Scheduling Algorithms and Throughput Maximization for the Downlink of Packet-Data Cellular Systems with Multiple Antennas at the Base Station

The capacity-achieving coding scheme for the multiple-input multiple-output (MIMO) broadcast channel is dirty-paper coding. With this type of transmission scheme the optimal number of active users that receive data and the optimal power allocation strategy are highly dependent on the structure of the channel matrix and on the total transmit power available. In the context of packet-data access with adaptive transmission where mobile users are equipped with a single receive antenna and the base station has multiple transmit antennas, we study the optimal number of active users and the optimal power allocation. In the particular case of two transmit antennas, we prove that the optimal number of active users can be a non-monotonic function of the total transmit power. Thus not only the number of users that should optimally be served simultaneously depends on the user channel vectors but also on the power available at the base station transmitter. The expected complexity of optimal scheduling algorithms is thus very high. Yet we then prove that at most as many users as the number of transmit antennas are allocated a large amount of power asymptotically in the high-power region in order to achieve the sum-capacity. Simulations confirm that constraining the number of active users to be no more than the number of transmit antennas incurs only a marginal loss in spectral efficiency. Based on these observations, we propose low-complexity scheduling algorithms with sub-optimal transmission schemes that can approach the sum-capacity of the MIMO broadcast channel by taking advantage of multiuser diversity. The suitability of known antenna selection algorithms is also demonstrated. We consider the cases of complete and partial channel knowledge at the transmitter. We provide simulation results to illustrate our conclusions.     

A Low Complexity Algorithm for Subcarrier-and-Bit Allocation in OFDMA-Based LTE Systems

In this paper, we propose optimum and sub-optimum resource allocation and opportunistic scheduling solutions for orthogonal frequency division multiple access (OFDMA)-based multicellular systems. The applicability, complexity, and performance of the proposed algorithms are analyzed and numerically evaluated. In the initial setup, the fractional frequency reuse (FFR) technique for inter-cell interference cancellation is applied to classify the users into two groups, namely interior and exterior users. Adaptive modulation is then employed according to the channel state information (CSI) of each user to meet the symbol error rate (SER) requirement. There then, we develop subcarrier-and-bit allocation method, which maximizes the total system throughput subject to the constraints that each user has a minimum data rate requirement. The algorithm to achieve the optimum solution requires high computational complexity which hinders it from practicability. Toward this end, we propose a suboptimum method with the complexity extensively reduced to the order of O(NK), where N and K denote the total number of subcarriers and users, respectively. Numerical results show that the proposed algorithm approaches the optimum solution, yet it enjoys the features of simplicity, dynamic cell configuration, adaptive subcarrier-and-bit allocation, and spectral efficiency.     

Transmit power adaptation for multiuser OFDM systems

In this paper, we develop a transmit power adaptation method that maximizes the total data rate of multiuser orthogonal frequency division multiplexing (OFDM) systems in a downlink transmission. We generally formulate the data rate maximization problem by allowing that a subcarrier could be shared by multiple users. The transmit power adaptation scheme is derived by solving the maximization problem via two steps: subcarrier assignment for users and power allocation for subcarriers. We have found that the data rate of a multiuser OFDM system is maximized when each subcarrier is assigned to only one user with the best channel gain for that subcarrier and the transmit power is distributed over the subcarriers by the water-filling policy. In order to reduce the computational complexity in calculating water-filling level in the proposed transmit power adaptation method, we also propose a simple method where users with the best channel gain for each subcarrier are selected and then the transmit power is equally distributed among the subcarriers. Results show that the total data rate for the proposed transmit power adaptation methods significantly increases with the number of users owing to the multiuser diversity effects and is greater than that for the conventional frequency-division multiple access (FDMA)-like transmit power adaptation schemes. Furthermore, we have found that the total data rate of the multiuser OFDM system with the proposed transmit power adaptation methods becomes even higher than the capacity of the AWGN channel when the number of users is large enough.     

Quantized feedback MIMO scheduling for heterogeneous broadcast networks

One-bit quantization of signal-to-interference-plus-noise ratio is discussed in literature for user scheduling in homogeneous network where users are assumed to have equal signal-to-noise ratio (SNR). It is mentioned in literature that 1-bit quantization with fixed quantization threshold does not achieve multiuser diversity. Moreover, the system sum-rate achieved by this lags significantly behind that of full feedback scheme. Two multi-bit quantized feedback scheduling schemes are proposed for broadcast network with heterogeneous users experiencing different channel statistics. It is presented that these two schemes with fixed optimum quantization thresholds profit from the diversity provided by independent and identically distributed channels. Moreover, proposed optimistic multi-bit quantized scheduling scheme achieves higher system sum-rate than the proposed multi-bit quantized scheme by addressing the limitations of the later one. The optimum quantization thresholds depend on the number of transmit antennas and system SNR. Moreover, these multi-bit quantized feedback scheduling schemes also ensure user fairness. Simulation results are presented to support the numerical analysis.     

New Optimal and Suboptimal Resource Allocation Techniques for Downlink Non-orthogonal Multiple Access

This paper investigates several new strategies for the allocation of radio resources (bandwidth and transmission power) using a non-orthogonal multiple access (NOMA) scheme with successive interference cancellation (SIC) in a cellular downlink system. In non-orthogonal access with SIC, the same subband is allocated to multiple users, which requires elaborate multiuser scheduling and subband assignment techniques, compared to orthogonal multiplexing. While taking into account various design issues, we propose and compare several optimum and suboptimum power allocation schemes. These are jointly implemented with multiple user scheduling strategies. Besides, a minimization of the total amount of used bandwidth is targeted. Also, to increase the total achieved system throughput, a hybrid orthogonal-non orthogonal scheme is introduced. This hybrid scheme enables a dynamic switching to orthogonal signaling whenever the non-orthogonal cohabitation in the power domain does not improve the achieved data rate per subband. Extensive simulation results show that the proposed strategies for resource allocation can improve both the spectral efficiency and the cell-edge user throughput, especially when compared to previous schemes employing either orthogonal signaling or NOMA with static inter-subband power allocation. They also prove to be robust in the context of crowded areas.     

CDMA multiuser detection: a nonlinear programming approach

The optimum receiver to detect the bits of multiple code-division multiple access (CDMA) users has an exponential complexity in the number of active users in the system. Consequently, many suboptimum receivers have been developed to achieve good performance with less complexity. We take the approach of approximating the solution of the optimum multiuser detection problem (OMUD) using nonlinear programming relaxations. First, we observe that some popular suboptimum receivers indeed correspond to relaxations of the optimal detection problem. In particular, one proposed approximation method yields to iterative solutions which correspond to previously proposed heuristic nonlinear detectors. Using a nonlinear programming approach, we identify the convergence properties of these iterative detectors. Secondly, we propose a relaxation that yields a receiver which we call the generalized minimum mean squared error detector. We give a simple iterative implementation of the detector. Its performance is evaluated and comparisons to other suboptimum detection schemes are given     

Antenna and User Subset Selection in Downlink Multiuser Orthogonal Space-Division Multiplexing

Block diagonalization (BD) and successive optimization (SO) are two suboptimal but more practical (compared to dirty paper coding (DPC)) orthogonal linear precoding techniques for the downlink of multiuser MIMO systems. Since the numbers of users supported by BD or SO for a given number of transmit antennas are limited, BD or SO should be combined with scheduling so that a subset of users is selected at a given time slot while meeting the dimensionality requirements of these techniques. On the other hand, receive antenna selection (RAS) is a promising hardware complexity reduction technique. In this paper, we consider user scheduling in conjunction with receive antenna selection. Since exhaustive search is computationally prohibitive, we propose simplified and suboptimal user scheduling algorithms for both BD and SO. For BD, we propose capacity and Frobenius-norm based suboptimal algorithms with the objective of sum rate maximization. Starting from an empty set, each step of proposed algorithms adds the best user from the set of users not selected yet until the desired number of users have been selected. Proposed receive antenna selection works in conjunction with user scheduling to further enhance the sum rate of BD. For SO, a Frobenius-norm based low complexity algorithm is proposed, which maximizes the ratio of the squared Frobenius norm of the equivalent channel (projected to the joint null space of the previously selected users) to the sum of the squared Frobenius norms of the previously selected users’ preprocessed channels. Simulation results demonstrate that the proposed algorithms achieve sum rates close to exhaustive search algorithms with much reduced complexity. We also show that in addition to reduced hardware complexity at the receiver, antenna selection enhances multiuser diversity gain that is achieved with user scheduling.     

Distributed closed-loop spatial multiplexing for uplink multiuser systems

Focusing on the uplink, where mobile users (each with a single transmit antenna) communicate with a base station with multiple antennas, we treat multiple users as antennas to enable spatial multiplexing across users. Introducing distributed closed-loop spatial multiplexing with threshold-based user selection, we propose two uplink channel-assigning strategies with limited feedback. We prove that the proposed system also outperforms the standard greedy scheme with respect to the degree of fairness, measured by the variance of the time averaged throughput. For uplink multi-antenna systems, we show that the proposed scheduling is a better choice than the greedy scheme in terms of the average BER, feedback complexity, and fairness. The numerical results corroborate our findings.     

A hybrid time divisioning scheme for power allocation in DMT-based DSL systems

We propose an iterative waterfilling based multiuser Hybrid Time Divisioning (HTD) scheme for power allocation in DMT based DSL systems. The problem of finding the (user,subchannel) pairs which should transmit alone and the pairs which should transmit along with other users, so as to result in the maximum aggregate data rate achievable using time divisioning, has been considered. The proposed scheme Is a low complexity, sub-optimal solution to this problem. Results show that the HTD scheme can achieve better data rates than Iterative Waterfilling a well as Multiuser Discrete Bit Loading scheme (for high coupling coefficient values) with comparatively lesser complexity.     

Capacity Optimizing Power Allocation in Interference Channels

The interference channel is an essential model in both wireline and wireless communication systems. This article addresses transmit power allocation in interference channels with total transmit power constraint. The optimum power allocation maximizing the sum rate in two user interference channels can be derived analytically. However, the non-convexity of the optimization problem makes it prohibitively complex to obtain the optimum solution either analytically or numerically in general K user scenarios. After reviewing several conventional suboptimum power allocation schemes including equal power allocation, greedy power allocation and waterfilling power allocation, an iterative waterfilling algorithm is proposed and discussed. The performance of various power allocation schemes is evaluated through simulations, which suggests that the proposed iterative waterfilling outperforms other suboptimum power allocation schemes in certain scenarios.     

Power-Minimizing Rate Allocation in Cooperative Uplink Systems

The rate-allocation problem, which has been aimed at minimizing the total transmit power in cooperative uplink systems, is investigated. Each user transmits over an orthogonal frequency band using cooperative broadcasting. The broadcasting nature of the wireless channel is exploited by allowing users to act as relays for one another. All users operate in the decode-and-forward mode. Depending on the number of relays that was selected by a user, we suggest two schemes: 1) the flow-optimized cooperative scheme (FCS) and 2) the single-relay cooperative scheme (SCS). We develop rate-allocation algorithms for them. In our simulation, we compare the outage performance of our schemes with two other schemes: 1) the orthogonal cooperative scheme and 2) direct transmission. Results indicate that our schemes achieve full diversity order and outperform other compared schemes. The algorithm for FCS achieves the optimality, whereas the algorithm for SCS is near optimal. In addition, our algorithms have fast convergence performance. SCS has a lower complexity than FCS, but it requires a higher total transmit power. However, the difference in total transmit power between FCS and SCS is not large under practical rate requirements. In addition to the total transmit power, we consider the improvement in the individual transmit powers of the users.      

Optimum rate allocation for two-class services in CDMA smart antenna systems

Transmission bit rates are optimized for two-class traffic in variable spreading gain code-division multiple-access systems with antenna arrays. In an array antenna system, the interference levels experienced by the users belonging to different beams are not the same. Thus, it is not efficient to allocate the same rates to all the data users even though they belong to a cell. Considering this, an optimum rate allocation scheme is proposed for delay-tolerant data users. Additionally, we also propose the optimum rate allocation scheme for voice and data users when a packet scheduling scheme is considered. Numerical results show that, in array antenna systems, the proposed schemes considerably outperform the conventional scheme designed for omniantenna systems.     

MIMO Scheduling Effectiveness Analysis for Bursty Data Service from View of QoE

In the user selection phrase of the conventional Multiple-input-multiple-output (MIMO) scheduling schemes,the frequent user exchange deteriorates the Quality of user experience (QoE) of the bursty data service.And the channel vector orthogonalization computation results in a high time cost.To address these problems,we propose an inertial scheduling policy to reduce the number of noneffective user exchange,and substitute self-organization policy for channel vector orthogonalization computation to reduce computational complexity.The relationship between the scheduling effectiveness and the inertia of objective function is observed in the simulation.The simulation results show that the inertial scheduling policy effectively reduce the number of potential noneffective scheduling which is inversely proportional to the Mean opinion score (MOS) that quantifies the QoE.Our proposed scheduling scheme provides significant improvement in QoE performance in the simulation.Although the proposed scheduling scheme does not consider the channel vector orthogonalization in the user selection phrase,its throughput approaches the level of the throughput-oriented scheme because of its selforganization scheduling policy.     

Low Complexity User Scheduling,Ordering and Transmit Covariance Matrix Optimization Algorithms for Successive Zero-Forcing Precoding

In this paper we consider user scheduling, ordering and transmit covariance matrix optimization problems under successive zero-forcing (SZF) precoding for multiuser multiple-input multiple-output downlink. We propose a heuristic user scheduling metric and an intermediate user grouping technique to develop a low complexity greedy scheduling algorithm. A suboptimal user ordering technique is also proposed for transmit covariance matrix optimization under SZF. Proposed algorithm is of low complexity, but performs closely to the highly complex exhaustive search algorithm. For transmit covariance optimization under SZF, a dirty paper coding based algorithm has been previously proposed, which is computationally very complex. In this paper, we propose a suboptimal but much simplified algorithm, which employs an iterative procedure similar to a known multiple access channel (MAC) covariance optimization algorithm, but does not involve multiple levels of covariance matrix transformations. With the proposed suboptimal user ordering the exhaustive search through all possible user orders is avoided during transmit covariance matrix optimization resulting in a significant complexity reduction, and without a significant performance penalty. Simulation results show that the proposed algorithm performs very close to the known algorithm in the low SNR region.     

Generalization of Hybrid Time Divisioning for Power Allocation in DMT-Based DSL Systems

We propose an algorithm that seeks to generalize the recently proposed hybrid time divisioning scheme. It tries to make optimal groupings amongst all the (user, subchannel) pairs by deciding which users should transmit alone in a subchannel and which users should transmit along with each other in order to yield substantial data rate increments. This time divisioning based modification can be applied over any resource allocation scheme (e.g multi user discrete bit loading, iterative waterfilling, optimal spectrum balancing) which involves simultaneous transmission of all the users.     

Rate scheduling in multiple antenna downlink wireless systems

We consider scheduling strategies for multiantenna and multibeam cellular wireless systems for high-speed packet data services on the downlink. We establish a fundamental connection between the stability region of the queuing system and the set of feasible transmission rates, which provides the basis for the scheduling algorithm proposed in this paper. Transmission using adaptive steerable beams and fixed sector beams are considered and average delay versus throughput results are obtained through simulations for the proposed scheduling scheme in each case. While in single antenna systems multiuser diversity gains are achieved by the scheduling algorithms that transmit to a single user in each scheduling interval, our results show that with multiple antennas, transmitting to a carefully chosen subset of users has superior performance. The multiantenna scheduling problem is closely related to the problem of coordinated scheduling for transmission through multiple base stations, where a user can receive signals from several base stations simultaneously. We consider the special case when three single-antenna base stations are allowed to cooperate and transmit to the users in the triangular region between the base stations and propose scheduling strategies that demonstrate significant gains.     

Performance of Two‐User Two‐Way Amplify‐and‐Forward Relaying Systems with Scheduling

In this paper, we study scheduling schemes for two‐user two‐way wireless relaying systems. Two transmission modes are considered: point‐to‐point direct transmission and two‐way amplify‐and‐forward relaying. An optimal scheduling scheme that opportunistically selects the best transmission mode for each user is proposed to minimize the sum bit error rate (BER). The performance lower bound of the optimal scheduling scheme is analyzed, and closed‐form expression of the lower‐bound BER is derived. However, for optimal scheduling, the scheduler requires the knowledge of channel state information (CSI) of all links. To reduce the feedback information of CSI, we also propose a suboptimal scheduling scheme that selects the transmission mode using only the CSI of two direct links. Simulation results show that there are 4 dB to 8 dB gains for the proposed optimal and suboptimal schemes over the fixed direct transmission and fixed two‐way relayed transmission scheme. The performance gap between the optimal and suboptimal scheduling schemes is small, which implies a good trade‐off between implementation complexity and system performance.     

Multiple Connectivity and Spectrum Access Utilisation in Heterogeneous Small Cell Networks

In the context of heterogeneous and small cell networks, users will have the possibility to connect to multiple radio access (RA) carriers that will be available by a dense deployment of RA infrastructure consisting of high-power and low-power access nodes. Determining which RAs a user should be associated with and select from, for its downlink transmissions, depends on the long-term and short-term data rates that these RAs may offer to the user. In this study the multi-RA association and utilisation is decomposed into a multi-RA to user association problem that assigns multiple RAs to users, and a multi-RA selection problem that determines which of the assigned RAs should be used at any time for the user transmissions. As a solution to the first problem, we propose a distributed dual-based spectrum access scheme (DSA) that considers multi-connectivity, whilst, the second problem is solved by means of a heuristic multi-RA selection scheme that utilise different multi-radio transmit diversity (MRTD) schemes while taking into account different inter-cell interference coordination (ICIC) schemes. Our two-step approach is evaluated by means of simulations which demonstrate cell-edge user throughput performance improvements that exceed 100 % when the multi-connectivity DSA is employed. Further significant user rate and energy efficiency improvements up to 69 and 38 % respectively can be achieved when MRTD is combined with ICIC.     

A Fast Subcarrier, Bit, and Power Allocation Algorithm for Multiuser OFDM-Based Systems

In this paper, we propose a real-time subcarrier, bit, and power allocation algorithm for orthogonal frequency-division multiplexing-based multiuser communication systems in downlink transmission. Assuming that base stations know the channel gains of all subcarriers of all users, the proposed loading algorithm tries to minimize the required transmit power while satisfying the rate requirement and data error rate constraint of each user. The novel algorithm simultaneously determines subcarrier, bit, and power allocation by enhancing the suboptimal algorithm by Wong while having the same computational complexity. The proposed scheme offers better performance in terms of transmit power than that of Wong , as demonstrated in the simulation results, whereas the performance of the scheme in Wong was close to that of the optimal solution.