Majid Ghanbarinejad

Irregular repetition slotted ALOHA with multiuser detection

Irregular repetition slotted ALOHA is a random access scheme where users transmit multiple copies of a packet to the receiver to provide time-domain diversity; then, the receiver attempts to iteratively decode packets and cancel their interference contribution in other time slots, increasing the chance of resolving collisions and decoding more packets. This scheme was shown to support larger system loads compared to conventional slotted ALOHA. In the original scheme, collision resolution between l colliding packets is possible only when l - 1 of those packets are decoded in prior iterations, which is probable because of the other copies of each packet transmitted in other slots. However, although asymptotic analysis promises high efficiency of this scheme, the analysis relies on the large number of slots participating in the iterative collision resolution, which requires large receiver complexity and introduces delay. In this paper, we study this scheme for receivers capable of decoding multiple colliding packets jointly, which increases the chance of decoding more packets under large system loads. Asymptotic analysis for this generalized model is provided and it is shown by simulations that a multiuser detector supports larger loads for low number of slots jointly processed.

Adaptive Probabilistic Medium Access in MPR-Capable Ad-Hoc Wireless Networks

Medium access in ad-hoc wireless networks must be performed in a distributed fashion due to lack of coordination between nodes. Specifically, when nodes are capable of receiving more than one transmission simultaneously, the design of distributed medium-access mechanisms that efficiently exploit the receivers capability becomes more challenging. Adaptive probabilistic medium access for ad-hoc wireless networks is proposed in this paper. Nodes with data packets to transmit perform an announcement process in order to inform other nodes of their intended traffic. The acquired information through this process about other potential transmitters in the vicinity is then used by the nodes to choose a transmission probability with which they transmit their data packets. The performance of a multi-packet reception capable ad-hoc wireless network under the proposed protocol is analyzed and evaluated numerically and via simulations, and compared with Aloha-type random access.

Distributed probabilistic medium access with multipacket reception and Markovian traffic

Enabling multipacket reception (MPR) at the physical layer is a promising way to achieve higher bandwidth efficiency while reducing the complexity of the medium access control layer in distributed wireless networks. We study distributed probabilistic access where transmitting nodes access the shared wireless medium with a probability based on the node’s information about the aggregate traffic carried by the network. We model bursty traffic by rate-controlled two-state Markov sources and introduce a parameter that describes the “burstiness” level of the offered traffic. A throughput-optimal medium access strategy utilizing limited feedback is then described and its performance is examined for traffic with different levels of burstiness. It is shown that the bursty nature of the traffic in data networks allows for improvement of the bandwidth efficiency. Bounds on the system throughput are proposed and the queuing delay is analyzed.

Analysis of Controlled Probabilistic Access with Multipacket Reception

Multipacket reception (MPR) capability provides the opportunity to improve bandwidth utilization while reducing complexity of the medium access control layer. Specifically, it has been shown that ALOHA random access tends to become asymptotically optimal as the receivers joint decoding capability of the receiver grows to infinity. However, the average traffic offered to the medium is required to remain below a threshold in order for the MPR capability to be utilized efficiently. The effect of controlling the access probability according to the instantaneous offered traffic is studied in this paper. It is shown that, as the average rate of the offered traffic exceeds the optimal value, a dynamic control strategy can increase the maximum expected throughput of probabilistic access dramatically compared to uncontrolled ALOHA. The average throughput achieved by this strategy is analyzed and a lower bound on the system throughput of genie-aided probabilistic access is derived. Finally, the effect of uncertainty about the offered traffic is addressed and an approximation for the resulting performance loss is presented.

Controlled random access with multipacket reception and traffic uncertainty

The problem of optimizing the medium access probability in a multipacket-reception-capable network, when only inaccurate estimates of the offered traffic are known, is addressed. It is shown that a larger uncertainty in the traffic estimates must be compensated by a more conservative access policy. The analysis is verified by examples and simulation results.

Additive-Increase Multiplicative-Decrease MAC Protocol with Multi-Packet Reception

A distributed medium-access control (MAC) protocol for the time-slotted channel with multi-packet reception (MPR) capability is proposed. In contrast to the commonly assumed collision channel, in the MPR channel with channel capacity K, it is possible to decode up to K packets whose transmissions overlap in time. In order to exploit the MPR capability, the additive-increase multiplicative-decrease MAC (AIMD-MAC) protocol is designed to adaptively adjust the access probabilities of the independent nodes based on their local transmission histories. The examined performance metrics for evaluating this protocol include aggregate throughput, average packet delay and system fairness. Extensive simulations show that the performance of AIMD-MAC is superior to that of S-Aloha* under light traffic loads and achieves the optimum level after the system is saturated. With a suitable parameter set, AIMD-MAC can be adequately applied in a dynamic wireless environment.

Random access with multipacket reception and adaptive filtering

A probabilistic medium-access control (MAC) protocol is proposed for an uncoordinated network of nodes with multipacket reception (MPR) capability at the receiver. The protocol uses binary feedback at the end of each time slot and uses an extended Kalman filter (EKF) to compute an estimate of the number of currently active nodes in the service area. The estimate is then used to optimize the expected system throughput by adjusting the medium access probability of each node. Simulations show that the proposed MAC protocol succeeds in tracking the number of nodes and achieving near-optimal throughput performance.

Wi-Fi-Based mmWave Backhaul - Part 1: Feasibility

The growing demands for wireless access continue to drive research on wireless systems in order to meet requirements for higher rates, lower latencies, and denser deployments. As a result, small-cell-based densification is expected to play a key role for satisfying quality-of-service demands for future wireless networks. Since operators desire to expand coverage and services in accordance with the growing demands, wireless backhaul solutions for small cells are increasingly appealing from the viewpoint of the deployment and service expansion costs. Particularly, millimeter-wave backhaul solutions are being considered as an important element in realizing small-cell deployments. In this paper, we will study the feasibility and performance of a Wi-Fi-based millimeter-wave backhaul. Such a solution will have several advantages including the elimination of spectrum costs and the possibility of multiple-vendor solutions due to compatibility with a worldwide standard.

On throughput-delay tradeoff of random access over satellite links

Throughput-delay tradeoff of random access over satellite links is analyzed and scaling laws are derived for the cases of the collision channel and the multipacket reception (MPR) channel as well as repetition random access. It is shown that multiuser detection and repetition schemes improve the multiple access performance in the sense that the inevitable compromise between throughput and delay is mitigated by joint detection capabilities and/or repetitions.

Linear Unbiased Channel Estimation and Data Detection in Superimposed OFDM Systems

Reliable channel estimation is necessary for orthogonal frequency-division multiplexing (OFDM) systems employing coherent detection to achieve high data rates. Pilot-aided detection algorithms benefit from rapid convergence, but suffer from non-efficient bandwidth usage. The idea of superimposed data transmission can be enabled for channel estimation without sacrificing the data rate. In this paper, we first derive the best linear unbiased estimator (BLUE) for channel impulse response and then, we propose an iterative joint channel estimator and data detector to improve the performance of both the estimator and the detector. Furthermore, we derive the variance of the proposed estimator and show that the equispace and equipower conditions hold for the superimposed pilots to attain the minimum variance of the estimator. Simulations show that the performance with perfect knowledge of the channel impulse response can be achieved closely by the proposed iterative data detector.