In this work, we investigate the stability region, the throughput performance, and the queueing delay of an asymmetric relay-assisted cooperative random access wireless network with multipacket reception (MPR) capabilities. We consider a network of @math saturated source users that transmit packets to a common destination node with the cooperation of two relay nodes. The relays are equipped with infinite capacity buffers, and assist the users by forwarding the packets that failed to reach the destination. Moreover, the relays have also packets of their own to transmit to the destination. We assume random access of the medium and slotted time. With the relay-assisted cooperation, the packets originated by each user can be transmitted to the destination through multiple relaying paths formed by the relays. We assume that the relays employ an adaptive retransmission control mechanism. In particular, a relay node is aware of the status of the other relay, and accordingly adapts its transmission probability. Such a protocol is towards self-aware networks and leads to substantial performance gains in terms of delay. We investigate the stability region and the throughput performance for the full MPR model. Moreover, for the two-user, two-relay case we derive the generating function of the stationary joint queue-length distribution at the relays by solving a Riemann-Hilbert boundary value problem. Finally, for the symmetric case we obtain explicit expressions for the average queueing delay in a relay node without the need of solving a boundary value problem. Numerical examples are presented providing insights on the system performance.
In addition, random access recently re-gained interest due to the increased number of communicating devices in 5G networks, and the need for massive uncoordinated access @cite_28 . Random access and alternatives schemes and their effect on the operation of LTE and LTE-A are presented in @cite_28 , @cite_13 , @cite_23 . In @cite_15 , the effect of random access in Cloud-Radio Access Network is considered.
@cite_28 @cite_15 @cite_13 @cite_23
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The random access methods used for support of machine-type communications (MTC) in current cellular standards are derivatives of traditional framed slotted ALOHA and therefore do not support high user loads efficiently. Motivated by the random access method employed in LTE, we propose a novel approach that is able to sustain a wide random access load range, while preserving the physical layer unchanged and incurring minor changes in the medium access control layer. The proposed scheme increases the amount of available contention resources, without resorting to the increase of system resources, such as contention sub-frames and preambles. This increase is accomplished by expanding the contention space to the code domain, through the creation of random access codewords. Specifically, in the proposed scheme, users perform random access by transmitting one or none of the available LTE orthogonal preambles in multiple random access sub-frames, thus creating access codewords that are used for contention. In this way, for the same number of random access sub-frames and orthogonal preambles, the amount of available contention resources is drastically increased, enabling the support of an increased number of MTC users. We present the framework and analysis of the proposed code-expanded random access method and show that our approach supports load regions that are beyond the reach of current systems. Future 5G cellular networks supporting delay-sensitive, low-latency communications could employ random access communication to reduce the overhead compared to scheduled access techniques used in 4G networks. We consider a wireless communication system where multiple devices transmit payloads of a given fixed size in a random access fashion over shared radio resources to a common receiver. We allow retransmissions and assume Chase combining at the receiver. The radio resources are partitioned in the time and frequency dimensions, and we determine the optimal partition granularity to maximize throughput, subject to given constraints on latency and outage. In the regime of high and low signal-to-noise ratio (SNR), we derive explicit expressions for the granularity and throughput, first using a Shannon capacity approximation and then using finite block length analysis. Numerical results show that the throughput scaling results are applicable over a range of SNRs. The proposed analytical framework can provide insights for resource allocation strategies in reliable and delay-sensitive random access systems and in specific 5G use cases for massive, short packet uplink access. The 3GPP has raised the need to revisit the design of next generations of cellular networks in order to make them capable and efficient to provide M2M services. One of the key challenges that has been identified is the need to enhance the operation of the random access channel of LTE and LTE-A. The current mechanism to request access to the system is known to suffer from congestion and overloading in the presence of a huge number of devices. For this reason, different research groups around the globe are working towards the design of more efficient ways of managing the access to these networks in such circumstances. This paper aims to provide a survey of the alternatives that have been proposed over the last years to improve the operation of the random access channel of LTE and LTE-A. A comprehensive discussion of the different alternatives is provided, identifying strengths and weaknesses of each one of them, while drawing future trends to steer the efforts over the same shooting line. In addition, while existing literature has been focused on the performance in terms of delay, the energy efficiency of the access mechanism of LTE will play a key role in the deployment of M2M networks. For this reason, a comprehensive performance evaluation of the energy efficiency of the random access mechanism of LTE is provided in this paper. The aim of this computer-based simulation study is to set a baseline performance upon which new and more energy-efficient mechanisms can be designed in the near future. In multihop packet radio networks with randomly distributed terminals, the optimal transmission radii to maximize the expected progress of packets in desired directions are determined with a variety of transmission protocols and network configurations. It is shown that the FM capture phenomenon with slotted ALOHA greatly improves the expected progress over the system without capture due to the more limited area of possibly interfering terminals around the receiver. The (mini)slotted nonpersistent carrier-sense-multiple-access (CSMA) only slightly outperforms ALOHA, unlike the single-hop case (where a large improvement is available), because of a large area of "hidden" terminals and the long vulnerable period generated by them. As an example of an inhomogeneous terminal distribution, the effect of a gap in an otherwise randomly distributed terminal population on the expected progress of packets crossing the gap is considered. In this case, the disadvantage of using a large transmission radius is demonstrated. For wireless systems in which randomly arriving devices attempt to transmit a fixed payload to a central receiver, we develop a framework to characterize the system throughput as a function of arrival rate and per-device data rate. The frame- work considers both coordinated transmission (where devices are scheduled) and uncoordinated transmission (where devices com- municate on a random access channel and a provision is made for retransmissions). Our main contribution is a novel character- ization of the optimal throughput for the case of uncoordinated transmission and a strategy for achieving this throughput that relies on overlapping transmissions and joint decoding. Simula- tions for a noise-limited cellular network show that the optimal strategy provides a factor of four improvement in throughput compared with slotted ALOHA. We apply our framework to eval- uate more general system-level designs that account for overhead signaling. We demonstrate that, for small payload sizes relevant for machine-to-machine (M2M) communications (200 bits or less), a one-stage strategy, where identity and data are transmitted opti- mally over the random access channel, can support at least twice the number of devices compared with a conventional strategy, where identity is established over an initial random-access stage and data transmission is scheduled. The cloud radio access network (Cloud-RAN) has recently been proposed as one of the cost-effective and energy-efficient techniques for 5G wireless networks. By moving the signal processing functionality to a single baseband unit (BBU) pool, centralized signal processing and resource allocation are enabled in cloud-RAN, thereby providing the promise of improving the energy efficiency via effective network adaptation and interference management. In this paper, we propose a holistic sparse optimization framework to design green cloud-RAN by taking into consideration the power consumption of the fronthaul links, multicast services, as well as user admission control. Specifically, we first identify the sparsity structures in the solutions of both the network power minimization and user admission control problems, which call for adaptive remote radio head (RRH) selection and user admission. However, finding the optimal sparsity structures turns out to be NP-hard, with the coupled challenges of the @math -norm-based objective functions and the nonconvex quadratic QoS constraints due to multicast beamforming. In contrast to the previous works on convex but nonsmooth sparsity inducing approaches, e.g., the group sparse beamforming algorithm based on the mixed @math -norm relaxation, we adopt the nonconvex but smoothed @math -minimization ( @math @math $ -minimization problem from the SDR technique. We illustrate the effectiveness of the proposed algorithms with extensive simulations for network power minimization and user admission control in multicast cloud-RAN. Next generation cellular networks are envisioned to widely enable machine-to-machine (M2M) communication. For many applications in the M2M domain, deterministic communication latencies and high reliability are of very high importance. As a consequence, device-to-device (D2D) communication is a expected to play a key role in order to avoid from having to route the entire data through a centralized base station. Considering the large number of devices but relatively small payload lengths of many M2M applications, LTE currently fails to efficiently utilize the available radio resources. This is primarily because the granularity of resources that can be allocated to a single user is too coarse, resulting in parts of the allocation being wasted. In this paper, we present a hierarchical radio resource management scheme that allows ordinary cellular users to reuse and exploit the otherwise unused portion of a D2D scheduling grant. We show that our resource reuse scheme improves the uplink throughput of cellular users between 10 and 30 , depending on the actual number of D2D users, compared to current allocation schemes. Future machine-to-machine (M2M) communications need to support a massive number of devices communicating with each other with little or no human intervention. Random access techniques were originally proposed to enable M2M multiple access, but suffer from severe congestion and access delay in an M2M system with a large number of devices. In this paper, we propose a novel multiple access scheme for M2M communications based on the capacity-approaching analog fountain code to efficiently minimize the access delay and satisfy the delay requirement for each device. This is achieved by allowing M2M devices to transmit at the same time on the same channel in an optimal probabilistic manner based on their individual delay requirements. Simulation results show that the proposed scheme achieves a near optimal rate performance and at the same time guarantees the delay requirements of the devices. We further propose a simple random access strategy and characterize the required overhead. Simulation results show that the proposed approach significantly outperforms the existing random access schemes currently used in long term evolution advanced (LTE-A) standard in terms of the access delay. This paper investigates multiple access techniques for wireless downlink in cloud radio access networks (CRANs) where all base stations (BSs) are connected via a cloud. We first propose a power allocation scheme that makes use of non-orthogonal multiple access to allocate the power at the BSs based on their relative wireless distances to the cloud. Specifically, a successive interference cancellation mechanism is designed at the cloud to lay multiple BSs over each other in the power domain. We then analyse the achievable throughput of the NOMA in the CRANs. The derived expressions not only show the effectiveness of the proposed NOMA over the conventional orthogonal frequency division multiple access (OFDMA) but also allow us to develop an algorithm to find the optimal number of BSs in the CRANs. Finally, numerical results are provided to show an improvement of up to eight times of the sum data rate and a higher number of BSs that could be maintained with the proposed NOMA over the OFDMA scheme as well as evaluating the impact of the wireless propagation environment and channel quality on the system throughput and cloud-edge throughput performance. Here we continue the analytic study of packet switching in radio channels which we reported upon m our two previous papers [1], [2] Again we consider a population of terminals communicating with a central station over a packet-switched radio channel. The allocation of bandwidth among the contending terminals can be fixed [e.g., time-division multiple access (TDMA) or frequency-division multiple access (FDMA)], random [e.g., ALOHA or carrier sense multiple access (CSMA)] or centrally controlled (e.g., polling or reservation). In this paper we show that with a large population of bursty users, (as expected) random access is superior to both fixed assignment and polling. We also introduce and analyze a dynamic reservation technique which we call split-channel reservation multiple access (SRMA) which is interesting in that it is both simple and efficient over a large range of system parameters. The implementation of a cloud radio access network (C-RAN) with full dimensional (FD) multiple-input multiple-output (MIMO) is faced with the challenge of controlling the fronthaul overhead for the transmission of baseband signals as the number of horizontal and vertical antennas grows larger. This paper proposes to leverage the special low-rank structure of the FD-MIMO channel, which is characterized by a time-invariant elevation component and a time-varying azimuth component, by means of a layered precoding approach, to reduce the fronthaul overhead. According to this scheme, separate precoding matrices are applied for the azimuth and elevation channel components, with different rates of adaptation to the channel variations and correspondingly different impacts on the fronthaul capacity. Moreover, we consider two different central unit (CU)-radio unit (RU) functional splits at the physical layer, namely, the conventional C-RAN implementation and an alternative one in which coding and precoding are performed at the RUs. Via numerical results, it is shown that the layered schemes significantly outperform conventional nonlayered schemes, particularly in the regime of low fronthaul capacity and a large number of vertical antennas. Future wireless access points may have to support sporadic transmissions from a massive number of unattended machines. Recently, there has been a lot of interest in the design of massive uncoordinated multiple access schemes for such systems based on clever enhancements to slotted ALOHA. A close connection has been established between the design of the multiple access scheme and the design of low density generator matrix codes. Based on this connection, optimal multiple access schemes have been designed based on slotted ALOHA and successive interference cancellation, assuming that the number of users in the network is known at the transmitters. In this paper, we extend this work and consider the design of universal uncoordinated multiple access schemes that are agnostic to the number of users in the network. We design Markov chain based transmission policies and numerical results show that substantial improvement to slotted ALOHA is possible. Rapid growth of machine-to-machine (M2M) communications necessitates the reevaluation of the Long Term Evolution-Advanced (LTE-A) performance, since the current standard is not optimized for intensive M2M traffic. A serious issue is that massive M2M arrivals can overload the LTE-A random access channel, resulting in a significant access delay. There have been a number of proposals to control this overload; however, there are no studies on the mathematical characterization of delay bounds to the best of our knowledge. Here, we derive lower bounds for the LTE-A average random access delay for both a regular traffic pattern (uniformly distributed arrivals) and for a traffic pattern, indicating a serious congestion (beta-distributed arrivals). The proposed delay bounds, which predict the minimum delay with less than 6 error, present the fundamental limits of delay that can be achieved by a practical load-balancing algorithm. This paper is also one of the first attempts toward the mathematical analysis of beta-distributed arrivals. We also analyze the effect of estimation accuracy, frequency of random access opportunities, and the number of preambles on the access delay. We show that it is possible to reduce the access delay by several orders of magnitude using an appropriate configuration of these system parameters. It is a great challenge to evaluate the network performance of cellular mobile communication systems. In this paper, we propose new spatial spectrum and energy efficiency models for Poisson-Voronoi tessellation (PVT) random cellular networks. To evaluate the user access to the network, a Markov chain based wireless channel access model is first proposed for PVT random cellular networks. On that basis, the outage probability and blocking probability of PVT random cellular networks are derived, which can be computed numerically. Furthermore, taking into account the call arrival rate, the path loss exponent and the base station (BS) density in random cellular networks, spatial spectrum and energy efficiency models are proposed and analyzed for PVT random cellular networks. Numerical simulations are conducted to evaluate the network spectrum and energy efficiency in PVT random cellular networks. In this paper the possibility of device-to-device (D2D) communications as an underlay of an LTE-A network is introduced. The D2D communication enables new service opportunities and reduces the eNB load for short range data intensive peer-to-peer communication. The cellular network may establish a new type of radio bearer dedicated for D2D communications and stay in control of the session setup and the radio resources without routing the user plane traffic. The paper addresses critical issues and functional blocks to enable D2D communication as an add-on functionality to the LTE SAE architecture. Unlike 3G spread spectrum cellular and OFDM WLAN techniques, LTE-A resource management is fast and operates in high time-frequency resolution. This could allow the use of non-allocated time-frequency resources, or even partial reuse of the allocated resources for D2D with eNB controlled power constraints. The feasibility and the range of D2D communication, and its impact to the power margins of cellular communications are studied by simulations in two example scenarios. The results demonstrate that by tolerating a modest increase in interference, D2D communication with practical range becomes feasible. By tolerating higher interference power the D2D range will increase. In this paper, we focus on the deployment of LTE technologies coexisting with Wi-Fi technologies in the unlicensed spectrum 5 GHz. Listen before talk (LBT) functionality is required in unlicensed band in order to ensure the fair coexistence among different operators. We propose a LBT enhancement algorithm with contention window size adaptation for LTE with Licensed-Assisted Access (LTE-LAA) in order to achieve not only channel access fairness but also the QoS fairness. Simulation results show that LTE-LAA with LBT mechanism does not impact Wi-Fi services more than an additional Wi-Fi network. Compared with the fixed LBT mechanism, our proposed LBT algorithm could achieve around 4 and 6 LTE-LAA performance gain in user perceived throughput (UPT) and transmission latency, respectively. And, more than 25 Wi-Fi transmission latency gain can be also achieved. Furthermore, the simulation result shows the advantage of proposed LBT algorithm over original LBT procedure in the case of two LTE operators coexistence. The performance of cloud radio access network (C-RAN) is constrained by the limited fronthaul link capacity under future heavy data traffic. To tackle this problem, extensive efforts have been devoted to design efficient signal quantization compression techniques in the fronthaul to maximize the network throughput. However, most of the previous results are based on information-theoretical quantization methods, which are hard to implement practically due to the high complexity. In this paper, we propose using practical uniform scalar quantization in the uplink communication of an orthogonal frequency division multiple access (OFDMA) based C-RAN system, where the mobile users are assigned with orthogonal sub-carriers for transmission. In particular, we study the joint wireless power control and fronthaul quantization design over the sub-carriers to maximize the system throughput. Efficient algorithms are proposed to solve the joint optimization problem when either information-theoretical or practical fronthaul quantization method is applied. We show that the fronthaul capacity constraints have significant impact to the optimal wireless power control policy. As a result, the joint optimization shows significant performance gain compared with optimizing only wireless power control or fronthaul quantization. Besides, we also show that the proposed simple uniform quantization scheme performs very close to the throughput performance upper bound, and in fact overlaps with the upper bound when the fronthaul capacity is sufficiently large. Overall, our results reveal practically achievable throughput performance of C-RAN for its efficient deployment in the next-generation wireless communication systems. Device-to-device (D2D) communication as an underlaying cellular network empowers user-driven rich multimedia applications and also has proven to be network efficient offloading eNodeB traffic. However, D2D transmitters may cause significant amount of interference to the primary cellular network when radio resources are shared between them. During the downlink (DL) phase, primary cell UE (user equipment) may suffer from interference by the D2D transmitter. On the other hand, the immobile eNodeB is the victim of interference by the D2D transmitter during the uplink (UL) phase when radio resources are allocated randomly. Such interference can be avoided otherwise diminish if radio resource allocated intelligently with the coordination from the eNodeB. In this paper, we formulate the problem of radio resource allocation to the D2D communications as a mixed integer nonlinear programming (MINLP). Such an optimization problem is notoriously hard to solve within fast scheduling period of the Long Term Evolution (LTE) network. We therefore propose an alternative greedy heuristic algorithm that can lessen interference to the primary cellular network utilizing channel gain information. We also perform extensive simulation to prove the efficacy of the proposed algorithm. We introduce a channel-opportunistic architecture that enhances the user experience in terms of throughput, fairness, and energy efficiency. Our proposed architecture leverages D2D communication and it is built on top of the forthcoming D2D features of 5G networks. In particular, we focus on outband D2D where cellular users are allowed to exploit both cellular (i.e., LTE-A) and WLAN (i.e., WiFi Direct) technologies to establish a D2D connection. In this architecture, cellular users form clusters, in which only the user with the best channel condition communicates with the base station on behalf of the entire cluster. Within the cluster, the unlicensed spectrum is utilized to relay traffic. In this article, we provide analytical models for the proposed system and study the impact of several payoff distribution methods commonly adopted in the literature on coalitional game theory. We then introduce an operator-controlled relay protocol based on the D2D features of LTE-A and WiFi Direct, and demonstrate the feasibility and the advantages of D2D-assisted cellular communication with our SDR prototype. The rise of machine-to-machine communications has rekindled interest in random access protocols as a support for a massive number of uncoordinatedly transmitting devices. The legacy ALOHA approach is developed under a collision model, where slots containing collided packets are considered as waste. However, if the common receiver (e.g. base station) is able to store the collision slots and use them in a transmission recovery process based on successive interference cancellation, the design space for access protocols is radically expanded. We present the paradigm of coded random access, in which the structure of the access protocol can be mapped to a structure of an erasure-correcting code defined on a graph. This opens the possibility to use coding theory and tools for designing efficient random access protocols, offering markedly better performance than ALOHA. Several instances of coded random access protocols are described, as well as a case study on how to upgrade a legacy ALOHA system using the ideas of coded random access.