Asynchronous code-division random access using convex optimization

Abstract

Many applications in cellular systems and sensor networks involve a random subset of a large number of users asynchronously reporting activity to a base station. This paper examines the problem of multiuser detection (MUD) in random access channels for such applications. Traditional orthogonal signaling ignores the random nature of user activity in this problem and limits the total number of users to be on the order of the number of signal space dimensions. Contention-based schemes, on the other hand, suffer from delays caused by colliding transmissions and the hidden node problem. In contrast, this paper presents a novel pairing of an asynchronous non-orthogonal code-division random access scheme with a convex optimization-based MUD algorithm that overcomes the issues associated with orthogonal signaling and contention-based methods. Two key distinguishing features of the proposed MUD algorithm are that it does not require knowledge of the delay or channel state information of every user and it has polynomial-time computational complexity. The main analytical contribution of this paper is the relationship between the performance of the proposed MUD algorithm in the presence of arbitrary or random delays and two simple metrics of the set of user codewords. The study of these metrics is then focused on two specific sets of codewords, random binary codewords and specially constructed algebraic codewords, for asynchronous random access. The ensuing analysis confirms that the proposed scheme together with either of these two codeword sets significantly outperforms the orthogonal signaling-based random access in terms of the total number of users in the system.

Coping with CDMA Asynchronicity in Compressive Sensing Multi-User Detection

“…To exploit this knowledge, we propose a restricted version of the GOMP. This approach is different from [7], where neither group-sparsity nor the additional information limiting the valid activity combinations were exploited.…”

“…The principle approach of detecting delays in CS MUD is shown for a random on/off access channel (RACH) in [7]. We expand this idea and propose a modified CS detection that simultaneously detects activity, data and delay for all nodes.…”

Compressed Sensing soft activity processing for sparse multi-user systems

“…As stated in Section II, we assume a sporadic synchronous frame based medium access of the nodes parametrized by the per node activity probability p a . In the following we further assume that the nodes are synchronous at chip level, which is not a general restriction as shown in [18], [19]. Moreover perfect Channel State Information is assumed at the aggregation node, which could, e.g., be obtained via a training phase at the beginning of each frame [20] or by random coding inspired techniques as introduced in [21].…”

Reduced-Dimension Multiuser Detection

“…In many applications, the number of active users, K, can be much smaller than the total number of users, N [7], [8]. This analog signal sparsity allows the use of techniques from analog compressed sensing [9], [10] in order to reduce the number of correlators.…”

“…Our work also differs from prior results on compressed sensing for MUD, such as Applebaum et.al. [7] and Fletcher et.al. [8], [23], where a so-called on-off random access channel is considered.…”