF) have also been proposed to enhance the throughput and fairness among the users, respectively. However, they are not throughput optimal, fairness and throughput decrease if each user queue length is different due to different users channel quality. Therefore, we propose two different scheduling algorithms: a throughput optimal scheduling algorithm (ZFBF-TO) and a reduced complexity scheduling algorithm (ZFBF-RC). Both are based on ZFBF strategy and, at every time slot, the scheduling algorithms have to select some users based on user channel quality, user queue length and orthogonality among users. Moreover, the proposed algorithms have to produce the rate allocation and power allocation for the selected users based on a modified water filling method. We analyze the schedulers complexity and numerical results show that ZFBF-RC provides throughput and fairness improvements compared to the ZFBF-SUS and PF-ZFBF scheduling algorithms.

We investigate the MIMO broadcast channels with imperfect channel knowledge due to estimation error and much more users than transmit antennas to exploit multiuser diversity. The channel estimation error causes the interference among users, resulting in the sum-rate loss. A tight upper bound of this sum-rate loss based on zeroforcing beamforming is derived theoretically. This bound only depends on the channel estimation quality and transmit antenna number, but not on the user number. Based on this upper bound, we show this system maintains full multiuser diversity, and always benefits from the increasing transmit power.

A precise analysis of the capacity of a wireless downlink packet data system with a fair scheduler is presented. We assume the use of a transmit diversity scheme is operating at each link under the assumption of spatially correlated Rayleigh fading. Numerical results show that spatial fading correlation of the channel improves the capacity of multiuser diversity by reducing the space diversity gain of transmit diversity in each link.

In this letter, the system capacity of multiuser diversity combined with spatial multiplexing schemes is analyzed. An analytic expression is derived for the ergodic system capacity with multiuser scheduling and dual multi-input multi-output (MIMO) systems by using a tight lower bound of the link capacity. The proposed analytic approach is verified through comparisons between analytic and simulated results, and is shown to make fairly precise predictions of the ergodic system capacity and the scheduling gains even when the numbers of antennas and users are small.

It is well known that the diversity gain attained by DCA (Dynamic Channel Allocation) is generally very high over OFDM (Orthogonal Frequency Division Multiplexing)-based broadband networks. This paper introduces a numerical approach for measuring the performance gain afforded by DCA. In the mathematical analysis, the property of order statistics is adopted to derive the upper bound of the expected throughput via the use of DCA. In the simulation, it was possible to achieve a gain of 5 dB by exploiting multi-user and spectral diversities when the number of users is 16 and the total number of subcarriers is 256.

Receiver enhancement at mobile terminals such as using receiver diversity is a way of achieving greater downlink capacity. The enhancement, however, is achieved not instantaneously by a network operator but gradually by the individual users that choose and purchase their own mobile terminals. We investigate in this letter the effect of gradually introducing enhanced receivers at mobiles in different locations. With greedy scheduling, capacity, fairness and coverage are quantified and numerically compared according to locations of enhanced mobiles. The results show that the enhancement made at mobiles nearer to the base provides the greater capacity but this capacity-driving introduction of the enhancement makes the fairness and the coverage poorer.

The explosive growth of wireless network users and the existence of various wireless services have demanded high throughput as well as user's quality-of-service (QoS) guarantees. In accordance with, this paper proposes a novel resource allocation scheme improving both the capability of QoS-provisioning for multiple users and the overall data throughput. Towards this, the modified resource allocation technique combined with the modified largest weighted delay first (M-LWDF) scheme will be exploited upon considering statistical channel behavior as well as real time queuing analysis connected to resource allocation. In order to verify the validity of the proposed resource allocation scheme, the time division multiple access (TDMA) system will be considered as a target application. The simulation results confirm that the proposed scheme gives rise to superior performance in a way of showing results of several performance measures under time-varying wireless fading channel.

Multiuser diversity, identified by recent information theoretic results, is a form of diversity inherent in a wireless network. The diversity gain is obtained from independent time-varying fading channels across different users. The main practical issue in multiuser diversity is lack of Quality of Service (QoS) guarantees. This study proposes a wireless scheduling algorithm named MUDSEQ for downlink channels exploiting multiuser diversity under explicit QoS constraints. The numerical results demonstrate that the novel algorithm can yield non-negligible diversity gain even under tight QoS constraints and little scattering or slow fading environments. Additionally, a system framework for dynamic resource allocation based on the proposed algorithm is developed.