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Abstract In this paper, the flexibility of unmanned aerial vehicles (UAVs), as well as the benefits of coordinated multi-point (CoMP) transmission, are utilized for mitigating the interference in cellular networks. Specifically, the joint problem of CoMP clusters and UAVs’ trajectories is addressed for downlink transmission in a UAV-assisted cellular system. The problem is presented as a non-convex optimization problem that aims to maximize the sum rate of the ground users by taking into account the clustering, UAV mobility and backhaul capacity constraints. Since the formulated problem is known to be NP-hard, we partition it into two sub-problems. Particularly, by using coalitional game theory, the CoMP clusters are obtained with a given UAVs’ trajectories. Then, UAVs’ trajectories are optimized with given CoMP clusters using successive convex approximation technique. Based on the block coordinate descent method, the two sub-problems are solved alternatively until convergence. Numerical results are conducted and demonstrated the effectiveness of the proposed algorithm.

In this paper, the flexibility of unmanned aerial vehicles (UAVs), as well as the benefits of coordinated multi-point (CoMP) transmission, are utilized for mitigating the interference in cellular networks. Specifically, the joint problem of CoMP clusters and UAVs' trajectories is addressed for downlink transmission in a UAV-assisted cellular system. The problem is presented as a non-convex optimization problem that aims to maximize the sum rate of the ground users by taking into account the clustering, UAV mobility and backhaul capacity constraints. Since the formulated problem is known to be NP-hard, we partition it into two sub-problems. Particularly, by using coalitional game theory, the CoMP clusters are obtained with a given UAVs' trajectories. Then, UAVs' trajectories are optimized with given CoMP clusters using successive convex approximation technique. Based on the block coordinate descent method, the two sub-problems are solved alternatively until convergence. Numerical results are conducted and demonstrated the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the dynamic power allocation for a visible light communication (VLC) cellular system consisting of two coordinating attocells, each equipped with one access-point (AP). The coordinated multipoint (CoMP) between the two cells is introduced to assist users experiencing high inter-cell-interference (ICI). Specifically, the coordinated zero-forcing (ZF) precoding is used to cancel the ICI at the users located near the centers of the cells, whereas the joint transmission (JT) is employed to eliminate the ICI at the users located at the edge of both cells and to improve their receptions as well. Furthermore, two multiple access techniques are invoked within each cell, namely, non-orthogonal-multiple-access (NOMA) and cooperative non-orthogonal-multiple-access (C-NOMA). Hence, two multiple access techniques are proposed for the considered multi-user multi-cell system, namely, the CoMP-assisted NOMA scheme and the CoMP-assisted C-NOMA scheme. For each scheme, two power allocation frameworks are formulated each as an optimization problem, where the objective of the former is maximizing the network sum data rate while guaranteeing a certain quality-of-service (QoS) for each user, whereas the goal of the latter is to maximize the minimum data rate among all coexisting users. The formulated optimization problems are not convex, and hence, difficult to be solved directly unless using heuristic methods, which comes at the expense of high computational complexity. To overcome this issue, optimal and low complexity power allocation schemes are derived. In the simulation results, the performance of the proposed CoMP-assisted NOMA and CoMP-assisted C-NOMA schemes are compared with those of the CoMP-assisted orthogonal-multiple-access (OMA) scheme, the C-NOMA scheme and the NOMA scheme, where the superiority of the proposed schemes are demonstrated. Finally, the performance of the proposed schemes and the considered baselines is evaluated while varying various system parameters. [ABSTRACT FROM AUTHOR]

In this paper, we consider a non-orthogonal multiple access (NOMA) system with coordinated multi-point (CoMP), which is used in 5G cellular networks to guarantee the rate requirements from the different edge users. Based on the China Family Panel Studies (CFPS) dataset, we use several learning algorithms to predict users' rate requirements according to their profiles. We propose a many-to-many two-side subchannel–user matching strategy, which can classify users into cell-center users, high-rate requirement edge users, and low-rate requirement edge users based on their status and learning prediction results, and pair users with different subchannels to form joint transmission CoMP (JT-CoMP) subchannels and dynamic point selection CoMP (DPS-CoMP) subchannels. Furthermore, a discrete power allocation algorithm based on group search is proposed. Simulation results show that our proposed algorithm outperforms the traditional NOMA-CoMP algorithm and maximum throughput (MT) NOMA-CoMP algorithm. It maximizes the rate of high-rate requirement edge users while guaranteeing user fairness. [ABSTRACT FROM AUTHOR]

Caching at mobile devices and leveraging cooperative device-to-device (D2D) communications are two promising approaches to support massive content delivery over wireless networks while mitigating the effects of interference. To show the impact of cooperative communication on the performance of cache-enabled D2D networks, the notion of device clustering must be factored in to convey a realistic description of the network performance. In this regard, this paper develops a novel mathematical model, based on stochastic geometry and an optimization framework for cache-assisted coordinated multi-point (CoMP) transmissions with clustered devices. Devices are spatially distributed into disjoint clusters and are assumed to have a surplus memory to cache files from a known library, following a random probabilistic caching scheme. Desired contents that are not self-cached can be obtained via D2D CoMP transmissions from neighboring devices or, as a last resort, from the network. For this model, we analytically characterize the offloading gain and rate coverage probability as functions of the system parameters. An optimal caching strategy is then defined as the content placement scheme that maximizes the offloading gain. For a tractable optimization framework, we pursue two separate approaches to obtain a lower bound and a provably accurate approximation of the offloading gain, which allows us to obtain optimized caching strategies. Remarkably, if we replace the obtained expression for offloading gain with its lower bound, we can find a suboptimal caching strategy that is not only described via analytical formulas but can also show an improvement over the state-of-the-art caching schemes. Results reveal that cooperative transmission becomes more appealing in denser D2D caching networks and adverse interference conditions, which is the case of the imminent Internet of Things (IoT) and ns era. [ABSTRACT FROM AUTHOR]

Applications of Unmanned aerial vehicles (UAVs) have advanced rapidly in recent years. The UAVs are used for a variety of applications, including surveillance, disaster management, precision agriculture, weather forecasting, etc. In near future, the growing number of UAV applications would necessitate densification of UAV infrastructure (ground radio station (GRS) and ground control station (GCS)) at the expense of increased energy consumption for UAV communications. Maximizing the energy efficiency of this UAV infrastructure is important. Motivated by this, we propose joint resource allocation and UAV scheduling with GRS sleeping (GRSS). Further, we propose the use of coordinated multi-point (CoMP) with joint transmission (JT) and non-orthogonal multiple access (NOMA) along with GRSS to increase the coverage and data rates, respectively. Through exhaustive simulation results, we show that the proposed CoMP along with GRSS results in up to 10% higher energy savings and 24% increase in coverage. Further, NOMA along with GRSS results in up to 9% enhancement in throughput of the system.

In this paper, we consider a non-orthogonal multiple access (NOMA) system with coordinated multi-point (CoMP), which is used in 5G cellular networks to guarantee the rate requirements from the different edge users. Based on the China Family Panel Studies (CFPS) dataset, we use several learning algorithms to predict users’ rate requirements according to their profiles. We propose a many-to-many two-side subchannel–user matching strategy, which can classify users into cell-center users, high-rate requirement edge users, and low-rate requirement edge users based on their status and learning prediction results, and pair users with different subchannels to form joint transmission CoMP (JT-CoMP) subchannels and dynamic point selection CoMP (DPS-CoMP) subchannels. Furthermore, a discrete power allocation algorithm based on group search is proposed. Simulation results show that our proposed algorithm outperforms the traditional NOMA-CoMP algorithm and maximum throughput (MT) NOMA-CoMP algorithm. It maximizes the rate of high-rate requirement edge users while guaranteeing user fairness.

Small cell base stations (SBSs) are being developed as a way of expanding the coverage of cellular networks. However, the power consumption of small cell networks has become an acute problem. To mitigate this problem, we propose a new power-saving scheme based on coordinate multi-point (CoMP) transmission for densely deployed small cell networks. This scheme turns off lightly loaded SBSs and switches their users to the cooperative clusters formed by their neighbor SBSs. The cooperative clusters adopt the virtual multiple-input multiple-output (MIMO) technology to serve the users in the switched-off SBSs. To achieve high power-efficiency, we first model the power consumption of all the SBSs by considering the quality of service of users in the switched-off SBSs and then provide in-depth proofs and analysis according to characteristics of small cell networks. Our extensive simulation results show that the proposed algorithm improves system power-saving efficiency significantly. [ABSTRACT FROM AUTHOR]

This paper studies an unmanned aerial vehicle (UAV)-enabled two-user interference channel for wireless powered communication networks (WPCNs). In this system, two UAVs wirelessly charge two low-power Internet-of-things (IoT)-devices on the ground and collect information from them. We consider two scenarios when both UAVs cooperate in energy transmission and/or information reception via interference coordination and coordinated multi-point (CoMP), respectively. For both scenarios, the UAVs’ trajectories are designed to not only enhance the wireless power transfer (WPT) efficiency in the downlink, but also mitigate the co-channel interference for wireless information transfer (WIT) in the uplink. In particular, the objective is to maximize the uplink common (minimum) throughput of the two IoT-devices over a finite UAV mission period, by jointly optimizing the trajectories of both UAVs and the downlink/uplink wireless resource allocation, subject to the maximum flying speed and collision avoidance constraints for UAVs, as well as the individual energy neutrality constraints at IoT-devices. Under both scenarios with interference coordination and CoMP, we first obtain the optimal solutions to the two common-rate maximization problems for the special case with sufficiently long UAV mission duration. Next, we obtain high-quality solutions for the practical case with finite UAV mission duration by using the alternating optimization and successive convex approximation (SCA). Numerical results show that the proposed designs significantly outperform benchmark schemes, and the utilization of CoMP achieves much higher uplink throughput than interference coordination. [ABSTRACT FROM AUTHOR]

To improve the system throughput, this paper proposes a network non-orthogonal multiple access (N-NOMA) technique for the uplink coordinated multi-point transmission (CoMP). In the considered scenario, multiple base stations collaborate with each other to serve a single user, referred to as the CoMP user, which is the same as for conventional CoMP. However, unlike conventional CoMP, each base station in N-NOMA opportunistically serves an extra user, referred to as the NOMA user, while serving the CoMP user at the same bandwidth. The CoMP user is typically located far from the base stations, whereas users close to the base stations are scheduled as NOMA users. Hence, the channel conditions of the two kinds of users are very distinctive, which facilitates the implementation of NOMA. Compared to the conventional orthogonal multiple access-based CoMP scheme, where multiple base stations serve a single CoMP user only, the proposed N-NOMA scheme can support larger connectivity by serving the extra NOMA users, and improve the spectral efficiency by avoiding the CoMP user solely occupying the spectrum. A stochastic geometry approach is applied to model the considered N-NOMA scenario as a Poisson cluster process, based on which insightful closed-form or quasi closed-form analytical expressions for outage probabilities and ergodic rates are obtained. Numerical results are presented to show the accuracy of the analytical results and also demonstrate the superior performance of the proposed N-NOMA scheme. [ABSTRACT FROM AUTHOR]

Both interference alignment (IA) and interference neutralization (IN) are exploited for coordinated multi-point (CoMP) communications. With the cooperation of the base station (BS), a transmit precoder and a receive filter are jointly designed, and concurrent transmissions of multiple data streams are then enabled. In the design of a precoder, the IN is applied to the interferences carrying the same data so as to align the interfering signals in the opposite direction in a subspace. On the other hand, for interferences carrying different information, IA is employed to align them in the same direction in a subspace, thus reducing the interference signal observed at the receiver side. Based on different precoding schemes at the transmitter’s side, receivers adopt zero forcing (ZF) so as to recover the desired data. The proposed IA- and IN-based CoMP (IAN-CoMP) mechanism can achieve effective interference cancellation and suppression by exploiting limited and flexible collaboration at the BS side. It can also make a flexible tradeoff between the cooperation overhead and the system’s achievable degrees of freedom (DoFs). We extend the mechanism to general cases where the antenna configurations at both the transmitter and receiver sides, the number of transmitters participating in CoMP, and that of simultaneously served users are variable. Moreover, we discuss both single-location and multi-location-based realizations of the IAN-CoMP. Finally, by defining the average transmit and receive cooperation order, we analyze the upper bound for IAN-CoMP. Our in-depth simulation shows that the IAN-CoMP can significantly improve the spectral efficiency (SE) for cell-edge users. [ABSTRACT FROM AUTHOR]

Coordinated Multi-Point (CoMP) is an important technique in B4G/5G networks. With CoMP, multiple base stations can be clustered to compose a cooperating set to improve system throughput, especially for the users in cell edges. Existed studies have discussed how to mitigate overloading scenarios and enhance system throughput with CoMP statically. However, static cooperation fixes the set size and neglects the fast-changing of B4G/5G networks. Thus, this paper provides a full study of off-peak hours and overloading scenarios. During off-peak hours, we propose to reduce BSs’ transmission power and use the free radio resource to save energy while guaranteeing users’ QoS. In addition, if large-scale activities happen with crowds gathering or in peak hours, we dynamically compose the cooperating set based on instant traffic requests to adjust base stations’ BSs’ transmission power; thus, the system will efficiently offload the traffic to the member cells which have available radio resources in the cooperating set. Experimental results show that the proposed schemes enhance system throughput, radio resource utilization, and energy efficiency, compared to other existing schemes.

In this paper, a fundamental study of energy efficiency (EE) optimization for coordinated multi-point (CoMP) simultaneous wireless information and power transfer (SWIPT) heterogeneous networks (HetNets) is provided. We aim to optimize the EE while satisfying certain quality-of-service requirements in regard to transmission rate and energy harvesting at both the macro cell and small cells. The corresponding joint beamforming and power allocation in the presence of intra- and inter-cell interference constitutes an EE maximization problem that is non-convex, and hence, very challenging to solve. In order to solve this problem, we propose to separate the beamforming design and power allocation processes. First, we adopt linear zero-forcing (ZF) beamforming to suppress the multi-user interference from both the energy harvesting users (EH-UEs) as well as the information decoding UEs (ID-UEs), thus transforming the HetNet under consideration to a virtual point-to-point system. An efficient power allocation algorithm is then developed to maximize the corresponding EE. On the other hand, the ZF strategy does not utilize the notion that interference benefits the EH-UEs. As a result, we propose a partial ZF approach by differentiating the EH-UEs and ID-UEs in order to further improve the EE. Our findings show that the EE can be significantly improved through the integration of CoMP-SWIPT in HetNets. [ABSTRACT FROM AUTHOR]

This paper provides an analytical performance characterization of both the uplink (UL) and downlink (DL) user-centric network multiple-input multiple-output (MIMO) systems, where a cooperating base station (BS) cluster is formed for each user individually and the clusters for different users may overlap. In this model, cooperating BSs (each equipped with multiple antennas) jointly perform zero-forcing beamforming to the set of single-antenna users associated with them. As compared with a baseline network MIMO system with disjoint BS clusters, the effect of user-centric clustering is that it improves signal strength in both the UL and DL, while reducing cluster-edge interference in the DL. This paper quantifies these effects by assuming that BSs and users form Poisson point processes and by further approximating both the signal and interference powers using Gamma distributions of appropriate parameters. We show that BS cooperation provides significant gain as compared to single-cell processing for both the UL and DL, but the advantage of user-centric clustering over the baseline disjoint clustering system is significant for the DL cluster-edge users only. Although the analytic results are derived with the assumption of perfect channel state information and infinite backhaul between the cooperating BSs, they nevertheless provide architectural insight into the design of the future cooperative cellular networks. [ABSTRACT FROM AUTHOR]

We propose a novel proactive caching strategy with social community-aware learning in the Coordinated Multi-Point (CoMP)-enabled small-cell network. First, it predicts content request probabilities using community-aware non-negative matrix factorization (CNMF) with implicit feedback. The CNMF-based proactive caching algorithm then makes a caching decision by considering estimated content request probabilities of both the associated and neighbor users to closely cooperate with CoMP. Simulation results show that the proposed caching strategy improves the performance in terms of the content hit ratio and the average content delivery completion time according to the cache size. Furthermore, the performance of the proposed caching with and without CoMP is evaluated by varying the cache size and the small-cell base station density. [ABSTRACT FROM AUTHOR]

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In this paper, the energy-spectral efficiency (ESE) benefiting from the joint optimization of coordinated multi-point (CoMP) transmission and base station (BS) deployment is evaluated in the context of dense large-scale cellular network. We first derive a closed-form network ESE expression for a large-scale CoMP-enhanced network, which allows us to quantify the influence of key network parameters on the achievable network ESE, including the BS density and the cooperation activation probability, characterized by a CoMP activation factor as well as the users’ behaviors, such as their geographical mobile-traffic intensity and average user rate. With the aid of this tractable ESE expression and for a given BS density, we next formulate a cellular-scenario-aware CoMP activation optimization problem while considering the users’ outage probability as constraints to maximize the network’s ESE. We then jointly optimize the CoMP activation factor and the BS density to maximize the network ESE, again under the constraint of the users’ outage probability. Our simulation results confirm the accuracy of our analysis and verify the impact of several key parameters on the network ESE. Finally, the ESE improvement of our proposed strategies is evaluated under diverse scenarios, which provides valuable insight into the joint CoMP and BS deployment optimization in dense large-scale cellular networks. [ABSTRACT FROM PUBLISHER]

This paper studies user-specific clustering for a downlink cloud radio access network (C-RAN), where a central unit (CU), connected to all base stations (BSs) via limited-capacity backhaul links, coordinates the BSs to form cooperative clusters for every user. By taking into account the training overhead for channel estimation in C-RAN, we design the clustering scheme aimed at maximizing the average net throughput of the network subject to the constraint on backhaul capacity, where a hybrid coordinated multipoint (CoMP) transmission mode is considered. The proposed clustering scheme can be operated in a semi-dynamic manner merely based on large-scale channel information, has low computational complexity, and performs close to the optimal scheme found by exhaustive searching. Under two special cases where the backhaul capacity is very stringent and unlimited, the proposed scheme is then tailored for pure coordinated beamforming (CB) mode and pure joint transmission (JT) mode to further reduce the clustering complexity. Simulation results show that the proposed semi-dynamic clustering schemes are superior to the dynamic clustering scheme due to the reduction of required training overhead. [ABSTRACT FROM AUTHOR]

This paper studies the energy management in coordinated multipoint (CoMP) systems powered by smart grids, where each base station (BS) with local renewable energy generation is allowed to implement two-way energy trading with the grid. Due to the uneven renewable energy supply and communication energy demand over distributed BSs, as well as the difference in the prices for their buying/selling energy from/to the grid, it is beneficial for the cooperative BSs to jointly manage their energy trading with the grid and energy consumption in CoMP-based communication for reducing the total energy cost. Specifically, we consider the downlink transmission in one CoMP cluster by jointly optimizing the BSs' purchased/sold energy units from/to the grid and their cooperative transmit precoding to minimize the total energy cost subject to the given quality-of-service (QoS) constraints for the users. First, we obtain the optimal solution to this problem by developing an algorithm based on techniques from convex optimization and uplink–downlink duality. Next, we propose a suboptimal solution of lower complexity than the optimal solution, where zero-forcing (ZF)-based precoding is implemented at the BSs. Finally, through extensive simulations, we show the performance gain achieved by our proposed joint energy trading and communication cooperation schemes in terms of energy cost reduction, as compared with conventional schemes that separately design communication cooperation and energy trading. [ABSTRACT FROM AUTHOR]

In this paper, a sectored Coordinated Multi-Point (CoMP) scheme with constrained greedy resource allocation method is proposed to avoid the inter-cell interference and has a fair service provision advantage for a wireless cellular communication system. The proposed sectored CoMP is evaluated at the long term evolution system and compared with the traditional inter-cell interference coordination (ICIC) methods, such as the partial frequency reuse and the soft frequency reuse. Results show that the proposed scheme has a better ICIC performance than the conventional methods. Besides, the proposed sectored CoMP with constrained greedy resource allocation also has better system frequency utilization and fair cell-edge user data service advantages compared with the well-known proportional fair scheduling. [ABSTRACT FROM AUTHOR]

In coordinated multi-point (CoMP) transmission systems, coordinated base stations (BSs) are geographically separated and have their own oscillators, thereby causing multiple carrier frequency offsets (CFOs) at the receiver. Therefore, perfect synchronization cannot be obtained at the mobile station (MS), resulting in severe interference. To resolve this problem, this study proposes a novel transceiver structure with improved robustness toward interference. With the knowledge of CFO and channel frequency response, a closed-form solution is derived for the sub-optimal CFO compensation value to minimize the approximated upper bound of the inter-carrier interference (ICI) plus noise power for environments with large-scale fading. The results reveal that the sub-optimal CFO compensation value is a function of both the degree of large-scale fading and the value of CFOs. Simulation results demonstrate that the proposed method significantly outperforms the existing structures and exhibits improved performance in terms of bit error rate. [ABSTRACT FROM PUBLISHER]

Recently, Heterogeneous Network (HetNet) with Coordinated Multi-Point (CoMP) scheme is introduced into Long Term Evolution-Advanced (LTE-A) systems to improve digital services for User Equipments (UEs), especially for cell-edge UEs. However, Radio Resource Management (RRM), including Resource Block (RB) scheduling and Power Allocation (PA), in this scenario becomes challenging, due to the intercell cooperation. In this paper, we investigate the RRM problem for downlink transmission of HetNet system with Joint Processing (JP) CoMP (both joint transmission and dynamic cell selection schemes), aiming at maximizing weighted sum data rate under the constraints of both transmission power and backhaul capacity. First, joint RB scheduling and PA problem is formulated as a constrained Mixed Integer Programming (MIP) which is NP-hard. To simplify the formulation problem, we decompose it into two problems of RB scheduling and PA. For RB scheduling, we propose an algorithm with less computational complexity to achieve a suboptimal solution. Then, according to the obtained scheduling results, we present an iterative Karush-Kuhn- Tucker (KKT) method to solve the PA problem. Extensive simulations are conducted to verify the effectiveness and efficiency of the proposed algorithms. Two kinds of JP CoMP schemes are compared with a non-CoMP greedy scheme (max capacity scheme). Simulation results prove that the CoMP schemes with the proposed RRM algorithms dramatically enhance data rate of cell-edge UEs, thereby improving UEs' fairness of data rate. Also, it is shown that the proposed PA algorithms can decrease power consumption of transmission antennas without loss of transmission performance. [ABSTRACT FROM AUTHOR]

In CoMP, when collaborative users are in the edge of cooperation area, the users’ performance can’ l he improved for the reason that the base stations (BSs) in the cluster which limited by the radiation range can't cooperate for these users. In order to solve this problem, this paper introduced the scheme which combined CoMP and DF Relay technology. The scheme measured the performance of the users,divided the collaborative users which located in the collaboration edge area into the relay users, and forwarded data for them through the relay. As for the resource allocation conflict problem of CoMP-Relay system, it proposed the joint resouce allocation algorithm based on proportion fair, and the algorithm introduced the water flood algorithm to achieve the remaining resources allocation of BSs and Relay. Hie simulation results indicate that the joint resouce allocation algorithm not only improve the communication quality of edge users, but also enhance the throughput of system. [ABSTRACT FROM AUTHOR]

We consider transmit rate allocation and the associated cooperative decoding strategies in uplink multi-cell networks where base stations (BSs) are connected by capacity-limited backhaul (BH) links. In particular, we propose two cooperative group decoding (CGD) schemes for the BSs with partial decoding results shared via the BH. In parallel CGD, at each stage, each BS locally selects and jointly decodes a group of users by treating the remaining users as noise; then it forwards some partial decoding results to other BSs via the BH. After subtracting the decoded users and the received decoding results from other BSs, each BS repeats the same procedure until all its designated users are decoded. On the other hand, in sequential CGD, each user can be decoded at any BS. At each stage only one BS is selected to decode a group of users, which then forwards the decoding results to other BSs for interference cancellation. The process is repeated until all users are decoded. Numerical results are provided to demonstrate that the proposed CGD schemes offer significant gain in terms of the achievable rates. [ABSTRACT FROM PUBLISHER]

Coordinated multi-point transmission (CoMP) is considered as a strategic approach to handle inter-cell interference, hence increasing spectral efficiency in interference-limited cellular networks. This paper studies a CoMP downlink transmission with delayed and quantized channel state information feedback through a capacity-limited uplink channel. The delay effects and quantization error as well as large scale path loss potentially degrade entire network performance. Under this consideration, we first characterize the system performance in terms of achievable rate for two typical CoMP techniques, namely joint processing (JP) and coordinated beamforming (CBF), in a multi-cell network. Accurate closed-form expressions are derived for evaluating the CoMP performance. Based on the derived results, an adaptive transmission strategy of switching between JP and CBF is proposed to maximize the system throughput and the operating regions of the two schemes are provided under different system setup parameters. Simulation verifies that the superiority of JP or CBF depends on system parameters including feedback delay, codebook size as well as CoMP user locations. [ABSTRACT FROM AUTHOR]

Coordinated multi-point (CoMP) joint transmission (JT) is an effective technique to improve the quality of services for cell edge user. In JT, multiple points precode jointly to reduce the interference of the cell edge, thereby improve the spectral efficiency. Combining orthogonal projection (OP) with sorted QR decomposition (SQRD), the paper proposes two JT methods which are respectively named as OP-ZF-SQRD and OP-MMSE-SQRD. Both methods use OP to eliminate multi-user interference, and decompose the multi-user system into multiple parallel single-user systems without interference. Then, ZF-SQRD or MMSE-SQRD is applied to each single-user system separately. Simulation results show that compared to joint transmitter zero forcing (JT-ZF) and block diagonalization (BD) methods, the two proposed methods have obvious advantages in performance. Meanwhile, the two proposed methods can not only eliminate multi-user interference but also mitigate multi-stream interference of each user effectively, thereby they improve the quality of services and the spectral efficiency for the cell edge. [ABSTRACT FROM AUTHOR]

Heterogeneous networks (HetNets) consisting of macro- and pico-cells can well tackle the contradictory requirements on large coverage of the network and high data rate at the hot spots. In this paper, we study energy-efficient precoding for coordinated multi-point (CoMP) transmission for HetNets. We formulate a problem that maximizes the energy efficiency under the constraints of individual date rate requirement from each user, maximal transmit power of each base station (BS), and zero-forcing (ZF) for a HetNet where the macro-BS cooperates with multiple pico-BSs. We then simplify the problem with the help of the practical topology of HetNets where the macro-BS cooperates with each of the pico-BSs. By introducing the subspace decomposition method and exploiting the feature of HetNets, we obtain the structure of the optimal ZF CoMP precoder. To reduce the computational complexity and hence the circuit power consumed for signal processing, we propose a suboptimal ZF precoder with closed-form expression for the HetNets with isolated pico-cells. We demonstrate the performance of the proposed ZF precoders by comparing with several existing optimal linear precoders. [ABSTRACT FROM PUBLISHER]

This paper aims to explore the potential of a high spectrum efficiency (SE) technology, coordinated multi-point (CoMP) transmission, for improving energy efficiency (EE) of downlink cellular networks. To this end, a traffic-aware mechanism, named cooperative base station (BS) doze, is introduced and optimized. The key idea is to allow BS idling by exploiting the delay tolerance of some users as well as the short-term spatio-temporal traffic fluctuations in the network, and to increase the opportunity of the idling by using CoMP transmission. The cooperative BS doze strategy involves BS time-slot doze pattern, and multicell user scheduling and cooperative precoding with different amount of data sharing, which are jointly optimized in a unified framework. To ensure various performance requirements of multiple users including delay tolerance and data rate, we maximize the network EE under different time-average rate constraints for different users, where the consumptions on transmit power, circuitry power and backhauling power are taken into account. We then propose a hierarchical iterative algorithm to solve the optimization problem. Simulations under practical power consumption parameters demonstrate that cooperative BS doze can provide substantial EE gain and support high data rate services with high achievable SE. [ABSTRACT FROM AUTHOR]

In 3GPP LTE-A, Coordinated Multi-Point (CoMP) is adopted to enhance the transmission rates of edge users. To maximize the total downlink throughput of all edge users, it is crucial to properly determine the set of simultaneously served users in each physical resource block (PRB) and the cooperative base stations (BSs) for each scheduled user, as well as the transmit power of the BSs. Based on the reference signal receiving power (RSRP) of each edge user, we first propose two simple and integrated transmission scheduling algorithms, one distributed and the other centralized, to choose cell-edge users and cooperative BSs in each PRB. With the scheduling results, the classic Water-Filling (WF) algorithm is carried out over all PRBs at each BS to get an initial single cell power allocation. To take the interference among different cooperative BS sets into account, we further formulate a non-cooperative power allocation game to adjust the initial power allocation for interference coordination, where the initial power allocation provides the strategy space of the game for each BS. This increases the total downlink throughput of edge users over all BSs. We prove that the game has a unique Nash Equilibrium (NE), and design an algorithm to find the NE. Performance gain is then demonstrated through extensive simulation studies. [ABSTRACT FROM PUBLISHER]

This paper studies transmission strategies for downlink time division duplex coordinated multi-point (CoMP) systems with non-ideal uplink-downlink channel reciprocity, where several multi-antenna base stations (BSs) jointly serve multiple single-antenna users. Due to the inherent antenna calibration errors among different BSs, the uplink-downlink channels are no longer reciprocal such that the channel information at the BSs is with multiplicative noises. To mitigate the performance degradation caused by the imperfect channels, we employ a weighted sum rate estimate as the objective function for robust precoder design. To show the impact of data sharing on the performance of CoMP under the non-ideal channel reciprocity, we provide a unified framework for designing precoder for CoMP systems with different amount of data sharing. The optimal parametric linear precoder structure that maximizes the weighted sum rate estimate under per-BS power constraints is characterized, based on which a closed-form robust signal-to-leakage-plus-noise ratio (SLNR) precoder is proposed to exploit the statistics of the calibration errors. Simulation results show that the proposed precoder in conjunction with user scheduling provides substantial performance gain over Non-CoMP transmission and the CoMP transmission with non-robust precoders. [ABSTRACT FROM AUTHOR]

This paper studies an uplink multicell joint processing model in which the base-stations are connected to a centralized processing server via rate-limited digital backhaul links. We propose a simple scheme that performs Wyner-Ziv compress-and-forward relaying on a per-base-station basis followed by successive interference cancellation (SIC) at the central processor. The proposed scheme has a significantly reduced complexity as compared to joint decoding, resulting in an easily computable achievable rate region. Although suboptimal in general, this paper shows that the proposed per-base-station SIC scheme can achieve the sum capacity of a class of Wyner cellular model to within a constant gap. This paper also establishes that in order to achieve to within a constant gap to the maximum SIC rate with infinite backhaul, the limited-backhaul system must have backhaul capacities that scale logarithmically with the signal-to-interference-and-noise ratios (SINRs) at the base-stations. Further, this paper studies the optimal backhaul rate allocation problem for the per-base-station SIC model with a total backhaul capacity constraint, and shows that the sum-rate maximizing allocation should also have individual backhaul rates that scale logarithmically with the SINR at each base-station. Finally, the proposed per-base-station SIC scheme is evaluated in a practical multicell network to quantify the performance gain brought by multicell processing. [ABSTRACT FROM AUTHOR]

Orthogonal frequency division multiplexing (OFDM) combined with the coordinated multi-point (CoMP) transmission technique has been proposed to improve performance of the receivers located at the cell border. However, the inevitable carrier frequency offset (CFO) will destroy the orthogonality between subcarriers and induce strong inter-carrier interference (ICI) in OFDM systems. In a CoMP-OFDM system, the impact of CFO is more severe because of the mismatch in carrier frequencies among multiple transmitters. To reduce performance degradation, CFO estimation and compensation is essential. For simultaneous estimation of multiple CFOs, the performance of conventional CFO estimation schemes is significantly degraded by the mutual interference among the signals from different transmitters. In this work, our goal is to propose an effective approach that can simultaneously estimate multiple CFOs in the downlink by using the composite signal coming from multiple base stations corresponding to CoMP transmission. Based on the Zadoff-Chu sequences, we design an optimal set of training sequences, which minimizes the mutual interference and is robust to the variations in multiple CFOs. Then, we propose a maximum likelihood (ML)-based estimator, the robust multi-CFO estimation (RMCE) scheme, for simultaneous estimation of multiple CFOs. In addition, by incorporating iterative interference cancellation into the RMCE scheme, we propose an iterative scheme to further improve the estimation performance. According to the simulations, our scheme can eliminate the mutual interference effectively, approaching the Cramer-Rao bound performance. [ABSTRACT FROM PUBLISHER]

Coordinated scheduling/beamforming (CSB), which belongs to the coordinated multi-point (CoMP) transmission, has received lots of attention recently due to its great potential to mitigate inter-cell interference (ICI) and to increase the cell-edge throughput, and meanwhile it only requires limited base station cooperation and is easy to implement. However, to the best of our knowledge, there are no effective scheduling algorithms with low complexity and overhead in CoMP-CSB scenario as yet. Thus, in this paper, we propose three novel opportunistic scheduling algorithms in CoMP-CSB scenario. All of them jointly consider the intended channel condition of the scheduled user from its serving cell and the orthogonality between the intended channel and the corresponding interference channels to concurrently scheduled users in nearby cells, thus exploiting multi-user diversity (MUD) and mitigating ICI at the same time. Algorithm 1 cooperatively chooses the most orthogonal user pair within a candidate user set in which all users have a large local channel feedback, while Algorithm 2 concurrently schedules the user pair with the largest ratio between the local channel feedbacks and the aforementioned orthogonality within the same candidate user set. Algorithm 3 performs in the way similar to the proportional fairness scheduling, while making a proper modification for its usage in CoMP-CSB scenario. The performance of the proposed scheduling algorithms are evaluated through simulation. Results show that, they all can significantly enhance the received signal to interference plus noise ratio (SINR) with relatively good fairness guarantee, thus achieving larger throughputs and utilities than several well-known scheduling algorithms. Algorithm 2 even outperforms Algorithm 1 when the aforementioned candidate user set is big enough in size and has a bit more overhead/complexity. Furthermore, Algorithms 3 is the best one among all the three proposed algorithms, but it requires more overhead/complexity than Algorithm 1 and 2. Finally, we give the optimal parameter for all of the three proposed algorithms, which can make a good tradeoff between performance and overhead/complexity. [ABSTRACT FROM AUTHOR]