Non-coherent Joint Transmission Research Articles

Distributed Noncoherent Joint Transmission Based on Multi-Agent Reinforcement Learning for Dense Small Cell Networks

In dense small cell networks, the coordinated multi-point noncoherent joint transmission (JT) is a key technique to mitigate inter-cell interference and enhance network capacity. However, the capacity-maximizing power control and beamforming problem subject to a total transmit power constraint at each individual small cell base station (BS) is inherently nonconvex and NP-hard. To solve this problem, most existing algorithms require global channel state information (CSI) and a lot of computations, which are infeasible and impractical in dynamic wireless networks with limited computing power and link capacity. In this paper, we characterize a low-dimensional solution structure for the power control of the sum-rate maximization problem in time division duplex (TDD) dense small cell networks. Taking advantage of this low-dimensional structure, a distributed noncoherent JT scheme based on multi-agent reinforcement learning (MARL) is proposed to maximize the sum-rate of the dense small cell networks with reduced information overhead. In the proposed scheme, each BS acts as an agent and makes decisions locally. It is proved that the optimal sum-rate can be achieved for single-transmit-antenna BSs by using the proposed scheme. Compared to the best method presently known, the proposed scheme achieves a similar sum-rate with considerably lower computational complexity and information overhead, which makes it more appealing for practical implementations.

Coverage and Capacity of Terahertz Cellular Networks With Joint Transmission

Beamforming with high dimensional antenna arrays provides the gain needed to enable high bandwidth communication in the sub-terahertz (THz) band. The resulting narrow beams, however, come at the cost of increased sensitivity to beam alignment errors. A potential remedy to this problem is to introduce a form a macrodiversity through non-coherent joint transmission (NC-JT). We employ a stochastic geometry framework to analyze the performance of a THz network employing user-centric base station clustering and NC-JT. We derive semi-closed form lower bounds for the coverage probability and ergodic capacity experienced by a typical user in the network. Our model includes THz networks without joint transmission as a special case. Overall, our analysis indicates that joint transmission from a few base stations improves coverage and capacity by mitigating the impact of beam misalignment. Moreover, in certain settings, NC-JT is a more efficient usage a network access points compared to the non-cooperative case, and reduces the sensitivity of coverage and capacity to the choice of user beamwidth.

Layer-1 Mobility in Distributed MIMO with Non-Coherent Joint Transmission

Layer-1 Mobility in Distributed MIMO with Non-Coherent Joint Transmission

Distributed fronthaul-constrained joint transmission design and selection using augmented consensus-based dual decomposition

User-centric coordinated multipoint (CoMP) joint transmission (JT) is a novel technique to manage interference and enhance system performance with single frequency reuse, where user equipment (UE) communicates with their closest transmission points (TPs). Unfortunately, in coherent JT, requirement of strict network synchronization accuracy makes it difficult and expensive to be practically deployed. The noncoherent JT has therefore received growing attention since it requires less strict network synchronization accuracy compared to its coherent counterpart as it does not require the signal to be phase-aligned at the receiver. Moreover, cell-free massive MIMO, which is regarded as combining CoMP with massive MIMO systems, has recently been touted as a solution for avoiding intercell interference and provide uniform coverage over a large area. However, the operational costs of CoMP, such as the associated control signaling and communication overhead and the increase of network complexity, could prevent the practical implementation of CoMP. A distributed joint transmission CoMP (JT-CoMP) scheme is proposed herein that allows distributed design and selection of cooperating transmission nodes. To maximize user capacity, the proposed distributed consensus optimization problem assumes spectrum underlay transmission is used so that the solution can achieve non-orthogonal multiple access (NOMA) for cell-free user centric JT-CoMP systems. The proposed algorithm is different from others in the literature because it solves a design problem that involves a coupling constraint that no existing algorithm can solve. Analytical results based on spectral graph theory are given to prove its convergence and characterize its rate of convergence. The more practical scenario is further considered, where limited fronthaul capacity is also included in the problem. A successive convex approximation (SCA) method is used to solve the resulting nonconvex problem, which is shown to maximize spectral efficiency. Simulation results are provided to show that the performance of both proposed distributed algorithms (that address problem without and with fronthaul constraint) is comparable to its centralized counterpart.

Resource Allocation and Hybrid OMA/NOMA Mode Selection for Non-Coherent Joint Transmission

Supporting non-orthogonal multiple access (NOMA) in non-coherent joint transmission (NCJT) systems is beneficial for improving spectral efficiency (SE), but the interference coordination, user scheduling, and resource allocation problems in this new scenario have not been well studied. In this paper, a NOMA-enabled NCJT system is considered in which the connected users are jointly served by two multi-antenna transmitting-receiving points (TRPs) with non-ideal backhauls. Each user has two independent receiving (RX) chains that can work with orthogonal multiple access (OMA) or NOMA mode. A joint resource allocation and hybrid OMA/NOMA mode selection is proposed to maximize the throughput. The primal non-convex and NP-hard problem is decomposed into the following three subproblems, i.e., power allocation (PA) of a single TRP, hybrid mode selection (HMS) of a single TRP, and cross-TRP interference optimization (CIO). Firstly, a successive convex approximation (SCA) method is proposed to solve the non-convex PA subproblem, which achieves a local maximum solution. Secondly, the combinatorial HMS subproblem is transformed into finding the maximum matching of bipartite graphs. By constructing two weighted bipartite graphs for the OMA/near UEs and far UEs, a suboptimal solution is found. Thirdly, an alternating optimization is proposed to solve the CIO subproblem by iteratively performing PA and HMS of the two TRPs. Finally, simulation results demonstrate the superiority of throughput improvement of the proposed method, and the sum rate of the NOMA-enabled NCJT system can approach the sum rate of individual TRPs without interference.

On the Analysis of a Cellular Network With Macro-Diversity Using Stochastic Geometry

The use of macro-diversity, where each user maintains a communication link with more than one base station (BS), can help increase the signal-to-interference-plus-noise ratio (SINR) of the users. In this letter, we consider a cellular network consisting of multiple BSs and users with second-order macro-diversity, in particular, with non-coherent joint transmission (NCJT). We develop a stochastic geometry (SG) based analytical framework to derive the SINR coverage of a typical user. We then evaluate the user load on each BS and derive the rate coverage of the user. We validate our analysis via numerical results and present important design insights. We show that the macro-diversity is only beneficial when the user load on each BS is not very high.

Optimal Massive-MIMO-Aided Clustered Base-Station Coordination

A large-scale clustered massive MIMO network is proposed for improving the spectral efficiency of the next-generation wireless infrastructure by maximizing its sum-rate. Our solution combines the advantages of the centralized processing architecture and massive MIMO. Explicitly, the network is divided into multiple clusters; each cluster is handled by a centralized processing unit, which connects to a certain number of massive MIMO-aided BSs, where only limited information is exchanged among the clusters; each user of a cluster can be served by several nearby BSs in a user-centric way. We analyze the maximum sum-rate of the network with multiple antennas at BSs and UEs, relying on the optimal transmit precoder matrix of each BS configured for each user, and on the optimal frequency-domain power sharing scheme of each cluster. The optimizations are conceived for multiple coordination schemes that were widely studied in literature, namely the coherent-joint-transmission (CJT) scheme, the non-coherent-joint-transmission (NCJT) scheme and the coordinated-beamfoming/scheduling (CBF/CS) scheme. Our simulations show that the optimal CJT achieves 2.2 – 4.5 times higher average sum-rate than its non-cooperative massive MIMO network counterpart, while the optimal NCJT and the optimal CBF/CS achieve at most a factor 1.3 average sum-rate gain. The popular signal-to-leakage-and-noise-ratio (SLNR) scheme is also extended to the multi-antenna UE scenario and achieves a factor 1.1 – 1.2 gain.

Noncoherent Joint Transmission Beamforming for Dense Small Cell Networks: Global Optimality, Efficient Solution and Distributed Implementation

We investigate the coordinated multi-point noncoherent joint transmission (JT) in dense small cell networks. The goal is to design beamforming vectors for macro cell and small cell base stations (BSs) such that the weighted sum rate of the system is maximized, subject to a total transmit power at individual BSs. The optimization problem is inherently nonconvex and intractable, making it difficult to explore the full potential performance of the scheme. To this end, we first propose an algorithm to find a globally optimal solution based on the generic monotonic branch reduce and bound optimization framework. Then, for a more computationally efficient method, we adopt the inner approximation (InAp) technique to efficiently derive a locally optimal solution, which is numerically shown to achieve near-optimal performance. In addition, for decentralized networks such as those comprising of multi-access edge computing servers, we develop an algorithm based on the alternating direction method of multipliers, which distributively implements the InAp-based solution. Our main conclusion is that the noncoherent JT is a promising transmission scheme for dense small cell networks, since it can exploit the densitification gain, outperforms the coordinated beamforming, and is amenable to distributed implementation.

Downlink Power Optimization for Cell-Free Massive MIMO Over Spatially Correlated Rayleigh Fading Channels

Cell-free massive multiple-input multiple-output (mMIMO) is regarded as a promising technology in the future wireless communication. This paper aims to minimize the downlink power consumption of cell-free mMIMO system under the downlink rate constraints of users and the power constraints of per-antenna over spatially correlated Rayleigh fading channels. Firstly, this paper studies the performance of two different downlink transmission modes: non-coherent joint transmission and coherent joint transmission. Then, for the two transmission modes, the corresponding downlink power optimization model is established and an efficient power optimization algorithm is proposed based on the Lagrange multiplier (LM) method. Under the power optimization model, this paper analyzes the impact of different factors on the downlink power consumption of cell-free mMIMO system. Simulation results show that coherent joint transmission performs better than non-coherent joint transmission on spectral efficiency (SE) and energy efficiency (EE). In addition, under the same power control strategy, the downlink power consumption of cell-free mMIMO is much lower than co-located mMIMO. Moreover, the total transmission power decreases when more antennas are utilized at each access point (AP) or spatial correlation of channels becomes weak.

A Location-Dependent Base Station Cooperation Scheme for Cellular Networks

The link quality in cellular networks strongly depends on the location of the users relative to the serving and interfering base stations (BSs). This paper proposes a location-dependent BS cooperation scheme for general cellular networks, where BSs are modeled using a stationary point process and the Voronoi diagram forms the cell structure. The cooperation scheme is based on the relative average received signal strength from the three strongest BSs. For the channel model where Rayleigh fading and power-law path loss are considered, each cell is partitioned into three regions based on the relative distance to the three nearest BSs: the cell center region, cell edge region, and cell corner region. The area fraction of each region is tuned by the so-called cooperation level $\gamma \in [ {0},{1}]$ . We study the scheme where users in the above regions receive the non-coherent joint transmission from one, two, and three nearest BSs, respectively. As such, the scheme primarily helps users vulnerable to interference. We analyze the signal-to-interference ratio (SIR) in Poisson networks and show that a moderate $\gamma $ jointly improves the average SIR performance and the network fairness.

Optimizing Cluster Size Through Handoff Analysis in User-Centric Cooperative Wireless Networks

User-centric base station (BS) cooperation has been regarded as an effective solution for improving network coverage and throughput in next-generation wireless systems. However, it also introduces more complicated handoff patterns, which may potentially degrade user performance. In this paper, we aim to theoretically quantify the tradeoff between handoff cost and data rate. Two user-centric clustering modes are investigated: number-based cooperation (NBC), which is easier to implement, and distance-based cooperation (DBC), which gives higher data rate performance. In the NBC mode, a user is served by its $K$ closest BSs, while in the DBC mode, it is served by all BSs within a given distance. However, due to the randomness of network topology, it is a challenging task to track handoffs and to characterize data rates. To address this issue, we propose a stochastic geometric analysis framework on user mobility, to derive a theoretical expression for the handoff rate experienced by an active user with arbitrary movement trajectory. Then, we characterize the average downlink user data rate under a common non-coherent joint-transmission scheme, which is used to illustrate the tradeoff between handoff rate and data rate in optimizing the cooperative cluster size. We conclude that in the NBC (resp. DBC) mode, the optimal cluster size is asymptotically inversely (resp. inversely) proportional to the square of the user speed and asymptotically inversely (resp. inversely) proportional to the BS intensity. Finally, computer simulation is conducted to validate the correctness and usefulness of our analysis.

No blind spot: network coverage enhancement through joint cooperation and frequency reuse

Both coordinated multi-point transmission and frequency reuse are effective approaches to mitigate inter-cell interference and improve network coverage. The motivation of this work is to explore the manner to effectively utilize the spectrum resource by reasonably combining cooperation and frequency reuse. The Matern cluster process, which is appropriate to model networks with hot spots, is used to model the spatial distribution of base stations. Two cooperative mechanisms, coherent and non-coherent joint transmission (JT), are analyzed and compared. We also evaluate the effect of multiple antennas and imperfect channel state information. The simulation reveals that the proposed approach to combine cooperation and frequency reuse is effective to improve the network coverage for users located at both the center and the boundary of the cooperative region.

D2D Enhanced Co-Ordinated Multipoint in Cloud Radio Access Networks

Coordinated multipoint (CoMP) is an efficient technique to increase cell-edge coverage probability and throughput in cloud radio access network (C-RAN). In this paper, we integrate device-to-device (D2D) communications with CoMP by applying a distance based mode selection rule for downlink users in C-RAN, exploiting the proximity of D2D communications to improve system spectral efficiency. Using stochastic geometry, we first derive the signal-to-interference ratio distribution at a typical downlink user and a typical D2D receiver when two types of CoMP schemes, namely, zero-forcing beamforming (ZFBF) and noncoherent joint transmission (NC-JT), are applied in C-RAN. In addition, we analytically compare ZFBF and NC-JT using rate coverage probability. Meanwhile, we analyze the effect of D2D communications on enhancing the area spectral efficiency (ASE) of CoMP enabled C-RAN system. Numerical results show that increasing the co-operative cluster size would potentially degrade the system ASE when the network is heavily loaded. Furthermore, it is observed that enabling D2D mode in C-RAN can effectively offload the traffic of C-RAN and provide significant ASE gains if mode selection threshold is properly designed. Lastly, it is analytically demonstrated that spectrum resources can be better exploited by D2D users if they coexist with ZFBF enabled radio units (RUs) rather than NC-JT enabled RUs.

Joint Power Allocation and User Association Optimization for Massive MIMO Systems

This paper investigates the joint power allocation and user association problem in multi-cell Massive MIMO (multiple-input multiple-output) downlink (DL) systems. The target is to minimize the total transmit power consumption when each user is served by an optimized subset of the base stations (BSs), using non-coherent joint transmission. We first derive a lower bound on the ergodic spectral efficiency (SE), which is applicable for any channel distribution and precoding scheme. Closed-form expressions are obtained for Rayleigh fading channels with either maximum ratio transmission (MRT) or zero forcing (ZF) precoding. From these bounds, we further formulate the DL power minimization problems with fixed SE constraints for the users. These problems are proved to be solvable as linear programs, giving the optimal power allocation and BS-user association with low complexity. Furthermore, we formulate a max-min fairness problem which maximizes the worst SE among the users, and we show that it can be solved as a quasi-linear program. Simulations manifest that the proposed methods provide good SE for the users using less transmit power than in small-scale systems and the optimal user association can effectively balance the load between BSs when needed. Even though our framework allows the joint transmission from multiple BSs, there is an overwhelming probability that only one BS is associated with each user at the optimal solution.

Joint Power Allocation and User Association Optimization for Massive MIMO Systems

This paper investigates the joint power allocation and user association problem in multi-cell Massive MIMO (multiple-input multiple-output) downlink (DL) systems. The target is to minimize the total transmit power consumption when each user is served by an optimized subset of the base stations (BSs), using non-coherent joint transmission. We first derive a lower bound on the ergodic spectral efficiency (SE), which is applicable for any channel distribution and precoding scheme. Closed-form expressions are obtained for Rayleigh fading channels with either maximum ratio transmission (MRT) or zero forcing (ZF) precoding. From these bounds, we further formulate the DL power minimization problems with fixed SE constraints for the users. These problems are proved to be solvable as linear programs, giving the optimal power allocation and BS-user association with low complexity. Furthermore, we formulate a max-min fairness problem that maximizes the worst SE among the users, and we show that it can be solved as a quasi-linear program. Simulations manifest that the proposed methods provide good SE for the users using less transmit power than in small-scale systems and the optimal user association can effectively balance the load between BSs when needed. Even though our framework allows the joint transmission from multiple BSs, there is an overwhelming probability that only one BS is associated with each user at the optimal solution.

Performance Analysis of Finite-Sized Cooperative Systems with Unreliable Backhaul Links

This paper presents a performance analysis of a finite-sized co-operative wireless system, where a group of transmitters with unreliable backhauls serve a desired receiver using noncoherent joint transmission. To facilitate analysis, an analytical expression for the distribution of the spatially averaged signal-to-interference-plus-noise ratio (SA-SINR) is derived in terms of key system and channel parameters. Leveraging the derived expression, the joint impact of node co-operation, backhaul reliability, interference, and communication range is investigated in the considered finite-sized co-operative system. Furthermore, based on the SA-SINR, closed form expressions for the average bit error rate (ABER) and average spectral efficiency (ASE) are derived. Further insights are established by analyzing the asymptotic performance in the high transmission power regime. From analytical derivations for the outage probability, ABER, and ASE and link-level simulations, it is verified that these asymptotic performance metrics are exclusively influenced by unreliable backhauls, so that the conventional diversity gains are not achievable.

Coordinated Multipoint Joint Transmission in Heterogeneous Networks

Motivated by the ongoing discussion on coordinated multipoint in wireless cellular standard bodies, this paper considers the problem of base station cooperation in the downlink of heterogeneous cellular networks. The focus of this paper is the joint transmission scenario, where an ideal backhaul network allows a set of randomly located base stations, possibly belonging to different network tiers, to jointly transmit data, to mitigate intercell interference and hence improve coverage and spectral efficiency. Using tools from stochastic geometry, an integral expression for the network coverage probability is derived in the scenario where the typical user located at an arbitrary location, i.e., the general user, receives data from a pool of base stations that are selected based on their average received power levels. An expression for the coverage probability is also derived for the typical user located at the point equidistant from three base stations, which we refer to as the worst case user. In the special case where cooperation is limited to two base stations, numerical evaluations illustrate absolute gains in coverage probability of up to 17% for the general user and 24% for the worst case user compared with the noncooperative case. It is also shown that no diversity gain is achieved using noncoherent joint transmission, whereas full diversity gain can be achieved at the receiver if the transmitting base stations have channel state information.

A Tractable Model for Noncoherent Joint-Transmission Base Station Cooperation

This paper presents a tractable model for analyzing non-coherent joint transmission base station (BS) cooperation, taking into account the irregular BS deployment typically encountered in practice. Besides cellular-network specific aspects such as BS density, channel fading, average path loss and interference, the model also captures relevant cooperation mechanisms including user-centric BS clustering and channel-dependent cooperation activation. The locations of all BSs are modeled by a Poisson point process. Using tools from stochastic geometry, the signal-to-interference-plus-noise ratio ($\mathtt{SINR}$) distribution with cooperation is precisely characterized in a generality-preserving form. The result is then applied to practical design problems of recent interest. We find that increasing the network-wide BS density improves the $\mathtt{SINR}$, while the gains increase with the path loss exponent. For pilot-based channel estimation, the average spectral efficiency saturates at cluster sizes of around $7$ BSs for typical values, irrespective of backhaul quality. Finally, it is shown that intra-cluster frequency reuse is favorable in moderately loaded cells with generous cooperation activation, while intra-cluster coordinated scheduling may be better in lightly loaded cells with conservative cooperation activation.