Yingqun Yu

High-Throughput Random Access Using Successive Interference Cancellation in a Tree Algorithm

Random access is well motivated and has been widely applied when the network traffic is bursty and the expected throughput is not high. The main reason behind relatively low-throughput expectations is that collided packets are typically discarded. In this paper, we develop a novel protocol exploiting successive interference cancellation (SIC) in a tree algorithm (TA), where collided packets are reserved for reuse. Our SICTA protocol can achieve markedly higher maximum stable throughput relative to existing alternatives. Throughput performance is analyzed for general d-ary SICTA with both gated and window access. It is shown that the throughput for d-ary SICTA with gated access is about (ln d)/(d - 1), and can reach 0.693 for d = 2. This represents a 40% increase over the renowned first-come-first-serve (FCFS) 0.487 tree algorithm. Delay performance is also analyzed for SICTA with gated access, and numerical results are provided.

SICTA: a 0.693 contention tree algorithm using successive interference cancellation

Contention tree algorithms have provable stability properties, and are known to achieve stable throughput as high as 0.487 for the infinite population Poisson model. A common feature in all these random access protocols is that collided packets at the receive-node are always discarded. In this paper, we derive a novel tree algorithm (TA) that we naturally term SICTA because it relies on successive interference cancellation to resolve collided packets. Performance metrics including throughput and delay are analyzed to establish that SICTA outperforms existing contention tree algorithms reaching 0.693 in stable throughput.

Cross-layer congestion and contention control for wireless ad hoc networks

We consider joint congestion and contention control for multihop wireless ad hoc networks, where the goal is to find optimal end-to-end source rates at the transport layer and per-link persistence probabilities at the medium access control (MAC) layer to maximize the aggregate source utility. The primal formulation of this problem is non-convex and non-separable. Under certain conditions, by applying appropriate transformations and introducing new variables, we obtain a decoupled and dual-decomposable convex formulation. For general non-logarithmic concave utilities, we develop a novel dual-based distributed algorithm using the subgradient method. In this algorithm, sources at the transport layer adjust their log rates to maximize their net benefits, while links at the MAC layer select transmission probabilities proportional to their conceived contribution to the system reward. The two layers are connected and coordinated by link prices. Our solutions enjoy the benefits of cross-layer optimization while maintaining the simplicity and modularity of the traditional layered architecture.

Opportunistic medium access for wireless networking adapted to decentralized CSI

Relative to a centralized operation, opportunistic medium access capitalizing on decentralized multiuser diversity in a channel-aware homogeneous slotted Aloha system with analog-amplitude channels has been shown to incur only partial loss in throughput due to contention. In this context, we provide sufficient conditions for stability as well as upper bounds on average queue sizes, and address three equally important questions. The first one is whether there exist decentralized scheduling algorithms for homogeneous users with higher throughputs than available ones. We prove that binary scheduling maximizes the sum-throughput. The second issue pertains to heterogeneous systems where users may have different channel statistics. Here we establish that binary scheduling not only maximizes the sum of the logs of the average throughputs, but also asymptotically guarantees fairness among users. The last issue we address is extending the results to finite state Markov chain (FSMC) channels. We provide a convex formulation of the corresponding throughput optimization problem, and derive a simple binary-like access strategy

Channel-Adaptive Optimal OFDMA Scheduling

Joint subcarrier, power and rate allocation in orthogonal frequency division multiple access (OFDMA) scheduling is investigated for both downlink and uplink wireless transmissions. Using a time-sharing argument, a convex formulation is obtained avoiding the NP-hardness of the usual 0-1 integer program solution. It is rigourously established that the optimal allocation can be obtained almost surely through a greedy water-filling approach with linear complexity in the number of users and subcarriers. Stochastic approximation is further employed to develop on-line algorithms which are capable of dynamically learning the underlying channel distribution and asymptotically converges to the off-line optimal solution from arbitrary initial values.

A Robust High-Throughput Tree Algorithm Using Successive Interference Cancellation

A novel random access protocol combining a tree algorithm (TA) with successive interference cancellation (SIC) has been introduced recently. To mitigate the deadlock problem of SICTA arising in error-prone wireless networks, we put forth a SICTA with first success (SICTA/FS) protocol, which is capable of high throughput while requiring limited-sensing and gaining robustness to errors relative to SICTA.

Joint Congestion Control and OFDMA Scheduling for Hybrid Wireline-Wireless Networks

We consider joint congestion control and multiuser scheduling in a hybrid wireline and wireless network, where the air interface of wireless links is based on orthogonal frequency division multiplexing (OFDM). For static channels, we formulate this cross-layer design as a network utility maximization (NUM) problem with both wireline and wireless link constraints. The convexity of the problem enables a well-established dual-based approach to decompose it into two subproblems, the transport layer source rate adaptation and the medium access control (MAC) layer multiuser OFDM scheduling, which are connected and coordinated by link prices. While the rate and link price adjustments follow the same fashion as the conventional utility-based congestion control for wireline networks, the key difference is the multiuser OFDM scheduling performed at the wireless access point (AP). Independent from specific utilities used by each source, this scheduling problem always maximizes a wireless link-price-weighted sum throughput (LPWST), which can be solved efficiently by a block-coordinate descent method, resulting in optimal subcarrier assignment and power allocation at the AP. Convergence of the dual-based algorithm is established using the convex optimization theory. To extend our results to dynamic wireless channels, we provide a NUM formulation with long-term average feasible rate region and develop a gradient scheduling algorithm to handle channel variations. Our work represents a systematic cross-design framework for distributed fair resource allocation in a hybrid network with both static and dynamic wireless channels.

On the instability of slotted aloha with capture

We analyze the stability properties of slotted Aloha with capture for random access over fading channels with infinitely-many users. We assume that each user node knows only its own uplink channel gain, and uses this decentralized channel state information (CSI) to perform power control and/or probability control. The maximum stable throughput (MST) for a general capture model is obtained by means of drift analysis on the backlog Markov chain. We then specialize our general result to a signal-to-interference-plus-noise ratio (SINR) capture model. Our analysis shows that if the channels of all users are identical and independently distributed (i.i.d.) with finite means, the system is unstable under any kind of power and probability control mechanism that is based only on decentralized CSI.

Achieving Wireline Random Access Throughput in Wireless Networking Via User Cooperation

Well appreciated at the physical layer, user cooperation is introduced here as a diversity enabler for wireless random access (RA) at the medium access control sublayer. This is accomplished through a two-phase protocol in which active users start with a low power transmission attempting to reach nearby users and follow up with a high power transmission in cooperation with the users recruited in the first phase. We show that such a cooperative protocol yields a significant increase in throughput. Specifically, we prove that for networks with a large number of users, the throughput of a cooperative wireless RA network operating over Rayleigh-fading links approaches the throughput of an RA network operating over additive white Gaussian noise links-thus justifying the title of the paper. The message borne out of this result is that user cooperation offers a viable choice for migrating diversity benefits to the wireless RA regime, thus bridging the gap to wireline RA networks, without incurring a bandwidth or energy penalty

Cooperative random access with long PN spreading codes

Cooperative wireless communication systems have attracted much attention in recent years, due to the diversity advantage they can afford. Existing cooperative transmission modalities have been developed in conjunction with fixed-rate multiplexing based on TDMA, CDMA or FDMA. We advocate user cooperation as the method of choice for enabling diversity in wireless random access networks. The specific protocol developed herein exploits the fact that user cooperation can be viewed as a form of multipath, and capitalizes on the suitability of long pseudo-noise (PN) spreading codes for dealing with multipath channels. Analysis and numerical results confirm that throughput increases considerably when random access via spread-spectrum slotted Aloha protocols is aided by user collaboration.