Max-min beamforming for multicell downlink systems using long-term channel statistics

This paper studies the performance improvement of a multi-user downlink system via polarization design at the transmitter such that the gains at the desired locations are maximized. To this end, a weighted sum rate maximization problem is formulated, constrained under total power, polarization norm, and a minimum signal-to-interference-and-noise ratio guarantee to the users for simultaneous transmission (ST), and its performance is compared with time-shared transmission (TT). As a solution strategy, weighted minimum mean square error based and fair resource allocation algorithms have been proposed to optimize ST and TT respectively with only long-term channel statistics as well as with channel state information (CSI) at the transmitter. Weighted sum rate performance is theoretically studied for long-term channel statistics. Branch-and-bound approach and the duality gap are considered to validate the optimal resource allocation with CSI for small-scale and large scale scenarios, respectively. Simulation results show that the proposed joint phase and polarization beamforming consistently enhances the multiaccess performance with respect to only phase beamforming, with average gain of about 23% and 6% with CSI and 89% and 4% with long-term channel statistics for ST and TT, respectively. We also study the performance of the proposed beamforming strategies with imperfect CSI and non-orthogonal multiple access-based ST to capture practical scenarios.

In a conventional cellular network, a terminal receives signals not only from the base station of that cell, but also from other cell base stations. This inter-cell interference has more impact on the cell-edge users, in multi cell environment. The inter-cell interference degrades the performance of wireless systems. Using Base Station Cooperation, the ability of a mobile station to receive signals from multiple base stations can be utilized as an opportunity to improve the spectral efficiency and to get higher data rates for cell edge users. In multi cell environment using base station cooperation overall interference can be minimized marginally, whereas the interference within the cooperation region is largely reduced. This leads to a question whether it is worth doing cooperation all the time. However increase in terms of throughput may not always be enough to increase the throughput of each of the user .Hence for such a scenario the distinct cooperation scheme is used. The distinct cooperation is a joint transmission scheme in which the selection criterion is based on user’s signal to interference plus noise ratio (SINR) is proposed and the capacity achieved through cooperation is shared equally among the cell-edge users. Here we will analyze the normal operation, full cooperation and distinct cooperation scheme in the downlink environment for cell edge users in cellular network and we will compare and see which method improves the user capacity and data rate.KeywordsCooperative transmissionfull cooperationDistinct cooperationsignal to interference plus noise ratio (SINR)

This paper considers transmit beamforming optimization problem for a multi-cell downlink channel with multiple transmit antennas at the base-station. In contrast to the conventional sum-power constraint on the transmit antennas, this paper adopts a per-cell power constraint, which is more realistic in practical implementations. Assuming that the second-order statistics of the channel coefficients are available, this paper investigates the optimization problem of minimizing the total transmission power with individual signal-to-interference-plus-noise ratio (SINR) constraint and per-cell transmission power constraint using Lagrangian duality theory. It is shown that with the approach of Lagrangian duality, the downlink beamforming problem with per-cell power constraint can be transformed into a dual uplink minimax problem with an uncertain noise, and the uplink-downlink duality gives rise to efficient numerical algorithm for solving the downlink per-cell beamforming problem.

In this paper, we address the problem of the coordinated beamforming design for multi-cell multiple input single output (MISO) downlink system subject to per-BS power constraints. The objective is taken as the maximization of the minimum signal-to-interference plus noise ratio (SINR), while a complete analysis of the duality between the multi-cell downlink and the virtual uplink optimization problems is provided. A hierarchical iterative scheme is proposed to solve the virtual uplink optimization problem, whose solution is then converted to derive the one of the multi-cell downlink beamforming problem. The proposed algorithm is proved to converge to a stable point. Additional, the complexity of the proposed algorithm is analyzed. Simulation results show that, in contrast to existing multi-cell beamforming schemes, the proposed algorithm achieves better performance in terms of both rate per energy (RPE) and the worst-user rate.

This study considers the joint transmission precoding design for downlink multicell multiuser multiple‐input single‐output systems where imperfect channel variances are available at the base stations. The authors aim to tackle the robust signal‐to‐interference‐plus‐noise ratio (SINR) balancing problem to maximise the minimum worst‐case user rate. To solve the non‐convex problem, a duality relationship between the downlink max–min worst‐case SINR optimisation problem and the virtual uplink min–max worst‐case SINR optimisation problem is first revealed. Based on this, a new algorithm is developed to solve the virtual problem by using jointly the sub‐gradient method and the geometric programming methods, whose achieved solution is finally converted to the downlink. Their analysis shows that the proposed algorithm is guaranteed to converge and has lower computational complexity than conventional approaches. Moreover, computer simulations validate the effectiveness of the proposed method and show that the proposed algorithm has fast convergence and achieves a performance close to that of the brute search method.

We address the problem of combining limited feedback information with long-term channel statistical information in the design of downlink SDMA schemes. A novel combining method is developed to improve the quality of channel knowledge at the base station. More specifically, a set of novel feedback parameters is proposed and a related method is developed to estimate a representation of the multiuser channel vectors at the base station. This method utilizes the hybrid information by combining instantaneous channel feedback and long-term channel statistics, and is based on a channel phase codebook designed using the generalized Lloyd algorithm. The estimated channel knowledge at the base station can be used for joint design of multiuser precoding and opportunistic scheduling. The advantage of the proposed scheme over existing CSI quantization based SDMA schemes is further confirmed by computer simulations.

Physical-layer network coding (PNC) promises a significant gain In overall network throughput for multi-user cooperative communications. In a multi-unicast scenario, one drawback associated with PNC is an additional noise term, coined as network coding (NC) noise, which severely degrades the system data rate. In this paper, our contribution to address this challenging problem is source and relay power control with the objective of maximization of the minimum average achievable rate among all the source-destination pairs subject to a given total power constraint. We further develop a joint power allocation and relay selection scheme, which only rely on long-term channel statistics, to extend our results to general network topologies. We show that the joint optimization problem can be divided into two problems: optimal power allocation and optimal relay selection where the former is scalable and leads to a power assignment algorithm that exhibits the same optimization complexity for any number of sources in the network and the latter can be performed in a decentralized manner. By means of simulations, we validate our theoretical developments and verify the efficiency of our algorithm in improving the average achievable rate compared to a multi-unicast system with no power control or relay selection. We conclude that the proposed algorithm largely combats the adverse effects of NC noise while achieving near optimal fairness.

In the paper, the effect of frequency-hopping spread spectra (FH-SS) on mobile channel characteristics is evaluated. Employing propagation studies, statistical analysis and simulation models, it is shown that the frequency-hopped channel displays improved characteristics when compared to the nonhopped case. Furthermore, the parameters specifically associated with the frequency-hopped channel are characterised, such as hop rate and system bandwidth. It is shown that the long-term channel statistics are unchanged by hopping. However, the short-term fading statistics are improved, and can be exploited to provide an overall increase in the quality of service. The short-term statistics of the frequency-hopped channel are derived, enabling prediction of the performance of FH-SS.

Communication technologies are critical in achieving potential advantages of smart gird (SG), as they enable electric utilities to interact with their devices and customers. This paper focuses on the integration of a massive multiple-input multiple-output (MIMO) technique into a SG communication architecture. Massive MIMO has the benefits of offering higher data rates, whereas operating a large number of antennas in practice could increase the system complexity and energy consumption. We propose to use antenna selection to preserve the gain provided by the large number of antennas, and investigate an energy efficient massive MIMO system design for SG communications. Specifically, we derive a closed-form asymptotic approximation to the system energy efficiency function in consideration of channel spatial correlation, which exhibits an excellent level of accuracy for a wide range of system dimensions in SG communication scenarios. Based on the accurate approximation, we propose a novel antenna selection scheme aiming at maximizing the system energy efficiency, using only the long-term channel statistics. Simulation results show that the proposed antenna selection scheme can always achieve an energy efficiency gain compared to other selection schemes or baseline systems without antenna selection, and thus is particularly valuable for enabling an energy efficient communication system of the SG.

In spatial time division multiple access wireless mesh networks, not all links can be activated simultaneously, as links scheduled for transmission must satisfy the specified SINR requirements. Previously, slot assignment has been done on a link basis, where a set of links is selected for transmission in a given slot. However, if selected links are in deep fade or have no traffic to transmit, the slot is wasted. Thus, a node-based scheme was proposed, where a set of nodes is selected for transmission. Which link to be used by a node depends on the links’ instantaneous traffic load. Although this allows us to exploit multi-user diversity, it creates a planning discrepancy: slot assignment is designed based on long-term channel statistics, but scheduling on short-term channel fading conditions. Consequently, the performance gain of the node-based scheme is not consistent: it is marginal under certain scenarios. To avoid the design discrepancy, we develop a new slot-assignment and routing framework in this paper. The new approach incorporates short-term channel fading statistics to optimize the long term slot assignment, routing and scheduling simultaneously. Hence, multi-user diversity can be exploited more efficiently. Not only is the performance gain of the resulting system significant (can be as much as 64% higher throughput than the scheme introduced by Chen and Lea), it is also less topology dependent compared with the one by Chen and Lea.

Coordinated multiple point transmission/reception (CoMP) has been investigated recently as a promising technology to fulfill the requirements of LTE-Advanced. This paper proposes a downlink coordination scheme applied in the CoMP cooperating set to provide best groups of CoMP transmission points and scheduled users for multi-user multi-input multi-output (MU-MIMO) operation with partial channel state information (CSI) and low complexity. First, based on the analysis of composite channel characteristics and feedback overhead, the large-scale channel matrix is proposed for MU-MIMO precoding by using long-term channel statistics. The benefits are easy to acquire and highly reduced feedback overhead. The throughput loss is demonstrated to be acceptable in contrast to using instantaneous CSI via linear precoding. Second, a downlink construction algorithm is developed based on the greedy process, in which a simple channel orthogonality metric is proposed to pre-select the links that are worthwhile for joint processing so as to reduce the scheduling complexity and avoid ill-conditioned channel matrix. About 20% throughput gain is achieved over non-coordination scheme using the same scheduling criterion. The proposed scheme is not limited to any structures of CoMP cooperating set or wireless environments.

Cellular networks with a dense reuse of spectrum strongly suffer from intercell interference (ICI). By coordinating the resource allocations (RA) of the individual base stations (BS) the ICI can be effectively mitigated. Since centralized ICI coordination schemes become prohibitive in large-scale networks, we propose a decentralized RA procedure that coordinates the local RA steps among the BSs. Our scheme efficiently suppresses the so-called domino effect where a RA step of a single BS may impact the entire network by causing a large number of subsequent RA adaptations at remote BSs. The objective of our proposed RA procedure is to provide high degrees of fairness among the users. Since such an objective usually results in poor overall system performance (e.g. high blocking rates) we extended the RA procedure for a cooperative user detection scheme that employs an ICI cancellation. The results indicate significant gains in user fairness for both cases, ICI coordination based on short-term as well as long-term channel statistics.

Integrated access and backhaul (IAB) network consists of base station (BS), relay nodes (RNs), and user-equipments (UEs), where BS and RNs exchange UE data via wireless in-band backhaul while sharing the same frequency-time resources with access links. In this paper, a flexible time-division-duplex (TDD)-based IAB network is considered where RNs and BS are assigned to distinct uplink (UL) or downlink (DL) transmission modes to mitigate conventional half-duplex (HD) loss at RNs. An iterative beamformer design is proposed to manage the resulting cross-channel interference and to allocate wireless backhaul and access resources jointly over two consecutive data delivery intervals required for communications between the BS and UEs through HD RNs. Dynamic traffic behavior is handled via weighted queue minimization objective, and user-specific UL/DL queues are also introduced at RNs to guarantee reliable end-to-end data delivery. Bi-directional forward-backward training via spatially precoded over-the-air pilot signaling is employed to allow decentralized beamformer design across all the nodes. A novel user allocation method is proposed to assign UEs to BS or RNs based only on long-term channel statistics and some practical IAB limitations. The numerical examples illustrate the superior system performance of the considered flexible IAB in comparison to the conventional HD relaying system.

Typical formulations of max-min weighted SIR problems involve either a total power constraint or individual power constraints. These formulations are unable to handle the complexities in multicell networks where each base station can be subject to its own sum power constraint. This paper considers the max-min weighted SIR problem subject to multiple weighted-sum power constraints, where the weights can represent relative power costs of serving different users. First, we derive the uplink-downlink duality principle by applying Lagrange duality to the single-constraint problem. Next, we apply nonlinear Perron-Frobenius theory to derive a closed-form solution for the multiple-constraint problem. Then, by exploiting the structure of the closed-form solution, we relate the multiple-constraint problem with its single-constraint subproblems and establish the dual uplink problem. Finally, we further apply nonlinear Perron-Frobenius theory to derive an algorithm which converges geometrically fast to the optimal solution.

Herein, we study transmit beamforming techniques in an underlay cognitive mode for the coexistence of satellite and terrestrial networks with the satellite forward link as primary and the terrestrial downlink as secondary. Since geostationary satellite terminals have predetermined propagation characteristics so that they always point towards the geostationary satellite, the interference received by the satellite terminals from the terrestrial Base Station (BS) is confined in an angular sector. Based on this a priori knowledge, we propose transmit beamforming techniques at the BS to maximize the Signal to Interference plus Noise Ratio (SINR) towards the desired Secondary User (SU) and to mitigate the interference towards the primary satellite terminals. Different types of Linearly Constrained Minimum Variance (LCMV) techniques have been proposed for our considered scenario where the exact locations and the number of satellite terminals within a specific angular sector are not known while designing the beamformer. Furthermore, an optimization problem is formulated for maximizing the SU rate and it is shown that the worst case SU rate depends on the Primary User (PU) distance, PU interference threshold and the angular separation of the desired SU from the region of interest.